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11. 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: identifying, by a processor of a computer in the one or more computers, one or more sessions for a query, each session comprising a chain of respective resources and linked to each other and watched by a respective user, each session beginning with a first resource that was identified by a first search result responsive to the query linked to one or more second resources, wherein each second resource was associated with a different resource in the session by a respective link, and wherein the user visited each second resource by following the links; associating a total of watch times of the respective resources watched in the sessions with the query; calculating one or more watch time signals for the first resource and the query based on the total of watch times associated with the query; after the one or more sessions have ended: receiving the query from a user; obtaining a search result responsive to the query, wherein the search result identifies the first resource and has an associated score S; calculating an updated score S′ based on at least S and a watch time function, the watch time function being a function of the one or more watch time signals; and providing the updated score S′ to a process for ranking search results including the first search result.

11. 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: identifying, by a processor of a computer in the one or more computers, one or more sessions for a query, each session comprising a chain of respective resources and linked to each other and watched by a respective user, each session beginning with a first resource that was identified by a first search result responsive to the query linked to one or more second resources, wherein each second resource was associated with a different resource in the session by a respective link, and wherein the user visited each second resource by following the links; associating a total of watch times of the respective resources watched in the sessions with the query; calculating one or more watch time signals for the first resource and the query based on the total of watch times associated with the query; after the one or more sessions have ended: receiving the query from a user; obtaining a search result responsive to the query, wherein the search result identifies the first resource and has an associated score S; calculating an updated score S′ based on at least S and a watch time function, the watch time function being a function of the one or more watch time signals; and providing the updated score S′ to a process for ranking search results including the first search result. 15. The system of claim 11 , wherein the watch time function is given by: S′=S×M Q,D i , wherein M Q,D i is a watch time multiplier computed from the one or more watch time signals for the query and the first resource.

29. A computer program product for distributing an electronic document, the computer program product being embodied in a non-transitory computer readable storage medium or memory device and comprising computer instructions for: maintaining the electronic document in a memory; associating with a copy of the electronic document one or more rights, wherein each of said rights defines an action capable of being performed on at least a portion of the copy of the electronic document; and providing the copy of the electronic document in a form that allows a first client to exercise the one or more rights associated with the copy of the electronic document, wherein one of the rights associated with the copy of the electronic document includes the ability of the first client to share with a second client rights to at least a portion of a body of content of the electronic document to enable the second client to access the shared content based on rights derived from the first client through an act of said sharing even if the second client is not otherwise entitled to access the shared content, and wherein said second client receives said at least a portion of said shared body of content from said central server only after the second client's rights to receive the shared content, as derived from the first client, are exercised by said second client such that the exercise of such rights by said second client directly causes the shared content to be delivered to the second client.

29. A computer program product for distributing an electronic document, the computer program product being embodied in a non-transitory computer readable storage medium or memory device and comprising computer instructions for: maintaining the electronic document in a memory; associating with a copy of the electronic document one or more rights, wherein each of said rights defines an action capable of being performed on at least a portion of the copy of the electronic document; and providing the copy of the electronic document in a form that allows a first client to exercise the one or more rights associated with the copy of the electronic document, wherein one of the rights associated with the copy of the electronic document includes the ability of the first client to share with a second client rights to at least a portion of a body of content of the electronic document to enable the second client to access the shared content based on rights derived from the first client through an act of said sharing even if the second client is not otherwise entitled to access the shared content, and wherein said second client receives said at least a portion of said shared body of content from said central server only after the second client's rights to receive the shared content, as derived from the first client, are exercised by said second client such that the exercise of such rights by said second client directly causes the shared content to be delivered to the second client. 30. The computer program product of claim 29 further comprising computer instructions for receiving information associated with the usage by the first client of the provided copy.

10. A fill-in form document completion system, comprising: a processing device; an image capturing device; one or more communications hardware components; and a non-transitory computer-readable medium containing programming instructions that are configured to cause the processing device to: receive, from the image capturing device, an image file of a printed form having at least one fill-in field that contains a handwritten symbol within a field boundary, process the image file to identify a fill-in field on the printed form and the handwritten symbol that is contained within the identified fill-in field, communicatively connect the system to a proximate user mobile device via the one or more communications hardware components, access a data file from the proximate user mobile device, wherein the data file comprises a plurality of categories and stored values, retrieve a candidate value that corresponds to the identified handwritten symbol by: identifying, from the data file, a category that corresponds to the handwritten symbol, extracting the stored value for the identified category from the data file, and using the extracted stored value as the candidate value, insert the candidate value in the identified fill-in field, and cause a document generation device to generate a document comprising the form with the selected candidate value displayed in the identified fill-in field.

10. A fill-in form document completion system, comprising: a processing device; an image capturing device; one or more communications hardware components; and a non-transitory computer-readable medium containing programming instructions that are configured to cause the processing device to: receive, from the image capturing device, an image file of a printed form having at least one fill-in field that contains a handwritten symbol within a field boundary, process the image file to identify a fill-in field on the printed form and the handwritten symbol that is contained within the identified fill-in field, communicatively connect the system to a proximate user mobile device via the one or more communications hardware components, access a data file from the proximate user mobile device, wherein the data file comprises a plurality of categories and stored values, retrieve a candidate value that corresponds to the identified handwritten symbol by: identifying, from the data file, a category that corresponds to the handwritten symbol, extracting the stored value for the identified category from the data file, and using the extracted stored value as the candidate value, insert the candidate value in the identified fill-in field, and cause a document generation device to generate a document comprising the form with the selected candidate value displayed in the identified fill-in field. 15. The system of claim 10 wherein: the image capturing device is a component of a multifunction device that further comprises an image scanner and a print device; the programming instructions are further configured to: cause the image scanner to capture the image of the printed form, and cause the processing device to generate the image file from the captured image; the instructions to cause the document generation device to generate the document comprising the form with the selected candidate value comprise instructions to cause the print device to print, on a substrate, the form with the selected candidate value displayed in the identified fill-in field.

1. A computer-implemented method for matching audio sequences, the method performed by a computer processor and comprising: deriving, by the computer processor, a first probability density function P M outputting a probability that an initial correspondence score for a pair of chroma vectors of an audio sequence indicates a semantic correspondence between the chroma vectors; deriving, by the computer processor, a second probability density function P R outputting a probability that the initial correspondence score for a pair of chroma vectors of an audio sequence indicates that the chroma vectors have a random correspondence, the deriving of P R comprising: randomly selecting a set of pairs of audio sequences; deriving initial correspondence scores for the set of pairs of audio sequences; and fitting the initial correspondence scores to a probability distribution; deriving, by the computer processorusing P M and P R , a match function indicating whether a given pair of chroma vectors of an audio sequence correspond semantically; obtaining a first audio sequence; comparing, by the computer processorusing the match function, the first audio sequence with a plurality of known audio sequences; and based on the comparing, identifying, by the computer processor, a best-matching audio sequence for the first audio sequence from the known audio sequences.

1. A computer-implemented method for matching audio sequences, the method performed by a computer processor and comprising: deriving, by the computer processor, a first probability density function P M outputting a probability that an initial correspondence score for a pair of chroma vectors of an audio sequence indicates a semantic correspondence between the chroma vectors; deriving, by the computer processor, a second probability density function P R outputting a probability that the initial correspondence score for a pair of chroma vectors of an audio sequence indicates that the chroma vectors have a random correspondence, the deriving of P R comprising: randomly selecting a set of pairs of audio sequences; deriving initial correspondence scores for the set of pairs of audio sequences; and fitting the initial correspondence scores to a probability distribution; deriving, by the computer processorusing P M and P R , a match function indicating whether a given pair of chroma vectors of an audio sequence correspond semantically; obtaining a first audio sequence; comparing, by the computer processorusing the match function, the first audio sequence with a plurality of known audio sequences; and based on the comparing, identifying, by the computer processor, a best-matching audio sequence for the first audio sequence from the known audio sequences. 2. The computer-implemented method of claim 1 , wherein the match function outputs, for an initial correspondence score for the given pair of chroma vectors, an indication of how much more likely it is that the given pair of chroma vectors correspond semantically than that the given pair of chroma vectors have a random correspondence.

1. A method for increasing the accuracy of optical character recognition (OCR) for at least one item, comprising: obtaining OCR results of OCR scanning from at least one OCR module; creating at least one OCR seed using at least a portion of the OCR results, the at least one OCR seed comprising a plurality of imagelets corresponding to each character identified in the at least a portion of the OCR results, wherein the at least one OCR seed is cleaned by selecting imagelets similar to one another for each character identified in the at least a portion of the OCR results; creating at least one OCR learn set using at least a portion of the OCR seed; comparing the at least one OCR learn set to each imagelet to create at least one mismatch distribution of the at least one OCR learn set compared to each imagelet, the at least one mismatch distribution comprising at least one confidence rating including a confidence score for the imagelet compared to at least one possible character; and applying the OCR learn set and the at least one mismatch distribution to the at least one item to obtain additional OCR results such that only possible characters having a confidence score higher than a threshold are considered when applying the at least one mismatch distribution to obtain the additional OCR results.

1. A method for increasing the accuracy of optical character recognition (OCR) for at least one item, comprising: obtaining OCR results of OCR scanning from at least one OCR module; creating at least one OCR seed using at least a portion of the OCR results, the at least one OCR seed comprising a plurality of imagelets corresponding to each character identified in the at least a portion of the OCR results, wherein the at least one OCR seed is cleaned by selecting imagelets similar to one another for each character identified in the at least a portion of the OCR results; creating at least one OCR learn set using at least a portion of the OCR seed; comparing the at least one OCR learn set to each imagelet to create at least one mismatch distribution of the at least one OCR learn set compared to each imagelet, the at least one mismatch distribution comprising at least one confidence rating including a confidence score for the imagelet compared to at least one possible character; and applying the OCR learn set and the at least one mismatch distribution to the at least one item to obtain additional OCR results such that only possible characters having a confidence score higher than a threshold are considered when applying the at least one mismatch distribution to obtain the additional OCR results. 8. The method of claim 1 , wherein the method is performed iteratively to allow for a refinement of the method.

1. A method comprising: receiving by one or more text processors, text from one or more text sources; converting, by the one or more text processors, the text into a plurality of intermediate logical statements that abstract over the syntactic form of information in the text; converting, by the one or more text processors using a semantic model, each intermediate logical statement into a semantic representation that equates intermediate logical statements having equivalent meanings such that the semantic model comprises a plurality of frames, each frame representing a relation or event and comprising one or more variables serving roles in the relation or event and each frame comprising one or more equivalent patterns, each pattern having a form of an intermediate logical statement including at least one variable and comprising a definition of a logical form that corresponds to a plurality of logically equivalent grammatical forms; sending, by one or more text processors, the semantic representation to a semantic database configured to store the semantic representation; receiving a query from a computing device; converting the query, by one or more query processors, connected to the semantic database into one or more semantic subqueries; matching, by the semantic database, each semantic subquery to stored semantic representations and joining results as appropriate to determine one or more answers to the query; sending, by the one or more query processors, the one or more answers to the computing device from which the query was received.

1. A method comprising: receiving by one or more text processors, text from one or more text sources; converting, by the one or more text processors, the text into a plurality of intermediate logical statements that abstract over the syntactic form of information in the text; converting, by the one or more text processors using a semantic model, each intermediate logical statement into a semantic representation that equates intermediate logical statements having equivalent meanings such that the semantic model comprises a plurality of frames, each frame representing a relation or event and comprising one or more variables serving roles in the relation or event and each frame comprising one or more equivalent patterns, each pattern having a form of an intermediate logical statement including at least one variable and comprising a definition of a logical form that corresponds to a plurality of logically equivalent grammatical forms; sending, by one or more text processors, the semantic representation to a semantic database configured to store the semantic representation; receiving a query from a computing device; converting the query, by one or more query processors, connected to the semantic database into one or more semantic subqueries; matching, by the semantic database, each semantic subquery to stored semantic representations and joining results as appropriate to determine one or more answers to the query; sending, by the one or more query processors, the one or more answers to the computing device from which the query was received. 3. The method of claim 1 , wherein the one or more text sources comprise at least one of: web pages and internal documents.

21. At least one non-transitory computer-readable storage medium comprising a plurality of programming instructions to enable an apparatus, in response to execution of the programming instructions, to: receive a search expression associated with a content item, wherein the search expression was generated based on the content item to evaluate or facilitate evaluation of probable effect of publication of the content item, wherein the content item is a selected one of a web page, a post to a social networking site, a post to a blog, a document, or an electronic message, having text divisible into sub-texts, and wherein the search expression includes a hierarchy of nested juxtaposition sub-expressions, wherein the nesting of the nested juxtaposition sub-expressions corresponds to nesting of the sub-texts; apply the search expression to other content items, including establishment of relevance geometries for the other content items, and generation of search scores for the other content items for the search expression having the hierarchy of nested juxtaposition sub-expressions, based at least in part on the relevance geometries; and evaluate, or cause to be evaluated, the content item to recommend publication or re-write at least a portion of the content item, wherein the evaluation being based at least in part on search scores of the other content items generated through application of the search expression having the hierarchy of nested juxtaposition sub-expressions.

21. At least one non-transitory computer-readable storage medium comprising a plurality of programming instructions to enable an apparatus, in response to execution of the programming instructions, to: receive a search expression associated with a content item, wherein the search expression was generated based on the content item to evaluate or facilitate evaluation of probable effect of publication of the content item, wherein the content item is a selected one of a web page, a post to a social networking site, a post to a blog, a document, or an electronic message, having text divisible into sub-texts, and wherein the search expression includes a hierarchy of nested juxtaposition sub-expressions, wherein the nesting of the nested juxtaposition sub-expressions corresponds to nesting of the sub-texts; apply the search expression to other content items, including establishment of relevance geometries for the other content items, and generation of search scores for the other content items for the search expression having the hierarchy of nested juxtaposition sub-expressions, based at least in part on the relevance geometries; and evaluate, or cause to be evaluated, the content item to recommend publication or re-write at least a portion of the content item, wherein the evaluation being based at least in part on search scores of the other content items generated through application of the search expression having the hierarchy of nested juxtaposition sub-expressions. 24. The computer-readable storage medium of claim 21 , wherein the instructions, in response to execution, cause the apparatus to evaluate the content item to recommend publication or re-write at least a portion of the content item, wherein the evaluation being based at least in part on search scores of the other content items generated through application of the search expression having the hierarchy of nested juxtaposition sub-expressions.

1. A method of creating a grammar for a natural language dialog system from a descriptor of a device, the method comprising: creating, on a computing device, instances of universal grammar rules for the natural-language dialog as a new grammar based on the device descriptor, the universal grammar rules including a plurality of selected domain objects, each of the selected domain objects including one or more attributes associated with the device, wherein the creating comprises: creating a bridging rule for each broad category of queries in the universal grammar rules; selectively including domain objects as domain objects in the new grammar; creating bridging rules for domain object attributes; and selectively including attributes in the new grammar; wherein the device descriptor specifies functions of the device that are available to an end user through the domain objects for implementing the grammar.

1. A method of creating a grammar for a natural language dialog system from a descriptor of a device, the method comprising: creating, on a computing device, instances of universal grammar rules for the natural-language dialog as a new grammar based on the device descriptor, the universal grammar rules including a plurality of selected domain objects, each of the selected domain objects including one or more attributes associated with the device, wherein the creating comprises: creating a bridging rule for each broad category of queries in the universal grammar rules; selectively including domain objects as domain objects in the new grammar; creating bridging rules for domain object attributes; and selectively including attributes in the new grammar; wherein the device descriptor specifies functions of the device that are available to an end user through the domain objects for implementing the grammar. 7. The method of claim 1 wherein the domain objects specify data transfer among networked devices and an interoperability of one or more network connections.

1. A computer-readable medium containing instructions for controlling a computer system to rank documents, by a method comprising: providing a sentence classifier to classify sentences into classifications of sentences; training a document rank classifier by representing each document of training data by the classifications of its sentences as determined by the sentence classifier and a rank of each document; representing a document by the classifications of its sentences as determined by the sentence classifier; and applying the trained document rank classifier to the representation of the document to determine the rank of the document.

1. A computer-readable medium containing instructions for controlling a computer system to rank documents, by a method comprising: providing a sentence classifier to classify sentences into classifications of sentences; training a document rank classifier by representing each document of training data by the classifications of its sentences as determined by the sentence classifier and a rank of each document; representing a document by the classifications of its sentences as determined by the sentence classifier; and applying the trained document rank classifier to the representation of the document to determine the rank of the document. 6. The computer-readable medium of claim 1 wherein the training includes applying an Ada-boosting algorithm.

1. A system for search engine optimization, comprising: several modules comprising smart tools that provide isolation and workflow collaboration of tools in a search engine optimization (SEO) suite; a first smart tool using log files for key-wordless rank checking; a second smart tool using log files for hyperlink analysis; a third smart tool identifying web authorities for competitive analysis; a fourth smart tool providing live relevancy metrics in on-page optimization editor; a fifth smart tool rotating authorization code to prevent usage of a software license in more than one computer; wherein more incoming links for a user website are extracted than querying search engines directly; wherein processing of website log files to identify every single internal page on the user website and external pages that are linking to each internal page; wherein an identification of every single internal page on the user website and external pages that are linking to each internal page is present in a referrer log file; and wherein extracted hyperlink information is used to identify link rich pages and link poor pages, wherein the link poor pages are less likely to be included in search engines index than the link rich pages.

1. A system for search engine optimization, comprising: several modules comprising smart tools that provide isolation and workflow collaboration of tools in a search engine optimization (SEO) suite; a first smart tool using log files for key-wordless rank checking; a second smart tool using log files for hyperlink analysis; a third smart tool identifying web authorities for competitive analysis; a fourth smart tool providing live relevancy metrics in on-page optimization editor; a fifth smart tool rotating authorization code to prevent usage of a software license in more than one computer; wherein more incoming links for a user website are extracted than querying search engines directly; wherein processing of website log files to identify every single internal page on the user website and external pages that are linking to each internal page; wherein an identification of every single internal page on the user website and external pages that are linking to each internal page is present in a referrer log file; and wherein extracted hyperlink information is used to identify link rich pages and link poor pages, wherein the link poor pages are less likely to be included in search engines index than the link rich pages. 5. The system for search engine optimization of claim 1 , further comprising a reporting engine wherein: users can define and create arbitrary reports using information provided by the smart tools at runtime; reports are defined with simple xml tags and the reporting engine extracts and combines required data from the smart tools; said reporting engine provides advanced filtering capability to limit a display of necessary information; the smart tools provide information to the reporting engine via record sets; said reporting engine receives a schema that specifies the information displayed on the report; and said reporting engine uses the schema to determine a data source, compile the data source to produce results, and generate and render reports that include text and graphics.

1. A method for parsing a domain-specific language (DSL) statement, the method comprising: accessing, by one or more processors, a DSL statement that includes contracted phrases; identifying, by one or more processors, one or more contracted phrases in the DSL statement utilizing an annotated domain vocabulary for a DSL associated with the DSL statement and grammar rules for the DSL; determining, by one or more processors, expanded phrases corresponding to the identified one or more contracted phrases based on the annotated domain vocabulary and the grammar rules; creating, by one or more processors, an expanded abstract syntax tree (AST) that is representative of the DSL statement with the determined expanded phrases replacing the identified one or more contracted phrases; determining, by one or more processors, whether the expanded AST includes any contracted phrases; and responsive to determining that the expanded AST does include contracted phrases, identifying, by one or more processors, one or more contracted phrases in the expanded AST utilizing the annotated domain vocabulary for the DSL and the grammar rules for the DSL.

1. A method for parsing a domain-specific language (DSL) statement, the method comprising: accessing, by one or more processors, a DSL statement that includes contracted phrases; identifying, by one or more processors, one or more contracted phrases in the DSL statement utilizing an annotated domain vocabulary for a DSL associated with the DSL statement and grammar rules for the DSL; determining, by one or more processors, expanded phrases corresponding to the identified one or more contracted phrases based on the annotated domain vocabulary and the grammar rules; creating, by one or more processors, an expanded abstract syntax tree (AST) that is representative of the DSL statement with the determined expanded phrases replacing the identified one or more contracted phrases; determining, by one or more processors, whether the expanded AST includes any contracted phrases; and responsive to determining that the expanded AST does include contracted phrases, identifying, by one or more processors, one or more contracted phrases in the expanded AST utilizing the annotated domain vocabulary for the DSL and the grammar rules for the DSL. 2. The method of claim 1 , wherein the identifying one or more contracted phrases in the DSL statement utilizing the annotated domain vocabulary for the DSL associated with the DSL statement and grammar rules for the DSL comprises: creating, by one or more processors, an AST that is representative of the DSL statement that includes contracted phrases; and identifying, by one or more processors, one or more contracted phrases in the created AST utilizing the annotated domain vocabulary for the DSL and the grammar rules for the DSL.

1. A computer-implemented method comprising: accessing a software code file that comprises structural code and behavioral code; extracting from the software code file, at least a portion of the behavioral code into a separate file; generating binding code for referencing the extracted behavioral code to maintain run-time behavior of the software code file consistent with its run-time behavior before said extracting, wherein behavioral code extractor logic inserts into the software code file said binding code for referencing the extracted behavioral code; and wherein said extracting comprises enabling, by a user interface, selection of one or more of identified behavioral code that is to be extracted from the software code file into the separate file; and extracting the selected one or more of the identified behavioral code from the software code file into the separate file.

1. A computer-implemented method comprising: accessing a software code file that comprises structural code and behavioral code; extracting from the software code file, at least a portion of the behavioral code into a separate file; generating binding code for referencing the extracted behavioral code to maintain run-time behavior of the software code file consistent with its run-time behavior before said extracting, wherein behavioral code extractor logic inserts into the software code file said binding code for referencing the extracted behavioral code; and wherein said extracting comprises enabling, by a user interface, selection of one or more of identified behavioral code that is to be extracted from the software code file into the separate file; and extracting the selected one or more of the identified behavioral code from the software code file into the separate file. 2. The method of claim 1 wherein said accessing, extracting, and generating are performed by behavioral code extractor logic.

1. A method for converting both a tabbed table in an XML format and a collapsible section in the XML format to forms configured for storage in a relational database and use by a web-based application, said method comprising: converting, by a processor of a computing device, unstructured rich text information to XML files in the XML format, wherein the unstructured rich text information comprises the tabbed table as unstructured rich text and the collapsible section as unstructured rich text, wherein the tabbed table is a first type of unstructured rich text information that is tabbed table specific, wherein the collapsible section is a second type of unstructured rich text information that is collapsible section specific, and wherein the XML files in the XML format comprise the tabbed table in the XML format and the collapsible section in the XML format; transforming, by the processor using a first reusable stylesheet that is specific to the first type of unstructured rich text information that is tabbed table specific, the tabbed table in the XML format to an XHTML format configured for storage in the relational database by creating a parent, table object, creating a body for the parent table object to form a container including cells for the tabbed table and creating children of the parent, table object to record information contents of the cells in the container; initiating, by the processor, storage of the tabbed table object, including the body of the parent table object and the children of the parent table object, in the XHTML format in the relational database; subsequently exporting, by the processor, the tabbed table, including the body of the parent table object and the children of the parent table object, in the XHMTL format from the relational database to the web-based application; transforming, by the processor using a second reusable stylesheet that is specific to the second type of unstructured rich text information that is collapsible section specific, the collapsible section in the XML format to an XHTML format configured for storage in the relational database by creating a parent, collapsed object and creating children of the parent, collapsed object to record information content of an uncollapsed form of the collapsed parent object; initiating, by the processor, storage of the collapsible section in the XHTML format in the relational database; and subsequently exporting, by the processor, the collapsible section in the XHMTL format from the relational database to the web-based application.

1. A method for converting both a tabbed table in an XML format and a collapsible section in the XML format to forms configured for storage in a relational database and use by a web-based application, said method comprising: converting, by a processor of a computing device, unstructured rich text information to XML files in the XML format, wherein the unstructured rich text information comprises the tabbed table as unstructured rich text and the collapsible section as unstructured rich text, wherein the tabbed table is a first type of unstructured rich text information that is tabbed table specific, wherein the collapsible section is a second type of unstructured rich text information that is collapsible section specific, and wherein the XML files in the XML format comprise the tabbed table in the XML format and the collapsible section in the XML format; transforming, by the processor using a first reusable stylesheet that is specific to the first type of unstructured rich text information that is tabbed table specific, the tabbed table in the XML format to an XHTML format configured for storage in the relational database by creating a parent, table object, creating a body for the parent table object to form a container including cells for the tabbed table and creating children of the parent, table object to record information contents of the cells in the container; initiating, by the processor, storage of the tabbed table object, including the body of the parent table object and the children of the parent table object, in the XHTML format in the relational database; subsequently exporting, by the processor, the tabbed table, including the body of the parent table object and the children of the parent table object, in the XHMTL format from the relational database to the web-based application; transforming, by the processor using a second reusable stylesheet that is specific to the second type of unstructured rich text information that is collapsible section specific, the collapsible section in the XML format to an XHTML format configured for storage in the relational database by creating a parent, collapsed object and creating children of the parent, collapsed object to record information content of an uncollapsed form of the collapsed parent object; initiating, by the processor, storage of the collapsible section in the XHTML format in the relational database; and subsequently exporting, by the processor, the collapsible section in the XHMTL format from the relational database to the web-based application. 3. The method of claim 1 , wherein the unstructured rich text information further comprises twisties as unstructured rich text, wherein the twisties is a third type of unstructured rich text information that is twisties specific, wherein the XML files in the XML format further comprise the twisties in the XML format, and wherein the method further comprises: transforming, by the processor using a third reusable stylesheet that is specific to the third type of unstructured rich text information that is twisties specific, the twisties in the XML format to an XHTML format configured for storage in the relational database.

1. A method of providing a language interpretation service, comprising: providing a language access telephone number that a caller speaking a first language and having a business need dials to place a telephone call to a language interpretation service to obtain language interpretation assistance; receiving a language access telephone call at the language interpretation service provider from the caller; identifying, after the telephone call is initiated, the first language from a plurality of languages with a voice recognition system so as to provide the caller with an interpreter that can translate between the first language and a second language, wherein the interpreter is associated with the language interpretation service provider; and permitting the interpreter to telephonically engage an agent representing a merchant that can serve the business need of the caller, wherein the agent speaks the second language and the interpreter translates a conversation between the caller and the agent.

1. A method of providing a language interpretation service, comprising: providing a language access telephone number that a caller speaking a first language and having a business need dials to place a telephone call to a language interpretation service to obtain language interpretation assistance; receiving a language access telephone call at the language interpretation service provider from the caller; identifying, after the telephone call is initiated, the first language from a plurality of languages with a voice recognition system so as to provide the caller with an interpreter that can translate between the first language and a second language, wherein the interpreter is associated with the language interpretation service provider; and permitting the interpreter to telephonically engage an agent representing a merchant that can serve the business need of the caller, wherein the agent speaks the second language and the interpreter translates a conversation between the caller and the agent. 13. The method of claim 1 , wherein the first language is English, Spanish, German, French, or Chinese.

7. The computer-implemented method of claim 1 , wherein the at least one metric comprises a phone-based metric for identifying phones in the plurality of words.

7. The computer-implemented method of claim 1 , wherein the at least one metric comprises a phone-based metric for identifying phones in the plurality of words. 9. The computer-implemented method of claim 7 , wherein said controlling step comprises temporarily reducing a presentation rate of the plurality of words responsive to an amount of the phones in one or more words being above the threshold.

8. A system for correcting words in transcribed text, the system comprising: an automated speech recognizer operable to receive speech audio data and in response transcribe the speech audio data in a word lattice; and a computing device comprising: a microphone operable to receive speech audio and generate the speech audio data, a network interface operable to send the speech audio data to the automated speech recognizer and in response receive the word lattice from the automated speech recognizer, a display screen operable to present one or more transcribed words from the word lattice, a user interface operable to receive a user selection of at least one of the transcribed words, and one or more processors and a memory storing instructions that when executed by the processors cause the computing device to perform operations to: provide a transcription of an utterance for output in an output region of a display of a computing device; receive a user selection of a portion of the transcription of the utterance, the user-selected portion of the transcription of the utterance comprising one or more words; in response to receiving the user selection of the portion of the transcription of the utterance, present one or more controls at the display of the computing device that each correspond to (i) one or more alternate words for the user-selected portion of the transcription of the utterance or (ii) a remove command to remove the user-selected portion of the transcription of the utterance from the transcription of the utterance; receive a user selection of a particular control from among the one or more controls; and update the transcription of the utterance output in the output region of the display of the computing device based at least on the user selection of the particular control.

8. A system for correcting words in transcribed text, the system comprising: an automated speech recognizer operable to receive speech audio data and in response transcribe the speech audio data in a word lattice; and a computing device comprising: a microphone operable to receive speech audio and generate the speech audio data, a network interface operable to send the speech audio data to the automated speech recognizer and in response receive the word lattice from the automated speech recognizer, a display screen operable to present one or more transcribed words from the word lattice, a user interface operable to receive a user selection of at least one of the transcribed words, and one or more processors and a memory storing instructions that when executed by the processors cause the computing device to perform operations to: provide a transcription of an utterance for output in an output region of a display of a computing device; receive a user selection of a portion of the transcription of the utterance, the user-selected portion of the transcription of the utterance comprising one or more words; in response to receiving the user selection of the portion of the transcription of the utterance, present one or more controls at the display of the computing device that each correspond to (i) one or more alternate words for the user-selected portion of the transcription of the utterance or (ii) a remove command to remove the user-selected portion of the transcription of the utterance from the transcription of the utterance; receive a user selection of a particular control from among the one or more controls; and update the transcription of the utterance output in the output region of the display of the computing device based at least on the user selection of the particular control. 10. The system of claim 8 , wherein the transcription of the utterance is a transcription of the utterance that has a highest probability of being correct.

17. A method comprising: identifying a table of contents in a document including of an ordered sequence of indexing text fragments and an ordered sequence of body text fragments by: associating a lower-ordered indexing text fragment with a set of one or more candidate linked body text fragments at lower order in the ordered sequence of body text fragments than a highest order candidate linked body text fragment associated with a set of N contiguous indexing text fragments at higher order and abutting the lower-ordered indexing text fragment in the ordered sequence of indexing text fragments; associating a higher-ordered indexing text fragment with a set of one or more candidate linked body text fragments at higher order in the ordered sequence of body text fragments than a lowest order candidate linked body text fragment associated with a set of M contiguous indexing text fragments at lower order and abutting the higher-ordered indexing text fragment ordered sequence of indexing text fragments; decrementing the order of the lower-ordered indexing text fragment; incrementing the order of the higher-ordered indexing text fragment; repeating the associating of the lower-ordered indexing text fragment, the associating of the higher-ordered indexing text fragment, the decrementing, and the incrementing to generate sets of one or more candidate linked body text fragments associated with the indexing text fragments; and optimizing the candidate linked body text fragments to identify the table of contents including indexing text fragments each linked to a body text fragment.

17. A method comprising: identifying a table of contents in a document including of an ordered sequence of indexing text fragments and an ordered sequence of body text fragments by: associating a lower-ordered indexing text fragment with a set of one or more candidate linked body text fragments at lower order in the ordered sequence of body text fragments than a highest order candidate linked body text fragment associated with a set of N contiguous indexing text fragments at higher order and abutting the lower-ordered indexing text fragment in the ordered sequence of indexing text fragments; associating a higher-ordered indexing text fragment with a set of one or more candidate linked body text fragments at higher order in the ordered sequence of body text fragments than a lowest order candidate linked body text fragment associated with a set of M contiguous indexing text fragments at lower order and abutting the higher-ordered indexing text fragment ordered sequence of indexing text fragments; decrementing the order of the lower-ordered indexing text fragment; incrementing the order of the higher-ordered indexing text fragment; repeating the associating of the lower-ordered indexing text fragment, the associating of the higher-ordered indexing text fragment, the decrementing, and the incrementing to generate sets of one or more candidate linked body text fragments associated with the indexing text fragments; and optimizing the candidate linked body text fragments to identify the table of contents including indexing text fragments each linked to a body text fragment. 18. A method as set forth in claim 17 , wherein N=M.

1. An information processing device implementing a document conversion and use system which converts a first structured document into a second structured document different in structure from the first structured document, comprising: a template storage device configured to store a template indicating the structure of the second structured document and described in a same language with the second structured document; and a processing unit including a structure specification unit configured to read the template from the template storage device, display a design represented by the read template on a screen of a display device, and specify an element or an element content configuring the template in the displayed design; a correspondence definition specification unit configured to define a correspondence definition indicating correspondence between an element in the first structured document and an element in the template by corresponding a tag of a element in the first structured document with a position of the specified element or element content in the displayed design; a structured document analysis unit configured to convert the template and the first structured document into tree structure objects, respectively; a search unit configured to search the element or the element content specified by the structure specification unit from the tree structure object of the template, sequentially search the element described in the correspondence definition from the searched element or element content in the tree structure object of the template as a start point, generate a tree structure object of the template which comprises the element sequentially-searched element, and search an element described in the correspondence definition from the tree structure object of the first structured document; and a conversion processing unit configured to, when the element detected by searching from the tree structure object of the first structured document having a child element and a corresponding element in the template having a parent element defined by the correspondence definition specification unit, enter the generated tree structure of the template into the tree object of the template according to the number of child elements, and when the element detected by searching from the tree structure object of the first structured document having only an element content and a corresponding element in the template having no child element, replace the element content of the detected element with the specified element content in the template.

1. An information processing device implementing a document conversion and use system which converts a first structured document into a second structured document different in structure from the first structured document, comprising: a template storage device configured to store a template indicating the structure of the second structured document and described in a same language with the second structured document; and a processing unit including a structure specification unit configured to read the template from the template storage device, display a design represented by the read template on a screen of a display device, and specify an element or an element content configuring the template in the displayed design; a correspondence definition specification unit configured to define a correspondence definition indicating correspondence between an element in the first structured document and an element in the template by corresponding a tag of a element in the first structured document with a position of the specified element or element content in the displayed design; a structured document analysis unit configured to convert the template and the first structured document into tree structure objects, respectively; a search unit configured to search the element or the element content specified by the structure specification unit from the tree structure object of the template, sequentially search the element described in the correspondence definition from the searched element or element content in the tree structure object of the template as a start point, generate a tree structure object of the template which comprises the element sequentially-searched element, and search an element described in the correspondence definition from the tree structure object of the first structured document; and a conversion processing unit configured to, when the element detected by searching from the tree structure object of the first structured document having a child element and a corresponding element in the template having a parent element defined by the correspondence definition specification unit, enter the generated tree structure of the template into the tree object of the template according to the number of child elements, and when the element detected by searching from the tree structure object of the first structured document having only an element content and a corresponding element in the template having no child element, replace the element content of the detected element with the specified element content in the template. 2. The information processing device implementing the document conversion and use system according to claim 1 , wherein the structure specification unit displays the template read from the template storage device, and allows a user to specify on a display screen an element or an element content configuring the template.

3. The method of claim 1 , wherein the condition for a predicate is specified by an operator and the respective predicate value.

3. The method of claim 1 , wherein the condition for a predicate is specified by an operator and the respective predicate value. 4. The method of claim 3 , wherein updating the predicate value of at least one predicate includes: updating the respective predicate value of the at least one predicate with an accessed data value based on accessed data satisfying the condition of the at least one predicate.

1. In a computer-implemented contact center enabling a user to create and launch on demand, automated outbound interactive voice calls to contacts based on a user-provided call script, a non-transitory computer-readable medium having program code embodied therein configured to cause the execution of the following steps: a. Providing a website application accessible by the user via a user computer equipped with a web browser, the website application comprising a visual user interface for a contact center, b. Prompting the user to create a user account for accessing and using the contact center by providing user information comprising a user password, c. Providing contact information comprising contact phone numbers, the contact information stored in a contact information database on a data server of the service provider of the contact center and accessible to the user via the user's account, d. Prompting the user to optionally input custom answers per a user-generated call script where the call script comprises at least one question anticipating a custom answer from a contact, the custom answers to be recognized b a speech application, e. Providing a built-in audio recording capability enabling the user to record and save voice recordings for each event of the call script, f. Via an Event Add Wizard and Logic Add Wizard, enabling the user to build and save a call sequence based on the call script by pointing and clicking to successively add previously saved prompts of each message event and each question event of the call script and a logic for controlling the sequencing of events dependent upon the contact's response to a question event, g. Providing a Transfer to Live Attendant functionality whereby the user optionally adds a Transfer to Live Attendant Event into a call sequence during the call sequence creation step f, the transfer to Live Attendant Event causing the call to be automatically transferred to a user-provided phone number upon a specified contact response to a question event in the call sequence, h. Creating a broadcast, the broadcast defined by a saved call sequence and a plurality of contacts who are the intended recipients of a call based on the call sequence, i. Launching the broadcast, j. Automatically capturing and saving exportable audio recordings of contact voice responses to open-ended questions in the call sequence, where the call script comprises at least one open-ended question, and k. Providing one or more reports comprising information from contact responses to question events in the call sequence of the broadcast.

1. In a computer-implemented contact center enabling a user to create and launch on demand, automated outbound interactive voice calls to contacts based on a user-provided call script, a non-transitory computer-readable medium having program code embodied therein configured to cause the execution of the following steps: a. Providing a website application accessible by the user via a user computer equipped with a web browser, the website application comprising a visual user interface for a contact center, b. Prompting the user to create a user account for accessing and using the contact center by providing user information comprising a user password, c. Providing contact information comprising contact phone numbers, the contact information stored in a contact information database on a data server of the service provider of the contact center and accessible to the user via the user's account, d. Prompting the user to optionally input custom answers per a user-generated call script where the call script comprises at least one question anticipating a custom answer from a contact, the custom answers to be recognized b a speech application, e. Providing a built-in audio recording capability enabling the user to record and save voice recordings for each event of the call script, f. Via an Event Add Wizard and Logic Add Wizard, enabling the user to build and save a call sequence based on the call script by pointing and clicking to successively add previously saved prompts of each message event and each question event of the call script and a logic for controlling the sequencing of events dependent upon the contact's response to a question event, g. Providing a Transfer to Live Attendant functionality whereby the user optionally adds a Transfer to Live Attendant Event into a call sequence during the call sequence creation step f, the transfer to Live Attendant Event causing the call to be automatically transferred to a user-provided phone number upon a specified contact response to a question event in the call sequence, h. Creating a broadcast, the broadcast defined by a saved call sequence and a plurality of contacts who are the intended recipients of a call based on the call sequence, i. Launching the broadcast, j. Automatically capturing and saving exportable audio recordings of contact voice responses to open-ended questions in the call sequence, where the call script comprises at least one open-ended question, and k. Providing one or more reports comprising information from contact responses to question events in the call sequence of the broadcast. 13. The on-transitory computer-readable medium per claim 1 further comprising program code configured to execute a contact authentication step whereby the contact's response to an authentication question of a call sequence in a broadcast is automatically verified against an expected response, the expected response pre-defined in the contact information database for the contact.

1. A system comprising: a processor and a computer readable memory, wherein the processor retrieves and executes instructions from the computer readable memory to perform a processor-implemented method comprising; receiving a reading speed of a reader, wherein the reader is a human reader, wherein the reading speed is based on a first source; determining a summary length of a summary of a document based on the received reading speed of the reader, wherein the document is a second source that differs from the first source, wherein a first reading speed is faster than a second reading speed, wherein the first reading speed results in a first summary length of the summary and the second reading speed results in a second summary length of the summary, and wherein the first summary length is longer than the second summary length; generating a summary of the document having the determined summary length; identifying an interest of the reader; modifying the summary of the document according to the interest of the reader in order to include, in the summary of the document, content from the document that is of interest to the reader, wherein the reader has multiple interests; weighting each interest from the multiple interests based on a reading history of the reader, wherein each interest is assigned a weight based on a percentage of the reading history of the reader that is devoted to said each interest; generating a weight ratio of interests of the reader from the multiple interests based on the percentage of the reading history of the reader that is devoted to said each interest; generating components of the summary based on the weight ratio of interests of the reader; and modifying the summary of the document to match the weight ratio such that a ratio of lengths of the components of the summary matches the weight ratio of the interests of the reader.

1. A system comprising: a processor and a computer readable memory, wherein the processor retrieves and executes instructions from the computer readable memory to perform a processor-implemented method comprising; receiving a reading speed of a reader, wherein the reader is a human reader, wherein the reading speed is based on a first source; determining a summary length of a summary of a document based on the received reading speed of the reader, wherein the document is a second source that differs from the first source, wherein a first reading speed is faster than a second reading speed, wherein the first reading speed results in a first summary length of the summary and the second reading speed results in a second summary length of the summary, and wherein the first summary length is longer than the second summary length; generating a summary of the document having the determined summary length; identifying an interest of the reader; modifying the summary of the document according to the interest of the reader in order to include, in the summary of the document, content from the document that is of interest to the reader, wherein the reader has multiple interests; weighting each interest from the multiple interests based on a reading history of the reader, wherein each interest is assigned a weight based on a percentage of the reading history of the reader that is devoted to said each interest; generating a weight ratio of interests of the reader from the multiple interests based on the percentage of the reading history of the reader that is devoted to said each interest; generating components of the summary based on the weight ratio of interests of the reader; and modifying the summary of the document to match the weight ratio such that a ratio of lengths of the components of the summary matches the weight ratio of the interests of the reader. 16. The system of claim 1 , wherein the processor-implemented method further comprises: determining the reading speed of the reader based on a length of time that the reader stays on a first webpage having a known number of words before switching to a second webpage.

13. A non-transitory computer-readable medium containing computer program code that, when executed, performs an operation, comprising: generating a data model for a first conversational gesture type, by analyzing captured video data to determine motion attribute data for a plurality of conversational gestures; upon receiving a request to splice a gesture of the first conversational gesture type into a first animation, determining a locomotion of a first virtual character, while the first virtual character is interacting with a second virtual character within the first animation; stylizing a gesture of the first conversational gesture type to match style criteria associated with the locomotion of the first virtual character based on the motion attribute data of the generated data model for the first conversational gesture type; and splicing the stylized gesture into the locomotion of the first virtual character within the first animation.

13. A non-transitory computer-readable medium containing computer program code that, when executed, performs an operation, comprising: generating a data model for a first conversational gesture type, by analyzing captured video data to determine motion attribute data for a plurality of conversational gestures; upon receiving a request to splice a gesture of the first conversational gesture type into a first animation, determining a locomotion of a first virtual character, while the first virtual character is interacting with a second virtual character within the first animation; stylizing a gesture of the first conversational gesture type to match style criteria associated with the locomotion of the first virtual character based on the motion attribute data of the generated data model for the first conversational gesture type; and splicing the stylized gesture into the locomotion of the first virtual character within the first animation. 14. The non-transitory computer-readable medium of claim 13 , the operation further comprising: determining a gaze of the virtual character within the first animation, wherein splicing the gesture of the first conversational gesture type into the first animation, using the generated data model, is further based on the determined gaze of the virtual character.

1. A system comprising: a. a security system; b. a first aerial drone device configured to acquire content and communicate with the security system including receiving trigger location information from the security system; and c. a second aerial drone device configured to acquire the content and communicate with the security system including receiving the trigger location information from the security system, wherein the first aerial drone device is configured to physically nest within the second aerial drone device, wherein the first aerial drone device and the second aerial drone device are each configured to acquire separate information by traveling in different directions, wherein the second aerial drone device includes a shielding component configured to protect the second aerial drone device, wherein the shielding component includes one or more extendible wings.

1. A system comprising: a. a security system; b. a first aerial drone device configured to acquire content and communicate with the security system including receiving trigger location information from the security system; and c. a second aerial drone device configured to acquire the content and communicate with the security system including receiving the trigger location information from the security system, wherein the first aerial drone device is configured to physically nest within the second aerial drone device, wherein the first aerial drone device and the second aerial drone device are each configured to acquire separate information by traveling in different directions, wherein the second aerial drone device includes a shielding component configured to protect the second aerial drone device, wherein the shielding component includes one or more extendible wings. 7. The system of claim 1 wherein at least one of the first aerial drone device and the second aerial drone device includes: a storage compartment configured to store a net, paint, pepper spray or a tracking device, wherein the tracking device is deployed by the at least one of the first aerial drone device and the second aerial drone device by dropping the tracking device onto an object and tracking the tracking device.

9. A system for predicting a future event associated with a business based on historical data associated with a model of past events of the business, comprising: a processor; and a memory in communication with the processor, the memory storing a plurality of processing instructions for directing the processor to: obtain a plurality of modeling variables associated with the model, a dependent variable associated with the model and dependent on the plurality of modeling variables, and the historical data associated with the model; perform a transformation of the plurality of modeling variables to obtain a linear relationship of each of the plurality of modeling variables in relation to the dependent variable; select a subset of the plurality of transformed modeling variables, wherein the selecting comprises applying a selecting rule based on at least one of: (i) a correlation between a transformed variable and the dependent variable, and (ii) a proportion of a range of the dependent variable explained by the transformed variable; or a selection rule based on a log-likelihood difference; determine a set of prediction variables, wherein the determining is based on a regression of the subset of the plurality of transformed variables; and generate a predictive model using the prediction variables obtained from the regression, wherein the predictive model is used by the system to predict the future event.

9. A system for predicting a future event associated with a business based on historical data associated with a model of past events of the business, comprising: a processor; and a memory in communication with the processor, the memory storing a plurality of processing instructions for directing the processor to: obtain a plurality of modeling variables associated with the model, a dependent variable associated with the model and dependent on the plurality of modeling variables, and the historical data associated with the model; perform a transformation of the plurality of modeling variables to obtain a linear relationship of each of the plurality of modeling variables in relation to the dependent variable; select a subset of the plurality of transformed modeling variables, wherein the selecting comprises applying a selecting rule based on at least one of: (i) a correlation between a transformed variable and the dependent variable, and (ii) a proportion of a range of the dependent variable explained by the transformed variable; or a selection rule based on a log-likelihood difference; determine a set of prediction variables, wherein the determining is based on a regression of the subset of the plurality of transformed variables; and generate a predictive model using the prediction variables obtained from the regression, wherein the predictive model is used by the system to predict the future event. 12. The system of claim 9 , further comprising instructions for directing the processor to: automatically cluster the transformed modeling variables; and select the set of variables from the variable clusters based on the selection rule.

5. The method of claim 1 , wherein if determining the confidence rating associated with each of the plurality of spoken utterances produces confidence ratings that are below a predefined threshold then reclassifying the plurality of spoken utterances with new classifications based on at least two different classification operations.

5. The method of claim 1 , wherein if determining the confidence rating associated with each of the plurality of spoken utterances produces confidence ratings that are below a predefined threshold then reclassifying the plurality of spoken utterances with new classifications based on at least two different classification operations. 6. The method of claim 5 , wherein the at least two different classification operations comprise at least one of generating a list of the three highest classification confidence levels among the plurality of utterances, performing a Naïve-Bayes classification operation on the plurality of spoken utterances, and performing a decision tree classification on the plurality of spoken utterances.

1. In a computing environment, a method of representing structured data extracted from unstructured data in a fashion which allows querying using relational database concepts, the method comprising: receiving user input specifying one or more database views; receiving user input specifying an information extraction technique, the information extraction technique defining how to extract structured data from unstructured data and the information extraction technique comprising a phrase semantic extraction technique which determines a semantic relationship about one or more words based upon a semantic environment of the one or more words; receiving user input specifying a corpus of data comprising unstructured data, the unstructured data comprising data that is not organized semantically such that it does not have a formalized type and is not in a formal entity level relationship; and applying the extraction technique to the corpus of data to extract structured data from the unstructured data of the corpus of data and to produce the one or more database views including the extracted structured data.

1. In a computing environment, a method of representing structured data extracted from unstructured data in a fashion which allows querying using relational database concepts, the method comprising: receiving user input specifying one or more database views; receiving user input specifying an information extraction technique, the information extraction technique defining how to extract structured data from unstructured data and the information extraction technique comprising a phrase semantic extraction technique which determines a semantic relationship about one or more words based upon a semantic environment of the one or more words; receiving user input specifying a corpus of data comprising unstructured data, the unstructured data comprising data that is not organized semantically such that it does not have a formalized type and is not in a formal entity level relationship; and applying the extraction technique to the corpus of data to extract structured data from the unstructured data of the corpus of data and to produce the one or more database views including the extracted structured data. 12. The method of claim 1 , wherein the one or more views represent a graph.

1. A web site system capable of rescuing invalid URLs included in URL request messages, the system comprising: a data repository that stores supplemental product information for different products, the product relationship information including a product identifier for a first product and supplemental product information for the first product; and a web server system for a website in communication with the data repository, said web server system comprising one or more computing devices, wherein the web server system is responsive to at least some invalid URLs received from a user computing device by: identifying a first product identifier referenced in an invalid URL referencing content not found on the website, the invalid URL including a domain name of the web server system and the first product identifier, said first product identifier corresponding uniquely to a first product; determining the first product identifier from the invalid URL; obtaining from the data repository supplemental product information for the first product using the first product identifier; determining from the supplemental product information that the first product has been superseded by a second product, said second product being different than the first product; determining that the second product is offered on the website; and at least partly in response to determining the second product is offered, providing to the user computing device a page having content associated with the second product, the page having a second URL including a second product identifier and the domain name of the web server system.

1. A web site system capable of rescuing invalid URLs included in URL request messages, the system comprising: a data repository that stores supplemental product information for different products, the product relationship information including a product identifier for a first product and supplemental product information for the first product; and a web server system for a website in communication with the data repository, said web server system comprising one or more computing devices, wherein the web server system is responsive to at least some invalid URLs received from a user computing device by: identifying a first product identifier referenced in an invalid URL referencing content not found on the website, the invalid URL including a domain name of the web server system and the first product identifier, said first product identifier corresponding uniquely to a first product; determining the first product identifier from the invalid URL; obtaining from the data repository supplemental product information for the first product using the first product identifier; determining from the supplemental product information that the first product has been superseded by a second product, said second product being different than the first product; determining that the second product is offered on the website; and at least partly in response to determining the second product is offered, providing to the user computing device a page having content associated with the second product, the page having a second URL including a second product identifier and the domain name of the web server system. 5. The system of claim 1 , wherein the second product identifier uniquely corresponds to the second product.

8. A system for identifying documents that represent similar information to train a text-to-text application, the system comprising: a database including a group of documents; a processor that determines reduced size versions of the documents and compares the reduced size versions to determine documents within the group that represent similar information, wherein the reduced size versions summarize information about words contained in the documents; and a text-to-text application module stored in memory and executable to use the documents that represent similar information for training a text-to-text application, wherein the text-to-text application is executable to carry out a rough translation to a second language of documents in the group to form a group of translated documents, and to compare the group of translated documents to other documents prior to determining the documents that represent similar information.

8. A system for identifying documents that represent similar information to train a text-to-text application, the system comprising: a database including a group of documents; a processor that determines reduced size versions of the documents and compares the reduced size versions to determine documents within the group that represent similar information, wherein the reduced size versions summarize information about words contained in the documents; and a text-to-text application module stored in memory and executable to use the documents that represent similar information for training a text-to-text application, wherein the text-to-text application is executable to carry out a rough translation to a second language of documents in the group to form a group of translated documents, and to compare the group of translated documents to other documents prior to determining the documents that represent similar information. 12. The system of claim 8 wherein the text-to-text application is executable to form vectors indicative of the documents, and compares the vectors.

1. A method for generating a word sequence for a passcode on a computer system, comprising: choosing a schema to guide the generation of the word sequence, wherein the schema comprises a set of pre-determined words; dividing the passcode into a plurality of bit groups, wherein a first bit group of the plurality of bit groups determines the schema chosen; selecting a set of words from a word category, wherein the word category corresponds to the schema, and wherein the word sequence comprises the set of pre-determined words and the set of words from the word category; and transforming the passcode into the word sequence using the schema and storing the word sequence on a storage medium readable by the computer system, wherein the word sequence contains mnemonic structure.

1. A method for generating a word sequence for a passcode on a computer system, comprising: choosing a schema to guide the generation of the word sequence, wherein the schema comprises a set of pre-determined words; dividing the passcode into a plurality of bit groups, wherein a first bit group of the plurality of bit groups determines the schema chosen; selecting a set of words from a word category, wherein the word category corresponds to the schema, and wherein the word sequence comprises the set of pre-determined words and the set of words from the word category; and transforming the passcode into the word sequence using the schema and storing the word sequence on a storage medium readable by the computer system, wherein the word sequence contains mnemonic structure. 17. The method of claim 1 , wherein the passcode corresponds to an encryption key.

1. A method for making and displaying predictions about a business location, comprising the steps of: providing, from a data source, heterogeneous data including a spatial component and an interface resource, the interface resource being hardware, for enabling output of the predictions; extracting entities from the heterogeneous data; clustering the entities to form a population of entities; and making and displaying a prediction about the business location using the population of entities.

1. A method for making and displaying predictions about a business location, comprising the steps of: providing, from a data source, heterogeneous data including a spatial component and an interface resource, the interface resource being hardware, for enabling output of the predictions; extracting entities from the heterogeneous data; clustering the entities to form a population of entities; and making and displaying a prediction about the business location using the population of entities. 11. A method as set forth in claim 1 , wherein the step of comparing compares a population of entities from the business location with a population of entities from another business location.

11. The method of claim 5 further comprising the step of periodically recording a replacement plurality of recorded messages onto the storage device.

11. The method of claim 5 further comprising the step of periodically recording a replacement plurality of recorded messages onto the storage device. 13. The method of claim 11 , the replacement plurality of recorded messages being recorded onto the storage device by the user.

25. A data processing system comprising: a display device; a processor system; a memory coupled to the processor system and to the display device, wherein the processor causes the display device to display a single text input field which, through a first input to the text input field itself, can select between at least a first operation and a second operation and wherein the processor system causes the display device to display a separator within the text input field and wherein a first portion and a second portion of the text input field are separated by the separator and wherein the processor system receives the first input to the single text input field to determine a selected operation which is one of the first operation or the second operation and the processor system receives a text input in the single text input field, the text input being displayable in the entire single text input field and performs the selected operation on the text input wherein the first input comprises receiving a user input in either the first portion or the second portion of the text input field, wherein the first operation is selected if the user input is positioned in the first portion when the user input is received and wherein the second operation is selected if the user input is positioned in the second portion when the user input is received, wherein the first operation is a text search through a first source of data and wherein the second operation is either a file operation or a search operation that is different than the first operation, and wherein in response to the first input, the separator automatically disappears from the text input field and the first portion dominates the entire area of the text input field if the first operation is selected and the second portion dominates the entire area of the text input field if the second operation is selected.

25. A data processing system comprising: a display device; a processor system; a memory coupled to the processor system and to the display device, wherein the processor causes the display device to display a single text input field which, through a first input to the text input field itself, can select between at least a first operation and a second operation and wherein the processor system causes the display device to display a separator within the text input field and wherein a first portion and a second portion of the text input field are separated by the separator and wherein the processor system receives the first input to the single text input field to determine a selected operation which is one of the first operation or the second operation and the processor system receives a text input in the single text input field, the text input being displayable in the entire single text input field and performs the selected operation on the text input wherein the first input comprises receiving a user input in either the first portion or the second portion of the text input field, wherein the first operation is selected if the user input is positioned in the first portion when the user input is received and wherein the second operation is selected if the user input is positioned in the second portion when the user input is received, wherein the first operation is a text search through a first source of data and wherein the second operation is either a file operation or a search operation that is different than the first operation, and wherein in response to the first input, the separator automatically disappears from the text input field and the first portion dominates the entire area of the text input field if the first operation is selected and the second portion dominates the entire area of the text input field if the second operation is selected. 29. A data processing system as in claim 25 wherein the separator scrolls in response to receiving the first input.

1. A method comprising: identifying state dependent content in an electronic document, wherein the state dependent content is renderable to have a plurality of appearances; receiving an attestation corresponding to the state dependent content; associating the attestation with the electronic document; and digitally signing the electronic document to generate a signed electronic document including a digital signature corresponding to a user associated with the attestation.

1. A method comprising: identifying state dependent content in an electronic document, wherein the state dependent content is renderable to have a plurality of appearances; receiving an attestation corresponding to the state dependent content; associating the attestation with the electronic document; and digitally signing the electronic document to generate a signed electronic document including a digital signature corresponding to a user associated with the attestation. 2. The method of claim 1 , wherein the attestation explains the presence of the state dependent content in the electronic document.

1. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; a set of instructions stored in the memory and executed by at least one of the processors to dynamically prioritize questions for response processing based on extracted question parameters, wherein the set of instructions perform actions of: receiving, by the information handling system, a plurality of questions; extracting, by the information handling system, a plurality of question priority parameters comprising one or more question topics and a plurality of question context parameters for each question; identifying, by the information handling system, system performance parameters for the information handling system comprising processor utilization data, available memory space data, and bandwidth utilization data; determining, by the information handling system, a target priority value for each question based on the system performance parameters and the plurality of question priority parameters identified for said question; dynamically prioritizing, by the information handling system, response processing of the plurality of questions by comparing the target priority values for each of the plurality of questions to generate a prioritized plurality of questions; storing the prioritized plurality of questions in a question queue at the information handling system which is configured to support asynchronous delivery of the prioritized plurality of questions; and passing the prioritized plurality of questions as messages between to one or more question answering systems.

1. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; a set of instructions stored in the memory and executed by at least one of the processors to dynamically prioritize questions for response processing based on extracted question parameters, wherein the set of instructions perform actions of: receiving, by the information handling system, a plurality of questions; extracting, by the information handling system, a plurality of question priority parameters comprising one or more question topics and a plurality of question context parameters for each question; identifying, by the information handling system, system performance parameters for the information handling system comprising processor utilization data, available memory space data, and bandwidth utilization data; determining, by the information handling system, a target priority value for each question based on the system performance parameters and the plurality of question priority parameters identified for said question; dynamically prioritizing, by the information handling system, response processing of the plurality of questions by comparing the target priority values for each of the plurality of questions to generate a prioritized plurality of questions; storing the prioritized plurality of questions in a question queue at the information handling system which is configured to support asynchronous delivery of the prioritized plurality of questions; and passing the prioritized plurality of questions as messages between to one or more question answering systems. 2. The information handling system of claim 1 , wherein extracting the plurality of question priority parameters comprises performing, by the information handling system, a natural language processing (NLP) analysis of each question, wherein the NLP analysis results in one or more question topics comprising extracted named entity information from said question.

13. The search system described in claim 12 , wherein the covering degree of the topic representation contained in the super page of one of the multiple Web pages is a similarity degree or a difference degree concerning the topic representation between the super pages of the multiple Web pages.

13. The search system described in claim 12 , wherein the covering degree of the topic representation contained in the super page of one of the multiple Web pages is a similarity degree or a difference degree concerning the topic representation between the super pages of the multiple Web pages. 19. The search system of claim 13 , wherein the search result page is obtained by a searching process by a Web search engine.

10. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions for managing user interface (UI) building blocks (UIBB) that when executed by one or more computers cause the one or more computers to perform operations comprising: presenting, by a form repeater UIBB, initial UI representations of two or more structured entities through a graphical user interface (GUI), each initial UI representation of the two or more structured entities comprising one or more fields; receiving a trigger from a user through the form repeater UIBB, the trigger associated with a particular initial UI representation of a particular structured entity of the two or more structured entities; in response to receiving the trigger, identifying an event condition ID associated with the trigger; matching the event condition ID to a stored ID value; based on the matching, identifying i) a substitute UI representation of the particular structured entity, ii) an event condition, and iii) a type of the event condition, wherein the substitute UI representation of the particular structured entity includes one or more fields that differ from the one or more fields of the particular initial UI representation of the particular structured entity; determining that the event condition identifies that an origination of the trigger is associated with the particular initial UI representation, and that the type of the event condition includes a swapping-in event condition; based on the determination that the event condition identifies that the origination of the trigger is associated with the particular initial UI representation, and that the type of the event condition includes the swapping-in event condition, replacing, by a substitute UIBB, the particular initial UI representation of the particular structured entity of the two or more structured entities with the identified substitute UI representation of the particular structured entity; removing the particular initial UI representation of the particular structured entity from the form repeater UIBB; and maintaining the initial UI representation of the remaining structured entities of the two or more structured entities concurrently with replacing the particular initial UI representation of the particular structured entity with the identified substitute UI representation of the particular structured entity.

10. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions for managing user interface (UI) building blocks (UIBB) that when executed by one or more computers cause the one or more computers to perform operations comprising: presenting, by a form repeater UIBB, initial UI representations of two or more structured entities through a graphical user interface (GUI), each initial UI representation of the two or more structured entities comprising one or more fields; receiving a trigger from a user through the form repeater UIBB, the trigger associated with a particular initial UI representation of a particular structured entity of the two or more structured entities; in response to receiving the trigger, identifying an event condition ID associated with the trigger; matching the event condition ID to a stored ID value; based on the matching, identifying i) a substitute UI representation of the particular structured entity, ii) an event condition, and iii) a type of the event condition, wherein the substitute UI representation of the particular structured entity includes one or more fields that differ from the one or more fields of the particular initial UI representation of the particular structured entity; determining that the event condition identifies that an origination of the trigger is associated with the particular initial UI representation, and that the type of the event condition includes a swapping-in event condition; based on the determination that the event condition identifies that the origination of the trigger is associated with the particular initial UI representation, and that the type of the event condition includes the swapping-in event condition, replacing, by a substitute UIBB, the particular initial UI representation of the particular structured entity of the two or more structured entities with the identified substitute UI representation of the particular structured entity; removing the particular initial UI representation of the particular structured entity from the form repeater UIBB; and maintaining the initial UI representation of the remaining structured entities of the two or more structured entities concurrently with replacing the particular initial UI representation of the particular structured entity with the identified substitute UI representation of the particular structured entity. 15. The non-transitory computer storage medium of claim 10 , wherein replacing, by the substitute UIBB, the particular initial UI representation of the particular structured entity of the two or more structured entities with the identified substitute UI representation of the particular structured entity comprises swapping the identified substitute UI representation of the particular structured entity with the particular initial UI representation of the particular structured entity based on the type of the event.

5. The method of claim 1 , further comprising: generating the second search query by reformulating the first search query.

5. The method of claim 1 , further comprising: generating the second search query by reformulating the first search query. 6. The method of claim 5 , wherein reformulating the first search query includes at least one of replacing or removing a term in the first search query.

10. A computer program product including instructions on a non-transitory computer readable medium and executable by a computer processor of a speech synthesis system to cause the system to implement steps comprising: (a) receiving first and second text inputs, the content of which collectively replies to a user request, in a text-to-speech synthesis system, wherein the first text input is obtained from one data source and the second text input is obtained from a different data source; (b) processing the first and second text inputs into respective first and second speech outputs corresponding to stored speech respectively from first and second speakers using a processor of the system; and (c) adapting the second speech output of the second speaker to sound like the first speech output of the first speaker; (d) outputting the first speech output of the first speaker; and (e) outputting the adapted second speech output of the second speaker wherein the first and second speech outputs include different content and are presented sequentially to a user of the text-to-speech system.

10. A computer program product including instructions on a non-transitory computer readable medium and executable by a computer processor of a speech synthesis system to cause the system to implement steps comprising: (a) receiving first and second text inputs, the content of which collectively replies to a user request, in a text-to-speech synthesis system, wherein the first text input is obtained from one data source and the second text input is obtained from a different data source; (b) processing the first and second text inputs into respective first and second speech outputs corresponding to stored speech respectively from first and second speakers using a processor of the system; and (c) adapting the second speech output of the second speaker to sound like the first speech output of the first speaker; (d) outputting the first speech output of the first speaker; and (e) outputting the adapted second speech output of the second speaker wherein the first and second speech outputs include different content and are presented sequentially to a user of the text-to-speech system. 11. The product of claim 10 , wherein step (c) includes: (c1) analyzing acoustic features of the first speech output for at least one speaker specific characteristic of the first speaker; (c2) adjusting an acoustic feature filter used to filter acoustic features from the second speech output, based on the at least one speaker specific characteristic of the first speaker; and (c3) filtering acoustic features from the second speech output using the filter adjusted in step (c2).

6. The method of claim 1 , wherein the morphemes in the user input are derived from an action of the user.

6. The method of claim 1 , wherein the morphemes in the user input are derived from an action of the user. 7. The method of claim 6 , wherein the action of the user comprises a focus of attention of the user.

7. A system for routing documents including a transaction processor front end operating on a processing server and connecting one or more client computers via a network with at least one operation running on at least one server, the system including: a plurality of operation interface specification data structures stored on a first server, including operation interface specifications, the operation interface specifications including descriptions of operations and definitions of input and output documents; the transaction processor front end running on the processing server coupled to the first server, comprising a network interface that accepts a document via the network from a client computer; a parser running on the processing server that analyzes the document according to the operation interface specifications, identifies an input document and identifies one or more operations that run on one or more processing servers, which accept the identified input document; and a document router running on the processing server that routes at least a portion of the input document from the processor server to the one or more operations running on servers, which accept the identified input document.

7. A system for routing documents including a transaction processor front end operating on a processing server and connecting one or more client computers via a network with at least one operation running on at least one server, the system including: a plurality of operation interface specification data structures stored on a first server, including operation interface specifications, the operation interface specifications including descriptions of operations and definitions of input and output documents; the transaction processor front end running on the processing server coupled to the first server, comprising a network interface that accepts a document via the network from a client computer; a parser running on the processing server that analyzes the document according to the operation interface specifications, identifies an input document and identifies one or more operations that run on one or more processing servers, which accept the identified input document; and a document router running on the processing server that routes at least a portion of the input document from the processor server to the one or more operations running on servers, which accept the identified input document. 11. The system of claim 7 , wherein the operation interface specifications include documents compliant with a definition of a predefined document including logical structures for storing an identifier of a particular operation, and at least one of definitions and references to definitions of input and output documents for the particular operation.

11. The pen input processing apparatus as set forth in claim 1, wherein said inputting means includes pen means for motivating said coordinate information generating means to generate the coordinate information by touching said screen therewith.

11. The pen input processing apparatus as set forth in claim 1, wherein said inputting means includes pen means for motivating said coordinate information generating means to generate the coordinate information by touching said screen therewith. 12. The pen input processing apparatus as set forth in claim 11, further comprising: controlling means, connected with said inputting means, for judging whether or not the inputting by handwriting is completed, wherein said controlling means judges that the inputting of editing instruction by handwriting is completed when said pen means touching said screen leaves said screen.

11. Apparatus, comprising: a memory, which is configured to hold a list of target users of a communication network and respective speech phrases that are characteristic of the target users; and a processor, which is configured to maintain the list in the memory, to select a plurality of candidate communication terminals from among multiple communication terminals in the communication network based on a selection criterion, to analyze speech that is communicated via the candidate communication terminals so as to identify one or more of the speech phrases in the speech, and to correlate one of the candidate communication terminals with a target user who is associated in the list with the identified speech phrases.

11. Apparatus, comprising: a memory, which is configured to hold a list of target users of a communication network and respective speech phrases that are characteristic of the target users; and a processor, which is configured to maintain the list in the memory, to select a plurality of candidate communication terminals from among multiple communication terminals in the communication network based on a selection criterion, to analyze speech that is communicated via the candidate communication terminals so as to identify one or more of the speech phrases in the speech, and to correlate one of the candidate communication terminals with a target user who is associated in the list with the identified speech phrases. 20. The apparatus according to claim 11 , wherein the processor is configured to automatically extract one or more of the speech phrases for a given target user from recorded speech of the given target user.

8. A method for processing user search requests comprising: receiving a search query from a user at a web server manager; processing the search query by a session manager and sending the search query to a neural network; generating, at a user map module, a user map of search terms based on a subset of the neural network; providing the user map to the user such that the user can select relevant search terms from the user map, wherein the search terms are semantically related to the user search query; processing search terms selected by the user from the user map; providing, via a search controller module, one or more search result documents corresponding to the selected search terms to the user; receiving a selection of at least one of the one or more search result documents from the user; and updating the neural network according to at least one of the selected relevant search terms from the user map or the at least one of the one or more search result documents selected by the user.

8. A method for processing user search requests comprising: receiving a search query from a user at a web server manager; processing the search query by a session manager and sending the search query to a neural network; generating, at a user map module, a user map of search terms based on a subset of the neural network; providing the user map to the user such that the user can select relevant search terms from the user map, wherein the search terms are semantically related to the user search query; processing search terms selected by the user from the user map; providing, via a search controller module, one or more search result documents corresponding to the selected search terms to the user; receiving a selection of at least one of the one or more search result documents from the user; and updating the neural network according to at least one of the selected relevant search terms from the user map or the at least one of the one or more search result documents selected by the user. 13. The method of claim 8 , wherein the search query comprises one or more of keywords and categories.

15. The apparatus according to claim 14 , wherein the first recognizing unit further calculates a second likelihood indicating a certainty of the first recognition result, and outputs the first recognition result including calculated second likelihood.

15. The apparatus according to claim 14 , wherein the first recognizing unit further calculates a second likelihood indicating a certainty of the first recognition result, and outputs the first recognition result including calculated second likelihood. 16. The apparatus according to claim 15 , wherein the rule-based translating unit translates the first recognition result into the second-language speech based on the rule, when the calculated second likelihood exceeds a third threshold.

20. The machine-readable medium of claim 18 , wherein the instructions further cause the processor to insert the word index into a tag associated with the captured object.

20. The machine-readable medium of claim 18 , wherein the instructions further cause the processor to insert the word index into a tag associated with the captured object. 21. The machine-readable medium of claim 20 , wherein the instructions further cause the processor to store the captured object in a canonical object store and storing the tag associated with the captured object in a tag database.

4. The apparatus according to claim 1 , wherein the named entity dictionary update module includes: a search result determination unit for determining whether or not the terminology is searched from the named entity dictionary as a result of the search; a named entity dictionary update unit for estimating the named entity of the terminology using the mining rule and storing the estimated named entity in the named entity dictionary depending on a user's selection, if the terminology is not searched from the named entity dictionary and the mining pattern is searched from the mining rule database as a result of the determination; and a control unit for controlling the named entity dictionary update unit to define and store properties of the named entity depending on a result of the determination of the search result determination unit.

4. The apparatus according to claim 1 , wherein the named entity dictionary update module includes: a search result determination unit for determining whether or not the terminology is searched from the named entity dictionary as a result of the search; a named entity dictionary update unit for estimating the named entity of the terminology using the mining rule and storing the estimated named entity in the named entity dictionary depending on a user's selection, if the terminology is not searched from the named entity dictionary and the mining pattern is searched from the mining rule database as a result of the determination; and a control unit for controlling the named entity dictionary update unit to define and store properties of the named entity depending on a result of the determination of the search result determination unit. 5. The apparatus according to claim 4 , wherein the named entity dictionary update unit defines the properties of the named entity to include authority data comprising a named entity corresponding to a concept (class) of the ontology schema, a terminology classified as the named entity, identification of the terminology, a representative terminology, and identification of the representative terminology, and connects and stores the properties of the named entity in one format.

1. A computer-implemented method for vulnerability risk management of an enterprise computer system, comprising the steps of: receiving, by an expert system, a list of potential vulnerabilities of the enterprise computer system from a vulnerability risk management module, wherein the expert system and the vulnerability risk management module are instantiated by a cloud computing system; converting a potential vulnerability on the list of potential vulnerabilities into a set of facts; verifying that the potential vulnerability is not a false positive by testing a rule against the set of facts; executing an action associated with the rule that modifies a fact of the set of facts to produce a modified set of facts when the conditions of the rule have been satisfied; incorporating the modified set of facts into a refined list of vulnerabilities; and transmitting the refined list of vulnerabilities to the vulnerability risk management module.

1. A computer-implemented method for vulnerability risk management of an enterprise computer system, comprising the steps of: receiving, by an expert system, a list of potential vulnerabilities of the enterprise computer system from a vulnerability risk management module, wherein the expert system and the vulnerability risk management module are instantiated by a cloud computing system; converting a potential vulnerability on the list of potential vulnerabilities into a set of facts; verifying that the potential vulnerability is not a false positive by testing a rule against the set of facts; executing an action associated with the rule that modifies a fact of the set of facts to produce a modified set of facts when the conditions of the rule have been satisfied; incorporating the modified set of facts into a refined list of vulnerabilities; and transmitting the refined list of vulnerabilities to the vulnerability risk management module. 8. The method of claim 1 , wherein the refined list of vulnerabilities is substantially free of extraneous information.

1. A computer-implemented method comprising: receiving search data by a computer system from a server hosting a first website, the search data including first information regarding content accessed by a user subsequent to a search, the first information indicative of a first content format accessed by the user, the first content format corresponding to a first search result of a plurality of search results provided to the user from the search, and the plurality of search results including content in a second content format that is different from the first content format, wherein the user does not access the second content format; identifying a category related to at least a portion of the search data, the identifying based at least on formats of content on target websites; determining, by the computer system and based on the search data, a topic for first content associated with the identified category; determining, by the computer system, a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data, information regarding different formats of content offered on the first website, the format of content accessed by the user on the first website, and the user not accessing the second content format; and presenting the topic and the score to a content provider for producing the first content for the target websites, the content provider to select a format for the first content based on the score and on user interaction with the plurality of search results.

1. A computer-implemented method comprising: receiving search data by a computer system from a server hosting a first website, the search data including first information regarding content accessed by a user subsequent to a search, the first information indicative of a first content format accessed by the user, the first content format corresponding to a first search result of a plurality of search results provided to the user from the search, and the plurality of search results including content in a second content format that is different from the first content format, wherein the user does not access the second content format; identifying a category related to at least a portion of the search data, the identifying based at least on formats of content on target websites; determining, by the computer system and based on the search data, a topic for first content associated with the identified category; determining, by the computer system, a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data, information regarding different formats of content offered on the first website, the format of content accessed by the user on the first website, and the user not accessing the second content format; and presenting the topic and the score to a content provider for producing the first content for the target websites, the content provider to select a format for the first content based on the score and on user interaction with the plurality of search results. 12. The method of claim 1 , wherein the search data further includes one or more of: search terms entered by a user; information regarding a website hosting content accessed by a user; information regarding content returned in response to search terms entered by a user; or combinations thereof.

3. The method of claim 2 , wherein coupling a second end of the connecting member to a second spinal rod comprises: positioning the second spinal rod within a rod receiving portion of a coupling member; and inserting a fastening element through the second end of the connecting member and into an opening formed in the coupling member to lock the second spinal rod, coupling member, and connecting member to one another.

3. The method of claim 2 , wherein coupling a second end of the connecting member to a second spinal rod comprises: positioning the second spinal rod within a rod receiving portion of a coupling member; and inserting a fastening element through the second end of the connecting member and into an opening formed in the coupling member to lock the second spinal rod, coupling member, and connecting member to one another. 5. The method of claim 3 , wherein the spinal rod is bottom-loaded into a rod-receiving recess formed in a bottom wall of the coupling member, and wherein the fastening element is inserted into an opening formed in a top wall of the coupling member.

1. A method for privilege control executed on a processor, comprising: selecting a privilege from at least one privilege supported by a document data object of document data stored in a docbase management system, wherein, the document data stored in the docbase management system includes at least one document data object, and the said at least one document object supports the at least one privilege; the document data stored in the docbase management system includes at least one signature, and each signature is the result of encrypting the HASH value of the regularization result of at least one document object with the private key of a role; setting, when setting a privilege for a role on the document data object, the privilege selected as the privilege of the role over the document data object; and controlling, when the role is to perform an operation on the document data object, the operation of the role on the document data object according to the privilege of the role over the document data object.

1. A method for privilege control executed on a processor, comprising: selecting a privilege from at least one privilege supported by a document data object of document data stored in a docbase management system, wherein, the document data stored in the docbase management system includes at least one document data object, and the said at least one document object supports the at least one privilege; the document data stored in the docbase management system includes at least one signature, and each signature is the result of encrypting the HASH value of the regularization result of at least one document object with the private key of a role; setting, when setting a privilege for a role on the document data object, the privilege selected as the privilege of the role over the document data object; and controlling, when the role is to perform an operation on the document data object, the operation of the role on the document data object according to the privilege of the role over the document data object. 2. The method of claim 1 , further comprising: storing a relationship which associates the document data object with the at least one privilege supported by the document data object to obtain the at least one privilege supported by the document data object according to the relationship; and/or storing a relationship which associates the role with the set of privilege granted to the role on the document data object to obtain the set of privilege granted to the role on the document data object according to the relationship.

3. The machine-readable media according to claim 2 , the data being interoperable with a machine to further cause: the encoding and the further encoding being in response to rule information input by the human user via the computer screen displayed subject matter expert interface.

3. The machine-readable media according to claim 2 , the data being interoperable with a machine to further cause: the encoding and the further encoding being in response to rule information input by the human user via the computer screen displayed subject matter expert interface. 5. The machine-readable media according to claim 3 , the data being interoperable with the machine to further cause: a rule from among the rules in the rule base being encoded in response to input by the human user by the computer screen displayed subject matter expert interface to also include a corresponding set of negation terms, and where a mined text snippet containing at least one negation term in a given set of negation terms is not associated with the label corresponding to the given set of negation terms.

1. A computer program product comprising a tangible computer usable medium having a computer readable program for managing granularity of a computing service infrastructure, wherein the computer readable program when executed on a computer causes the computer to: identify a group having a number of service requestors; identify a set of business functions that may be requested by the group of service requestors by either customized or non-customized service requests; create a value (n1) that represents the smallest number of customized service functions to realize all of the business functions; create a value (n2) that represents the smallest total number of non-customized service functions to realize all of the business functions; and iteratively determine an optimal number L of customized and non-customized service functions to realize the business functions, where L is between n1 and n2 and increases from n2 towards n1 as a number of each requestor is assigned a customized service request for each business function.

1. A computer program product comprising a tangible computer usable medium having a computer readable program for managing granularity of a computing service infrastructure, wherein the computer readable program when executed on a computer causes the computer to: identify a group having a number of service requestors; identify a set of business functions that may be requested by the group of service requestors by either customized or non-customized service requests; create a value (n1) that represents the smallest number of customized service functions to realize all of the business functions; create a value (n2) that represents the smallest total number of non-customized service functions to realize all of the business functions; and iteratively determine an optimal number L of customized and non-customized service functions to realize the business functions, where L is between n1 and n2 and increases from n2 towards n1 as a number of each requestor is assigned a customized service request for each business function. 2. The computer program product as in claim 1 , wherein the at least one set of service functions comprises at least one of logic, data and combinations of logic and data.

12. A non-transitory computer readable medium comprising instructions which, when executed, cause a machine to at least: a) calculate a set of motion primitives associated with a first aircraft intent description and a position of an aircraft based on combinations of AIDL instructions, the motion primitives including steady-state conditions or maneuvers to bring an aircraft from one steady-state condition to another; b) represent the motion primitives in AIDL; c) collect information associated with at least one of 1) an aircraft performance model, 2) an environmental model, 3) a flight dynamic model, or 4) the motion primitives; d) initialize a finite state machine based on the collected information, the finite state machine being configured to concatenate motion primitives, wherein states of the finite state machine correspond to steady-state conditions and transitions between the states are defined by maneuvers; e) collect specifications associated with at least one of: 1) flight plan instructions, 2) user preference indications, or 3) operational context indications; f) represent the specifications in a first formal language; g) combine the initialized finite state machine with the specifications represented in the first formal language to obtain a trajectory that satisfies a trajectory specification threshold; h) determine whether the obtained trajectory satisfies the trajectory specification threshold; i) iteratively initialize the finite state machine based on the information until a subsequently determined set of motion primitives satisfies the trajectory specification threshold, the subsequently determined set of motion primitives determined using incrementally modified motion primitives when the obtained trajectory is determined not to satisfy the trajectory specification threshold; and j) produce a representation of a second aircraft intent description of the obtained trajectory represented in AIDL and finalizing the method when the obtained trajectory is determined to satisfy the trajectory specification threshold.

12. A non-transitory computer readable medium comprising instructions which, when executed, cause a machine to at least: a) calculate a set of motion primitives associated with a first aircraft intent description and a position of an aircraft based on combinations of AIDL instructions, the motion primitives including steady-state conditions or maneuvers to bring an aircraft from one steady-state condition to another; b) represent the motion primitives in AIDL; c) collect information associated with at least one of 1) an aircraft performance model, 2) an environmental model, 3) a flight dynamic model, or 4) the motion primitives; d) initialize a finite state machine based on the collected information, the finite state machine being configured to concatenate motion primitives, wherein states of the finite state machine correspond to steady-state conditions and transitions between the states are defined by maneuvers; e) collect specifications associated with at least one of: 1) flight plan instructions, 2) user preference indications, or 3) operational context indications; f) represent the specifications in a first formal language; g) combine the initialized finite state machine with the specifications represented in the first formal language to obtain a trajectory that satisfies a trajectory specification threshold; h) determine whether the obtained trajectory satisfies the trajectory specification threshold; i) iteratively initialize the finite state machine based on the information until a subsequently determined set of motion primitives satisfies the trajectory specification threshold, the subsequently determined set of motion primitives determined using incrementally modified motion primitives when the obtained trajectory is determined not to satisfy the trajectory specification threshold; and j) produce a representation of a second aircraft intent description of the obtained trajectory represented in AIDL and finalizing the method when the obtained trajectory is determined to satisfy the trajectory specification threshold. 18. The computer readable medium of claim 12 , wherein the instructions, when executed, update at least one of the information and the specifications without precomputed motion planning.

14. A computer-readable medium, in a machine-readable storage device, storing a computer program product, the computer program product including instructions that, when executed, cause a configuration information handling component to perform operations comprising: receiving an indication of at least a first configuration information entry at a first computer storing a configuration directory and a repository containing multiple entries of configuration information for a software application program, each entry designed for customizing the software application program for a specific situation and the software application program being designed to remotely request configuration information as needed, wherein each configuration information entry includes 1) a configuration component available to be requested for the software application program and 2) a configuration attribute and an associated attribute value that define terms for the software application program to apply to a business transaction of a business enterprise in the specific situation, wherein the configuration repository stores the multiple entries of configuration information in XML format; activating a stored process on the first computer that converts the first configuration information entry from the XML format to a database table format in which access to the first configuration information entry is faster than in the XML format; and storing the first configuration information entry in the configuration directory in the database table format, the configuration directory being remote from the software application program and different from the configuration repository, wherein the first configuration information entry having the database table format is provided from the configuration directory to the software application program in response to a request.

14. A computer-readable medium, in a machine-readable storage device, storing a computer program product, the computer program product including instructions that, when executed, cause a configuration information handling component to perform operations comprising: receiving an indication of at least a first configuration information entry at a first computer storing a configuration directory and a repository containing multiple entries of configuration information for a software application program, each entry designed for customizing the software application program for a specific situation and the software application program being designed to remotely request configuration information as needed, wherein each configuration information entry includes 1) a configuration component available to be requested for the software application program and 2) a configuration attribute and an associated attribute value that define terms for the software application program to apply to a business transaction of a business enterprise in the specific situation, wherein the configuration repository stores the multiple entries of configuration information in XML format; activating a stored process on the first computer that converts the first configuration information entry from the XML format to a database table format in which access to the first configuration information entry is faster than in the XML format; and storing the first configuration information entry in the configuration directory in the database table format, the configuration directory being remote from the software application program and different from the configuration repository, wherein the first configuration information entry having the database table format is provided from the configuration directory to the software application program in response to a request. 19. The computer-readable medium of claim 14 , wherein the first configuration information entry is selected based on a received indication of a configuration information set, which comprises an indication of a market segment that includes an indication of an industry, the indication received based on selections received from the user in response to progressive user prompts that progressively prompt the user for increasing detail about a market segment.

13. The method of claim 1 , wherein the stimulus comprises one or more of questions, statements, or scenarios.

13. The method of claim 1 , wherein the stimulus comprises one or more of questions, statements, or scenarios. 16. The method of claim 13 , wherein the objective the individual is being assessed for is to ascertain one or more of emotional responses, potential veracity, personality type, and levels of enthusiasm for legal applications.

6. The method of claim 5 , wherein said optimizing the placed circuit design comprises performing an iterative optimization process to optimize an objective function based on the placed circuit design, wherein in each iteration of the iterative optimization process at least one cell is reassigned to a different layout bin based on the set of probability values.

6. The method of claim 5 , wherein said optimizing the placed circuit design comprises performing an iterative optimization process to optimize an objective function based on the placed circuit design, wherein in each iteration of the iterative optimization process at least one cell is reassigned to a different layout bin based on the set of probability values. 7. The method of claim 6 , wherein said optimizing the placed circuit design comprises terminating the iterative optimization process when the optimization function improves less than a minimum improvement threshold between two consecutive iterations or a maximum iteration limit is reached.

8. A computer system comprising: one or more processors which process program instructions; a display device; a memory device connected to said one or more processors; and program instructions residing in said memory device for displaying secondary data associated with primary data by generating a three-dimensional visualization of the primary data on the display device, the three-dimensional visualization including a plurality of primary graphical elements representing primary quantitative values and a plurality of primary labels respectively associated with and proximate to the primary graphical elements, the primary graphical elements and primary labels being presented on a front plane of the three-dimensional visualization, the front plane defining first and second axes, and at least one of the primary graphical elements having associated secondary graphical elements representing secondary quantitative values wherein the secondary graphical elements are presented along a third axis of the three-dimensional visualization, the third axis being different from the first and second axes, detecting that the at least one primary graphical elements has been selected, and responsive to the detecting, transitioning the three-dimensional visualization by moving the secondary graphical elements from the third axis of the three-dimensional visualization to the front plane of the three-dimensional visualization.

8. A computer system comprising: one or more processors which process program instructions; a display device; a memory device connected to said one or more processors; and program instructions residing in said memory device for displaying secondary data associated with primary data by generating a three-dimensional visualization of the primary data on the display device, the three-dimensional visualization including a plurality of primary graphical elements representing primary quantitative values and a plurality of primary labels respectively associated with and proximate to the primary graphical elements, the primary graphical elements and primary labels being presented on a front plane of the three-dimensional visualization, the front plane defining first and second axes, and at least one of the primary graphical elements having associated secondary graphical elements representing secondary quantitative values wherein the secondary graphical elements are presented along a third axis of the three-dimensional visualization, the third axis being different from the first and second axes, detecting that the at least one primary graphical elements has been selected, and responsive to the detecting, transitioning the three-dimensional visualization by moving the secondary graphical elements from the third axis of the three-dimensional visualization to the front plane of the three-dimensional visualization. 9. The computer system of claim 8 wherein the visualization is a bar chart and the primary and second graphical elements are bars.

19. A computer-readable medium having stored thereon a set of instructions which when executed causes a processor to perform a method comprising: obtaining training data; defining partitions for the training data based on a feature associated with the training data; and determining a confidence threshold for each partition based on the feature, wherein, in run-time operation, input information is converted into recognition results and the input information detected as having the feature is classified into one of the partitions of the training data defined using the feature and accepted or rejected as valid recognition results based on a comparison of the confidence threshold corresponding to the one of the partitions defined using the feature.

19. A computer-readable medium having stored thereon a set of instructions which when executed causes a processor to perform a method comprising: obtaining training data; defining partitions for the training data based on a feature associated with the training data; and determining a confidence threshold for each partition based on the feature, wherein, in run-time operation, input information is converted into recognition results and the input information detected as having the feature is classified into one of the partitions of the training data defined using the feature and accepted or rejected as valid recognition results based on a comparison of the confidence threshold corresponding to the one of the partitions defined using the feature. 23. The method of claim 19 , wherein the training data includes speech utterances, speech recognition results, and a confidence score for each of the speech recognition results.

8. A method for using a graphical data archive meta-model for flexible data archival, the method comprising: a computer analyzing application content of an enterprise application; the computer creating a data archive specification model based on the application content of the enterprise application, wherein the data archive specification model is based on the graphical data archive meta-model and is created in a general-purpose visual modeling language; modeling archive data based on the data archive specification model using one or more graphical modeling tools, wherein the graphical data archive meta-model comprises an archive operation schedule including instructions for: archiving and purging data; indicating when to start execution of an archive procedure; indicating what is to be archived; and identifying what to archive and how much to archive; and the computer transforming the data archive specification model to generate a second data archive specification.

8. A method for using a graphical data archive meta-model for flexible data archival, the method comprising: a computer analyzing application content of an enterprise application; the computer creating a data archive specification model based on the application content of the enterprise application, wherein the data archive specification model is based on the graphical data archive meta-model and is created in a general-purpose visual modeling language; modeling archive data based on the data archive specification model using one or more graphical modeling tools, wherein the graphical data archive meta-model comprises an archive operation schedule including instructions for: archiving and purging data; indicating when to start execution of an archive procedure; indicating what is to be archived; and identifying what to archive and how much to archive; and the computer transforming the data archive specification model to generate a second data archive specification. 9. The method as defined in claim 8 , wherein the archiving and purging data comprises purging archived data when a purge property is set as true, and archiving data when the purge property is not set as true.

11. A computer program product for adaptive matching of records in a data repository comprising: a computer usable memory medium having computer readable program code embodied therein wherein said computer readable program code comprises a matching executable unit configured to: present at least one field common to a first record and a second record wherein said at least one field is used to perform a match between said first record and said second record and wherein said at least one field is presented to a user; obtain a first selected field from said first record and a second selected field from said second record wherein said first selected field and said second selected field is obtained from said user; obtain a first data entry in said first selected field for said first record, said first data entry comprising a first string; tokenize said first string to retrieve a first tokenized data entry string; obtain a second data entry in said second selected field for said second record, said second data entry comprising a second string; tokenize said second string to retrieve a second tokenized data entry string; exclude at least one character from said first tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; exclude at least one different character with respect to said at least one character from said second tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; remove frequently used strings from said first tokenized data entry string and from said second tokenized data entry string; normalize data from said first selected field and from said second selected field to cleanse strings; alter a list of tokens presented to a user to define said match involving said first selected field when said user selects said second selected field; accept a first list of tokens desired for said match to occur utilizing said first selected field; accept a second list of tokens desired for said match to occur utilizing said second selected field; assign weights to each token in said first list of tokens and each token in said second list of tokens; calculate a score for said match through summation of said weights for each token that occurs in said first tokenized data entry string and said first record and for each token that occurs in said second tokenized data entry string and said second record; generate a group of similar records when said score is above a threshold; display said group of similar records to said user; learn at least one token that is relevant; learn at least one weight that results in a match; and learn at least one match criteria appropriate for said match for use in future matching based on user input regarding said score.

11. A computer program product for adaptive matching of records in a data repository comprising: a computer usable memory medium having computer readable program code embodied therein wherein said computer readable program code comprises a matching executable unit configured to: present at least one field common to a first record and a second record wherein said at least one field is used to perform a match between said first record and said second record and wherein said at least one field is presented to a user; obtain a first selected field from said first record and a second selected field from said second record wherein said first selected field and said second selected field is obtained from said user; obtain a first data entry in said first selected field for said first record, said first data entry comprising a first string; tokenize said first string to retrieve a first tokenized data entry string; obtain a second data entry in said second selected field for said second record, said second data entry comprising a second string; tokenize said second string to retrieve a second tokenized data entry string; exclude at least one character from said first tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; exclude at least one different character with respect to said at least one character from said second tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; remove frequently used strings from said first tokenized data entry string and from said second tokenized data entry string; normalize data from said first selected field and from said second selected field to cleanse strings; alter a list of tokens presented to a user to define said match involving said first selected field when said user selects said second selected field; accept a first list of tokens desired for said match to occur utilizing said first selected field; accept a second list of tokens desired for said match to occur utilizing said second selected field; assign weights to each token in said first list of tokens and each token in said second list of tokens; calculate a score for said match through summation of said weights for each token that occurs in said first tokenized data entry string and said first record and for each token that occurs in said second tokenized data entry string and said second record; generate a group of similar records when said score is above a threshold; display said group of similar records to said user; learn at least one token that is relevant; learn at least one weight that results in a match; and learn at least one match criteria appropriate for said match for use in future matching based on user input regarding said score. 18. The computer program product of claim 11 wherein said computer readable program code is further configured to: accept a weight value associated with a field.

18. The system of claim 11 , wherein selecting one of the n-grams comprises: selecting a current best n-gram from one or more 1-grams in the n-grams, where the current best n-gram has a highest overall score of all of the one or more 1-grams in the n-grams; considering each other highest overall scoring n-gram of all of the n-grams at each order of n-grams greater than 1 in increasing order, and determining, for each highest overall scoring n-gram at a given order whether to update the current best n-gram to be the highest overall scoring n-gram of the order, where the current best n-gram is updated when the highest overall scoring n-gram of the order has a higher overall score than a score associated with the current best n-gram or when the highest overall scoring n-gram is a superstring of the current best n-gram and has a score that satisfies an acceptance threshold.

18. The system of claim 11 , wherein selecting one of the n-grams comprises: selecting a current best n-gram from one or more 1-grams in the n-grams, where the current best n-gram has a highest overall score of all of the one or more 1-grams in the n-grams; considering each other highest overall scoring n-gram of all of the n-grams at each order of n-grams greater than 1 in increasing order, and determining, for each highest overall scoring n-gram at a given order whether to update the current best n-gram to be the highest overall scoring n-gram of the order, where the current best n-gram is updated when the highest overall scoring n-gram of the order has a higher overall score than a score associated with the current best n-gram or when the highest overall scoring n-gram is a superstring of the current best n-gram and has a score that satisfies an acceptance threshold. 19. The system of claim 18 , further comprising updating the current best n-gram to be the determined highest overall scoring n-gram of the order when it is determined that the current best n-gram should be updated.

1. A dictionary registration apparatus comprising: a first storing unit that stores therein dictionary information in which a first text in a first language is associated with a second text that is a translation of the first text into a second language; a first input unit that receives a first input text in the first language; an extracting unit that extracts, when the first input text includes an unregistered text that is not registered as the first text in the dictionary information, the unregistered text from the first input text; a determining unit that determines a part of speech of the unregistered text and that, in accordance with the part of speech, determines whether to convert a pronunciation of the unregistered text into an expression in the second language; a converting unit that converts the pronunciation of the unregistered text into the expression in the second language when the determining unit determines to convert the pronunciation; a second input unit that receives a second input text in the first language, the second input text expressing the unregistered text with a text being different from the unregistered text when the determining unit determines not to convert the pronunciation; a translating unit that translates the second input text into the second language; and a registering unit that registers the unregistered text in association with the second input text translated into the second language on the dictionary information or that registers the unregistered text in association with text which is the expression in the second language converted from the pronunciation of the unregistered text, on the dictionary information.

1. A dictionary registration apparatus comprising: a first storing unit that stores therein dictionary information in which a first text in a first language is associated with a second text that is a translation of the first text into a second language; a first input unit that receives a first input text in the first language; an extracting unit that extracts, when the first input text includes an unregistered text that is not registered as the first text in the dictionary information, the unregistered text from the first input text; a determining unit that determines a part of speech of the unregistered text and that, in accordance with the part of speech, determines whether to convert a pronunciation of the unregistered text into an expression in the second language; a converting unit that converts the pronunciation of the unregistered text into the expression in the second language when the determining unit determines to convert the pronunciation; a second input unit that receives a second input text in the first language, the second input text expressing the unregistered text with a text being different from the unregistered text when the determining unit determines not to convert the pronunciation; a translating unit that translates the second input text into the second language; and a registering unit that registers the unregistered text in association with the second input text translated into the second language on the dictionary information or that registers the unregistered text in association with text which is the expression in the second language converted from the pronunciation of the unregistered text, on the dictionary information. 4. The apparatus according to claim 1 , wherein the second input unit receives an input of the second input text using the first text that is already registered on the dictionary information.

2. The method of claim 1 , wherein the monitoring module executes on the client computing device, the method further comprising generating the document signature at the monitoring module.

2. The method of claim 1 , wherein the monitoring module executes on the client computing device, the method further comprising generating the document signature at the monitoring module. 3. The method of claim 2 , further comprising returning to the monitoring module an indication of a match of the document signature for the electronic document.

1. A teaching method of an image recognition apparatus, comprising: a step of capturing an image of a standard object having a standard conformation among objects to be recognized and extracting a characteristic value from a teacher image of the standard object through image processing; a step of making a user input an already-known knowledge of a range of fluctuation of objects and other objects and entering the knowledge in a knowledge base; a step of generating context data in which various attributes associated with the objects are described together with their semantics in accordance with the characteristic value extracted from the teacher image of the standard object and the knowledge entered in the knowledge base and updating the context data in the knowledge base based on comparison between the presently generated context data and the context data stored in the knowledge base; and a step of extracting an attribute corresponding to the type of a characteristic value used for recognition processing from the context data entered in the knowledge base and generating teaching data based on the extracted attribute for the recognition processing, wherein the teaching data include, at least, parameters related to a recognition logic, a threshold value, and a region recognized as the object applied to the recognition process; and wherein the already-known knowledge includes a parameter related to tolerance.

1. A teaching method of an image recognition apparatus, comprising: a step of capturing an image of a standard object having a standard conformation among objects to be recognized and extracting a characteristic value from a teacher image of the standard object through image processing; a step of making a user input an already-known knowledge of a range of fluctuation of objects and other objects and entering the knowledge in a knowledge base; a step of generating context data in which various attributes associated with the objects are described together with their semantics in accordance with the characteristic value extracted from the teacher image of the standard object and the knowledge entered in the knowledge base and updating the context data in the knowledge base based on comparison between the presently generated context data and the context data stored in the knowledge base; and a step of extracting an attribute corresponding to the type of a characteristic value used for recognition processing from the context data entered in the knowledge base and generating teaching data based on the extracted attribute for the recognition processing, wherein the teaching data include, at least, parameters related to a recognition logic, a threshold value, and a region recognized as the object applied to the recognition process; and wherein the already-known knowledge includes a parameter related to tolerance. 4. The teaching method of the image recognition apparatus according to claim 1 , wherein an attribute for a standard object is made to input as knowledge.

10. A handheld electronic device comprising: a processor and a memory storing a plurality of language objects and contextual data and a number of routines which, when executed by the processor, cause the electronic device to be configured to perform operations comprising: detecting a first language object as a first input; detecting as a second input an input that comprises one or more key selections; outputting at least a portion of a particular language object and another language object as proposed interpretations of the second input, the at least a portion of the particular language object being output at a position of preference with respect to the at least a portion of the another language object; detecting a selection of the at least a portion of the another language object; and responsive to the selection of the at least a portion of the another language object, storing in a data file a key object based on the another language object and an associated contextual value object based on the first language object, wherein the associated contextual value object is identified based on the key object occurring at a statistically significant incidence with the another language object.

10. A handheld electronic device comprising: a processor and a memory storing a plurality of language objects and contextual data and a number of routines which, when executed by the processor, cause the electronic device to be configured to perform operations comprising: detecting a first language object as a first input; detecting as a second input an input that comprises one or more key selections; outputting at least a portion of a particular language object and another language object as proposed interpretations of the second input, the at least a portion of the particular language object being output at a position of preference with respect to the at least a portion of the another language object; detecting a selection of the at least a portion of the another language object; and responsive to the selection of the at least a portion of the another language object, storing in a data file a key object based on the another language object and an associated contextual value object based on the first language object, wherein the associated contextual value object is identified based on the key object occurring at a statistically significant incidence with the another language object. 18. The device of claim 10 , the operations further comprising: receiving another input of the first language object; receiving another second input that comprises another key selection, the another key selection being the same as the one or more key selections; outputting the at least a portion of the another language object and the at least a portion of the particular language object as proposed interpretations of the another second input; receiving a selection of the at least a portion of the particular language object; locating an entry in the data file comprising a contextual value object that corresponds with the first language object and that is associated with a key object that corresponds with the another language object; and removing the entry from the data file, wherein the another contextual value object is identified based on its associated key object occurring at a statistically insignificant incidence with the another language object.

9. A computer-implemented method, comprising steps of: within a repository, storing: a first compound document that includes a first parent document that links to a first plurality of subdocuments that includes a first subdocument that corresponds to a first plurality of versions, a second compound document that includes a second parent document that links to a second plurality of subdocuments that includes a second subdocument that corresponds to a second plurality of versions, a first compound declaration in association with the first compound document, and a second compound declaration in association with the second compound document; while performing one or more operations to replace, in the first compound document, (a) links to the first plurality of subdocuments with (b) content of the first plurality of subdocuments, using said first compound declaration to return the most current version of the first plurality of versions of the first subdocument; while performing the one or more operations to replace, in the second compound document, (c) links to the second plurality of subdocuments with (d) content of the second plurality of subdocuments, using said second compound declaration to return a particular version, of the second plurality of versions, that is not the most current version of the second plurality of versions; in response to a request to check out a particular version of the first plurality of versions of the first subdocument for reading or modifying, checking out the particular version of the first subdocument without checking out any other subdocument of the first plurality of subdocuments and without checking out the first parent document.

9. A computer-implemented method, comprising steps of: within a repository, storing: a first compound document that includes a first parent document that links to a first plurality of subdocuments that includes a first subdocument that corresponds to a first plurality of versions, a second compound document that includes a second parent document that links to a second plurality of subdocuments that includes a second subdocument that corresponds to a second plurality of versions, a first compound declaration in association with the first compound document, and a second compound declaration in association with the second compound document; while performing one or more operations to replace, in the first compound document, (a) links to the first plurality of subdocuments with (b) content of the first plurality of subdocuments, using said first compound declaration to return the most current version of the first plurality of versions of the first subdocument; while performing the one or more operations to replace, in the second compound document, (c) links to the second plurality of subdocuments with (d) content of the second plurality of subdocuments, using said second compound declaration to return a particular version, of the second plurality of versions, that is not the most current version of the second plurality of versions; in response to a request to check out a particular version of the first plurality of versions of the first subdocument for reading or modifying, checking out the particular version of the first subdocument without checking out any other subdocument of the first plurality of subdocuments and without checking out the first parent document. 14. The method of claim 9 , further comprising: creating a new version of the first parent document; and in response to a request to check out the new version of the first parent document for reading or modifying, checking out the new version of the first parent document without checking out any subdocument of the first plurality of subdocuments.

20. A computer-implemented method for simulating consciousness, comprising: identifying perceived characteristics of objects in an environment based on perceptions of the objects, the perceptions obtained by experiencing the objects; storing lists of said characteristics; and forming concepts by comparing similarities in the perceived characteristics; wherein said steps of identifying, storing and forming are performed by said computer.

20. A computer-implemented method for simulating consciousness, comprising: identifying perceived characteristics of objects in an environment based on perceptions of the objects, the perceptions obtained by experiencing the objects; storing lists of said characteristics; and forming concepts by comparing similarities in the perceived characteristics; wherein said steps of identifying, storing and forming are performed by said computer. 22. The method of claim 20 , wherein: said lists are percepts.

27. A system for teaching a student in a computer-based learning environment, comprising: at least one processor that: identifies a first concept that was learned by a first student and that is related to a second concept to be learned by the first student; identifies a first type of content used to teach the first concept to the first student; identifies at least one other student that learned the first concept from the first type of content; identifies a second type of content through which the at least one other student learned the second concept; selects content corresponding to the second concept and the second type of content; and presents the content corresponding to the second concept and the second type of content to the first student.

27. A system for teaching a student in a computer-based learning environment, comprising: at least one processor that: identifies a first concept that was learned by a first student and that is related to a second concept to be learned by the first student; identifies a first type of content used to teach the first concept to the first student; identifies at least one other student that learned the first concept from the first type of content; identifies a second type of content through which the at least one other student learned the second concept; selects content corresponding to the second concept and the second type of content; and presents the content corresponding to the second concept and the second type of content to the first student. 29. The system of claim 27 , wherein the at least one processor also automatically categorizes content.

1. A method for converting an application, comprising: receiving application code from a source application, the application code written in a first programming framework; dividing the application code into clusters; evaluating clusters according to predetermined programming rules, wherein the evaluation comprises: determining a conversion score for each cluster; comparing the conversion score of each cluster to a predetermined threshold score; and converting clusters having a conversion score above the predetermined threshold into a second programming framework, wherein the converting comprises: extracting software features of each cluster having a score below the predetermined threshold; passing the software features into a model; and outputting, by the model, clusters of code performing the software features in the second programming framework; and optimizing the predetermined rules according to machine learning techniques for future application conversions.

1. A method for converting an application, comprising: receiving application code from a source application, the application code written in a first programming framework; dividing the application code into clusters; evaluating clusters according to predetermined programming rules, wherein the evaluation comprises: determining a conversion score for each cluster; comparing the conversion score of each cluster to a predetermined threshold score; and converting clusters having a conversion score above the predetermined threshold into a second programming framework, wherein the converting comprises: extracting software features of each cluster having a score below the predetermined threshold; passing the software features into a model; and outputting, by the model, clusters of code performing the software features in the second programming framework; and optimizing the predetermined rules according to machine learning techniques for future application conversions. 4. The method of claim 1 , wherein the model includes recognizing standardized features in the first programming framework and converting into standardized features in the second programming framework.

1. A system for providing regular expression support using kernel-mode code language matching functions, the system comprising: at least one hardware processor coupled to a non-transitory memory and configured to cause the system to execute: a translator module that receives a probe script comprising an input source code of an event occurring in a host machine operating system and compiles the probe script written in a scripting language comprising SystemTap, wherein the probe script includes a set of definitions assigned by a user to reference other probe scripts, wherein the probe script includes a regular expression in the scripting language, wherein the translator module further determines input characters of the regular expression and regular expression matching instructions from patterns of the input characters, wherein the regular expression matching instructions comprise at least one of an identification of at least one string to perform matching using the regular expression, a number of times to perform the matching using the regular expression, and a stop point of the matching using the regular expression, and wherein the probe script performs analysis of a system point or process, wherein the translator module further determines a matching function in kernel-mode code language corresponding to the regular expression using the input characters and the patterns and translates the regular expression matching instructions to an invocation to the matching function in kernel-mode code language, and wherein the matching function corresponds to a deterministic finite automaton; and a kernel module that processes at least one string using the matching function and the invocation for the regular expression matching instructions in kernel-mode when executing the compiled probe script with the set of definitions to execute the regular expression in the probe script when analyzing the system point or the process, wherein regular expression matching instruction is translated to an invocation to the matching function in kernel-mode code language, wherein the matching function simulates state transitions of the deterministic finite automaton using the at least one string and the regular expression matching instructions in the kernel-mode, and wherein the kernel module finds matching patterns in the at least one string using the deterministic finite automaton.

1. A system for providing regular expression support using kernel-mode code language matching functions, the system comprising: at least one hardware processor coupled to a non-transitory memory and configured to cause the system to execute: a translator module that receives a probe script comprising an input source code of an event occurring in a host machine operating system and compiles the probe script written in a scripting language comprising SystemTap, wherein the probe script includes a set of definitions assigned by a user to reference other probe scripts, wherein the probe script includes a regular expression in the scripting language, wherein the translator module further determines input characters of the regular expression and regular expression matching instructions from patterns of the input characters, wherein the regular expression matching instructions comprise at least one of an identification of at least one string to perform matching using the regular expression, a number of times to perform the matching using the regular expression, and a stop point of the matching using the regular expression, and wherein the probe script performs analysis of a system point or process, wherein the translator module further determines a matching function in kernel-mode code language corresponding to the regular expression using the input characters and the patterns and translates the regular expression matching instructions to an invocation to the matching function in kernel-mode code language, and wherein the matching function corresponds to a deterministic finite automaton; and a kernel module that processes at least one string using the matching function and the invocation for the regular expression matching instructions in kernel-mode when executing the compiled probe script with the set of definitions to execute the regular expression in the probe script when analyzing the system point or the process, wherein regular expression matching instruction is translated to an invocation to the matching function in kernel-mode code language, wherein the matching function simulates state transitions of the deterministic finite automaton using the at least one string and the regular expression matching instructions in the kernel-mode, and wherein the kernel module finds matching patterns in the at least one string using the deterministic finite automaton. 3. The system of claim 1 , wherein the translator module compiles the probe script by translating the input source code into a second source code language, and compiling the second source code language to a kernel module.

9. An apparatus that can be used to specify a subset of data, comprising: a communication interface; a storage device; and one or more processors in communication with the storage device and the communication interface, the one or more processors implement a user interface using the communication interface, the one or more processors receive a first input at the user interface for a first field of a natural language expression, the first input indicates a first data value for the first field, the one or more processors access options for a second field of the natural language expression that are determined based on the first data value and data stored in data group, the one or more processors display the second field and the options for the second field, the one or more processors receive a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field, the one or more processors access options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group, the one or more processors display the third field and the options for the third field, the one or more processors receive a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language, the one or more processors access and report a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language.

9. An apparatus that can be used to specify a subset of data, comprising: a communication interface; a storage device; and one or more processors in communication with the storage device and the communication interface, the one or more processors implement a user interface using the communication interface, the one or more processors receive a first input at the user interface for a first field of a natural language expression, the first input indicates a first data value for the first field, the one or more processors access options for a second field of the natural language expression that are determined based on the first data value and data stored in data group, the one or more processors display the second field and the options for the second field, the one or more processors receive a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field, the one or more processors access options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group, the one or more processors display the third field and the options for the third field, the one or more processors receive a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language, the one or more processors access and report a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language. 16. The apparatus of claim 9 , wherein: the first field, the second field and the third field are tiered data fields in the natural language expression; the first field and the third field are at a common tier; and the second field is at a tier lower than the common tier.

1. A method for evaluating contents of a message, comprising: characterizing a message segment, wherein the message segment further comprises a packet in a packet-switched network; scanning the message segment to define a stream of tokens associated with the message segment; associating the message segment with a meta session through the stream of tokens, wherein the meta session is made persistent across message transactions and different HTTP sessions by storing data generated by the meta session on a persistent storage medium; parsing the token stream to extract substructures according to a grammar; determining rules associated with the tokens, the rules when executed defining actions for intrusion detection and prevention; executing the actions associated with the message segment; and queuing the message segment for transmission to a destination, wherein each of the operations in the method is executed by an integrated circuit.

1. A method for evaluating contents of a message, comprising: characterizing a message segment, wherein the message segment further comprises a packet in a packet-switched network; scanning the message segment to define a stream of tokens associated with the message segment; associating the message segment with a meta session through the stream of tokens, wherein the meta session is made persistent across message transactions and different HTTP sessions by storing data generated by the meta session on a persistent storage medium; parsing the token stream to extract substructures according to a grammar; determining rules associated with the tokens, the rules when executed defining actions for intrusion detection and prevention; executing the actions associated with the message segment; and queuing the message segment for transmission to a destination, wherein each of the operations in the method is executed by an integrated circuit. 8. The method of claim 1 , wherein the message is composed of multiple segments.

1. A method of displaying text on an electronic display, the text being dividable into a plurality of respective display elements, at least some of the plurality of respective display elements corresponding to respective words, a word comprising a recognizable set of one or more characters, at least some of the words having an optimal recognition position, the method comprising: serially displaying, on the electronic display, a plurality of respective display elements such that an optimal recognition position of at least some display elements of the plurality of respective display elements is displayed at a substantially same location on the electronic display, referred to as a fixed display location, wherein, the at least some display elements are displayed such that the fixed display location is off-center toward the beginning of a displayed display element from the perspective of a reader of the electronic display.

1. A method of displaying text on an electronic display, the text being dividable into a plurality of respective display elements, at least some of the plurality of respective display elements corresponding to respective words, a word comprising a recognizable set of one or more characters, at least some of the words having an optimal recognition position, the method comprising: serially displaying, on the electronic display, a plurality of respective display elements such that an optimal recognition position of at least some display elements of the plurality of respective display elements is displayed at a substantially same location on the electronic display, referred to as a fixed display location, wherein, the at least some display elements are displayed such that the fixed display location is off-center toward the beginning of a displayed display element from the perspective of a reader of the electronic display. 3. The method of claim 1 wherein the at least some display elements include display elements having a length of greater than four characters.

1. A method comprising: providing a multi-layer model that comprises: an advertiser layer associated with advertisers that compensate syndicators to display advertisements; a syndicator layer associated with the syndicators that buy click traffic from aggregators for the advertisements; an aggregation layer associated with the aggregators that buy the click traffic from spammers to insulate the syndicators and the advertisers from being associated with spam content; a redirection layer associated with redirection domains used by the spammers to fetch the spam content after a doorway web page is clicked; and a doorway layer associated with doorway web pages that the spammers promote to top search result positions to attract the click traffic; identifying, based on an analysis of the multi-layer model, the aggregation layer as a bottleneck layer that uses at least one Internet Protocol (IP) block to funnel the advertisements and to associate the advertisements with the spam content; and performing, by one or more processors configured with executable instructions, one or more corrective actions that act on the bottleneck layer to protect web browsers from search spam.

1. A method comprising: providing a multi-layer model that comprises: an advertiser layer associated with advertisers that compensate syndicators to display advertisements; a syndicator layer associated with the syndicators that buy click traffic from aggregators for the advertisements; an aggregation layer associated with the aggregators that buy the click traffic from spammers to insulate the syndicators and the advertisers from being associated with spam content; a redirection layer associated with redirection domains used by the spammers to fetch the spam content after a doorway web page is clicked; and a doorway layer associated with doorway web pages that the spammers promote to top search result positions to attract the click traffic; identifying, based on an analysis of the multi-layer model, the aggregation layer as a bottleneck layer that uses at least one Internet Protocol (IP) block to funnel the advertisements and to associate the advertisements with the spam content; and performing, by one or more processors configured with executable instructions, one or more corrective actions that act on the bottleneck layer to protect web browsers from search spam. 2. The method of claim 1 , wherein the one or more corrective actions act on information associated with the bottleneck layer.

1. A method of determining information relevant to a location within a first document, the method comprising: receiving a selection of the first document, the first document being received through an input and output interface of a computer; identifying at least two structural elements in the first document having a dominance relationship, the identifying being performed by one or more processors of the computer; receiving a selection of a first location in the first document from a user through the input and output interface; determining surrounding structural elements surrounding the first location, the determining comprising selecting from the at least two structural elements; characterizing the surrounding structural elements by the one or more processors; characterizing one or more non-surrounding structural elements from among the at least two structural elements not determined to be the surrounding structural elements by the one or more processors; characterizing surrounding phrase for frequency of occurrence of a plurality of first terms by the one or more processors; characterizing non-surrounding phrases in the first document for the occurrence of the plurality of the first terms by the one or more processors, the non-surrounding phrases being phrases in the first document other than the surrounding phrase; associating one or more second documents with the surrounding structural elements based on the characterization of the surrounding structural elements and the one or more non-surrounding structural elements by the one or more processors, wherein the one or more second documents are determined as being similar to the surrounding structural elements and being dissimilar to the one or more non-surrounding structural elements; creating representative vectors based on the frequency of occurrence of the first terms in the surrounding structural elements, performing latent semantic analysis (LSA) on the surrounding structural elements, the surrounding structural elements are determined based on explicit or implicit information, the implicit information is determined based on theory of analysis, the theory of analysis is at least one of: Linguistic Discourse Model (LDM), Universal Linguistic Discourse Model (ULDM), Discourse Structures Theory (DST), Rhetorical Structures Theory (RST), and Structure Discourse Representation Theory (SDRT), the characterizing of the surrounding structural elements is based on similarity of the representative vectors, the representative vectors are used to select additional documents that are similar in meaning to the surrounding structure elements but are dissimilar to the non-surrounding structure elements, wherein the additional documents are in association with the first location; and removing a second group of the one or more second documents from among first groups of the one or more second documents to obtain a third group of the one or more documents, wherein the removing is based on the characterizing the surrounding structure elements.

1. A method of determining information relevant to a location within a first document, the method comprising: receiving a selection of the first document, the first document being received through an input and output interface of a computer; identifying at least two structural elements in the first document having a dominance relationship, the identifying being performed by one or more processors of the computer; receiving a selection of a first location in the first document from a user through the input and output interface; determining surrounding structural elements surrounding the first location, the determining comprising selecting from the at least two structural elements; characterizing the surrounding structural elements by the one or more processors; characterizing one or more non-surrounding structural elements from among the at least two structural elements not determined to be the surrounding structural elements by the one or more processors; characterizing surrounding phrase for frequency of occurrence of a plurality of first terms by the one or more processors; characterizing non-surrounding phrases in the first document for the occurrence of the plurality of the first terms by the one or more processors, the non-surrounding phrases being phrases in the first document other than the surrounding phrase; associating one or more second documents with the surrounding structural elements based on the characterization of the surrounding structural elements and the one or more non-surrounding structural elements by the one or more processors, wherein the one or more second documents are determined as being similar to the surrounding structural elements and being dissimilar to the one or more non-surrounding structural elements; creating representative vectors based on the frequency of occurrence of the first terms in the surrounding structural elements, performing latent semantic analysis (LSA) on the surrounding structural elements, the surrounding structural elements are determined based on explicit or implicit information, the implicit information is determined based on theory of analysis, the theory of analysis is at least one of: Linguistic Discourse Model (LDM), Universal Linguistic Discourse Model (ULDM), Discourse Structures Theory (DST), Rhetorical Structures Theory (RST), and Structure Discourse Representation Theory (SDRT), the characterizing of the surrounding structural elements is based on similarity of the representative vectors, the representative vectors are used to select additional documents that are similar in meaning to the surrounding structure elements but are dissimilar to the non-surrounding structure elements, wherein the additional documents are in association with the first location; and removing a second group of the one or more second documents from among first groups of the one or more second documents to obtain a third group of the one or more documents, wherein the removing is based on the characterizing the surrounding structure elements. 2. The method of claim 1 , in which the first location is selected based on at least one of: manually and programmatic control.

1. A method for performing speech recognition, the method comprising: acquiring a speech signal from a user; performing a first recognition pass by applying a first language model to said speech signal, said first language model being constrained in accordance with a structured data source; and generating a subsequent language model based at least in part on results from said first recognition pass.

1. A method for performing speech recognition, the method comprising: acquiring a speech signal from a user; performing a first recognition pass by applying a first language model to said speech signal, said first language model being constrained in accordance with a structured data source; and generating a subsequent language model based at least in part on results from said first recognition pass. 2. The method of claim 1 , further comprising: performing a subsequent recognition pass by applying said subsequent language model; and recognizing said speech signal.

9. The apparatus according to claim 8 , wherein the user information estimation unit estimates an emphasized section, which the speaker emphasizes and utters, in a sound section of the input sound, and wherein the matching unit performs matching between the search result target pronunciation symbol string and the recognition result pronunciation symbol string by weighting a pronunciation symbol in the emphasized section in the recognition result pronunciation symbol string, which is represented by the user information.

9. The apparatus according to claim 8 , wherein the user information estimation unit estimates an emphasized section, which the speaker emphasizes and utters, in a sound section of the input sound, and wherein the matching unit performs matching between the search result target pronunciation symbol string and the recognition result pronunciation symbol string by weighting a pronunciation symbol in the emphasized section in the recognition result pronunciation symbol string, which is represented by the user information. 10. The apparatus according to claim 9 , wherein the user information estimation unit estimates the emphasized section based on pitch, power, or an utterance speed of the input sound.

9. A method as in claim 1 , further comprising automatically re-selecting a second preferred component from the at least two translation components in response to an occurrence.

9. A method as in claim 1 , further comprising automatically re-selecting a second preferred component from the at least two translation components in response to an occurrence. 11. A method as in claim 9 , wherein the occurrence comprises improving at least one of the at least two translation components.

5. The computer implemented method of claim 1 , wherein the behavior expressing step explicitly expresses the user's behaviors in a behavior layer that expresses behaviors inferred in the context layer.

5. The computer implemented method of claim 1 , wherein the behavior expressing step explicitly expresses the user's behaviors in a behavior layer that expresses behaviors inferred in the context layer. 6. The computer implemented method of claim 5 , wherein the recognizing step generates the context association, which is dynamically expressed in an extended context association layer located above the behavior layer, with respect to the user's behaviors expressed in the behavior layer, and recognizes the user's behaviors as one behavior in an extended behavior layer located above the extended context association layer.

1. A method for electronically managing application development, comprising: providing an interface control document containing a first set of one or more sequence diagrams that model interactions between a plurality of applications, each of the plurality of applications including a plurality of software components, classes, or objects; providing an application model document containing a second set of one or more sequence diagrams that model interactions within one or more of the plurality of applications, wherein interactions modeled in the first set of sequence diagrams and the second set of sequence diagrams include a plurality of types of modeled interactions, the plurality of types of modeled interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions; defining a project for development, at least some of a plurality of functionalities of the project defined based on the modeled interactions provided in the interface control document and the application model document; providing a baseline document containing a third list of existing interactions related to one or more of the plurality of applications; generating a count reflecting a total number of business operation points based on each of the plurality of types of interactions in the interface control document and the application model document which are not associated with existing interactions in the third list contained in the baseline document, wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include data functions of the applications or interactions with external non-application actors; and estimating a level of effort to complete the project based on multiplying the total number of business operation points based on each of the plurality of types of interactions by a corresponding proportionality constant and summing a result of the multiplying for all of the plurality of types of interactions.

1. A method for electronically managing application development, comprising: providing an interface control document containing a first set of one or more sequence diagrams that model interactions between a plurality of applications, each of the plurality of applications including a plurality of software components, classes, or objects; providing an application model document containing a second set of one or more sequence diagrams that model interactions within one or more of the plurality of applications, wherein interactions modeled in the first set of sequence diagrams and the second set of sequence diagrams include a plurality of types of modeled interactions, the plurality of types of modeled interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions; defining a project for development, at least some of a plurality of functionalities of the project defined based on the modeled interactions provided in the interface control document and the application model document; providing a baseline document containing a third list of existing interactions related to one or more of the plurality of applications; generating a count reflecting a total number of business operation points based on each of the plurality of types of interactions in the interface control document and the application model document which are not associated with existing interactions in the third list contained in the baseline document, wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include data functions of the applications or interactions with external non-application actors; and estimating a level of effort to complete the project based on multiplying the total number of business operation points based on each of the plurality of types of interactions by a corresponding proportionality constant and summing a result of the multiplying for all of the plurality of types of interactions. 5. The method of claim 1 wherein the estimating involves using information from one or more completed projects selected from a plurality of completed projects based on a similar type of the completed projects to the project, and wherein the information from one or more completed projects is maintained electronically.

14. A method according to claim 13 , wherein: locating a first layout information file includes locating a layout information file specifying how first content and the first layout string are to be presented to the user; the method further comprises obtaining the first content from a first content provider; and presenting the first layout string to the user includes presenting the content and the first layout string to the user according to the first layout information file.

14. A method according to claim 13 , wherein: locating a first layout information file includes locating a layout information file specifying how first content and the first layout string are to be presented to the user; the method further comprises obtaining the first content from a first content provider; and presenting the first layout string to the user includes presenting the content and the first layout string to the user according to the first layout information file. 15. A method according to claim 14 , wherein locating a first layout strings file and a second layout strings file from a plurality of layout strings files includes locating the one of the plurality of layout strings files storing the first layout string in a selected language.

10. A system that generates tags for a video file, comprising: one or more processors; a storage device that includes a non-transitory, computer-readable storage medium; a communications subsystem; and a user interface including at least one input device and at least one graphical display; wherein the storage medium stores the video file and instructions that, when executed by the one or more processors, cause the system to perform operations including: receiving a list of candidate tags for the video file through the communications subsystem; receiving a transcript of audio associated with the video file; evaluating the transcript of audio associated with the video file; ranking the list of the candidate tags for the video file based on a plurality of ranking factors, wherein: ranking the list of candidate tags for the video file based on the plurality of ranking factors include ranking the list of candidate tags based on the evaluated transcript; associating a rank with each of the candidate tags in the list of the candidate tags, based on the ranking; forming a filtered list of the candidate tags by removing ones of the candidate tags having an associated rank that is below a threshold value from the list of the candidate tags, wherein: evaluating the transcript cause the system includes generating a list of top concepts for the video file in light of the selection of one or more of the filtered list of candidate tags; establishing a relationship between the video file and at least one other video file based on corresponding top concepts between the video file and the at least one other video file; presenting the filtered list of the candidate tags in the user interface; receiving a selection of one or more of the filtered list of the candidate tags from the user interface; producing an updated list of the candidate tags for the video file based on the selection; and storing the updated list of the candidate tags associated with the video file in the storage medium.

10. A system that generates tags for a video file, comprising: one or more processors; a storage device that includes a non-transitory, computer-readable storage medium; a communications subsystem; and a user interface including at least one input device and at least one graphical display; wherein the storage medium stores the video file and instructions that, when executed by the one or more processors, cause the system to perform operations including: receiving a list of candidate tags for the video file through the communications subsystem; receiving a transcript of audio associated with the video file; evaluating the transcript of audio associated with the video file; ranking the list of the candidate tags for the video file based on a plurality of ranking factors, wherein: ranking the list of candidate tags for the video file based on the plurality of ranking factors include ranking the list of candidate tags based on the evaluated transcript; associating a rank with each of the candidate tags in the list of the candidate tags, based on the ranking; forming a filtered list of the candidate tags by removing ones of the candidate tags having an associated rank that is below a threshold value from the list of the candidate tags, wherein: evaluating the transcript cause the system includes generating a list of top concepts for the video file in light of the selection of one or more of the filtered list of candidate tags; establishing a relationship between the video file and at least one other video file based on corresponding top concepts between the video file and the at least one other video file; presenting the filtered list of the candidate tags in the user interface; receiving a selection of one or more of the filtered list of the candidate tags from the user interface; producing an updated list of the candidate tags for the video file based on the selection; and storing the updated list of the candidate tags associated with the video file in the storage medium. 13. The system that generates tags for a video file as in claim 10 , the storage medium storing additional instructions that, when executed by the one or more processors, cause the system to perform operations including: providing one or more suggested video files associated with the video file based on the relationship between the video file and the at least one other video file.

1. A computer-implemented method comprising: extracting product descriptors from a product page; receiving a result of a search for prices of the product based on the extracted product descriptors; generating, using the result of the search for prices of the product, a price comparison result for the product displayed in the product page; identifying, using the price comparison result, a product with selected attributes; generating a buyer button, the buyer button including a direct link to the identified product with selected attributes; generating a browser toolbar and the product page contemporaneously in a client browser, wherein the browser toolbar includes a seller button, the buyer button, and the price comparison result for the product displayed in the product page; and generating, in response to operation of the seller button, a product listing on a marketplace, wherein generating the product listing includes determining a product category and a product description from the product descriptors extracted from the product page; wherein the preceding steps are performed by a computer processor.

1. A computer-implemented method comprising: extracting product descriptors from a product page; receiving a result of a search for prices of the product based on the extracted product descriptors; generating, using the result of the search for prices of the product, a price comparison result for the product displayed in the product page; identifying, using the price comparison result, a product with selected attributes; generating a buyer button, the buyer button including a direct link to the identified product with selected attributes; generating a browser toolbar and the product page contemporaneously in a client browser, wherein the browser toolbar includes a seller button, the buyer button, and the price comparison result for the product displayed in the product page; and generating, in response to operation of the seller button, a product listing on a marketplace, wherein generating the product listing includes determining a product category and a product description from the product descriptors extracted from the product page; wherein the preceding steps are performed by a computer processor. 4. The computer-implemented method of claim 1 , wherein displaying the price comparison result for the product displayed in the product page includes displaying a suggested price for the product, and wherein extracting product descriptors from a product page includes extracting the product title from the product page that displays the product.

2. Method as claimed in claim 1 , where extracting a rapidly varying input component includes generating the slowly varying input component, at least in part, through smoothing of the spectral envelope input representation, where the smoothing attenuates the magnitude of at least one of the formant and the spectral trough and preserves a non-constant coarse shape of the spectral envelope input representation and deriving the rapidly varying input component by subtracting the slowly varying input component from the spectral envelope input representation.

2. Method as claimed in claim 1 , where extracting a rapidly varying input component includes generating the slowly varying input component, at least in part, through smoothing of the spectral envelope input representation, where the smoothing attenuates the magnitude of at least one of the formant and the spectral trough and preserves a non-constant coarse shape of the spectral envelope input representation and deriving the rapidly varying input component by subtracting the slowly varying input component from the spectral envelope input representation. 3. Method as claimed in claim 2 , where the step of generating the slowly varying input component includes low-pass (LP) filtering the spectral envelope input representation.

10. The computer program product of claim 9 , wherein the one or more solutions to the selected at least one business challenge of the selected store each have a corresponding recommendation score that relates to an expected efficacy of the one or more solutions.

10. The computer program product of claim 9 , wherein the one or more solutions to the selected at least one business challenge of the selected store each have a corresponding recommendation score that relates to an expected efficacy of the one or more solutions. 12. The computer program product of claim 10 , wherein the corresponding recommendation score is calculated based on a projected cost to implement a solution.

1. A processor-based method of determining whether a keyword made up of characters is present in a bitmap input image containing words, the words being considered to extend horizontally, the method comprising the steps of: providing a set of previously trained single-character hidden Markov models (HMMs), each single-character HMM having a number of possible contexts, depending on whether the character has an ascender or a descender; concatenating those single-character HMMs that correspond to the characters in the keyword so as to create a keyword HMM, the context of a given single-character HMM used to create the keyword HMM being determined on the basis of whether the keyword contains characters having ascenders or a descenders; constructing an HMM network that includes a path passing through the keyword HMM; locating a portion of the input image potentially containing a word; providing an array of pixel values, referred to as a potential keyword, representing the portion of the input image; horizontally sampling the potential keyword to provide a plurality of segments wherein each segment extends the entire height of the potential keyword and the sampling to provide segments is performed in a manner that is independent of the values of the pixels in the potential keyword; for each segment, generating at least one feature that depends on the values of the pixels in the segment, thereby providing a set of features based on the potential keyword, the set of features providing shape information regarding the word potentially contained in the portion of the input image; applying the set of features to the HMM network; determining a probability for the potential keyword as applied to the path passing through the keyword HMM; and comparing the probability, so determined, relative to an additional probability value so as to provide an indication whether the potential keyword is the keyword.

1. A processor-based method of determining whether a keyword made up of characters is present in a bitmap input image containing words, the words being considered to extend horizontally, the method comprising the steps of: providing a set of previously trained single-character hidden Markov models (HMMs), each single-character HMM having a number of possible contexts, depending on whether the character has an ascender or a descender; concatenating those single-character HMMs that correspond to the characters in the keyword so as to create a keyword HMM, the context of a given single-character HMM used to create the keyword HMM being determined on the basis of whether the keyword contains characters having ascenders or a descenders; constructing an HMM network that includes a path passing through the keyword HMM; locating a portion of the input image potentially containing a word; providing an array of pixel values, referred to as a potential keyword, representing the portion of the input image; horizontally sampling the potential keyword to provide a plurality of segments wherein each segment extends the entire height of the potential keyword and the sampling to provide segments is performed in a manner that is independent of the values of the pixels in the potential keyword; for each segment, generating at least one feature that depends on the values of the pixels in the segment, thereby providing a set of features based on the potential keyword, the set of features providing shape information regarding the word potentially contained in the portion of the input image; applying the set of features to the HMM network; determining a probability for the potential keyword as applied to the path passing through the keyword HMM; and comparing the probability, so determined, relative to an additional probability value so as to provide an indication whether the potential keyword is the keyword. 5. The method of claim 1 wherein: the HMM network includes an HMM that models non-keywords and includes an additional path passing through the non-keyword HMM but not passing through the keyword HMM; the additional probability value is a probability determined for the potential keyword as applied to the additional path; and the indication is whether the probability of the potential keyword as applied to the keyword HMM is sufficiently greater than the probability for the potential keyword as applied to the non-keyword HMM.

9. An apparatus for capturing videos, comprising a processor and a memory, the memory storing instructions for a framework layer of a first programming language, instructions for an application layer of a second programming language other than the first programming language, instructions for an application in the application layer, and instructions for a setting module: the instructions for the setting module are executable by the processor to set a video capture class in the framework layer, the video capture class inherits a class in a video capture bottom layer library and registers a callback function for the video capture bottom layer library; the video capture class is configured to receive a video capture command sent by the application in the application layer, send the video capture command to the video capture bottom layer library which starts to capture video data according to the video capture command, obtain the video data from the video capture bottom layer library by using the callback function, send the video data to an encoder which is pre-set in the framework layer of the first programming language and instruct the encoder to encode the video data, and provide video data codes obtained by the encoder to the application in the application layer.

9. An apparatus for capturing videos, comprising a processor and a memory, the memory storing instructions for a framework layer of a first programming language, instructions for an application layer of a second programming language other than the first programming language, instructions for an application in the application layer, and instructions for a setting module: the instructions for the setting module are executable by the processor to set a video capture class in the framework layer, the video capture class inherits a class in a video capture bottom layer library and registers a callback function for the video capture bottom layer library; the video capture class is configured to receive a video capture command sent by the application in the application layer, send the video capture command to the video capture bottom layer library which starts to capture video data according to the video capture command, obtain the video data from the video capture bottom layer library by using the callback function, send the video data to an encoder which is pre-set in the framework layer of the first programming language and instruct the encoder to encode the video data, and provide video data codes obtained by the encoder to the application in the application layer. 16. The apparatus of claim 9 , wherein the instructions for the application are executable by the processor to send the video capture command to a camera API layer which sends the video capture command to the video capture class in the framework layer of the programming language.

18. An apparatus that is configured to transform an input data stream comprising data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: access a document plan containing one or more messages, wherein messages represent a phrase or a simple sentence and are created in an instance in which the input data stream comprises data that satisfies one or more message requirements; generate a text specification containing one or more phrase specifications that correspond to the one or more messages in the document plan; apply a set of lexicalization rules to each of the one or more messages to populate the one or more phrase specifications, wherein the set of lexicalization rules are specified using a microplanning rule specification language that is configured to hide linguistic complexities from a user and comprise a set of message-level rules and a set of slot-level rules; and realize the text specification to generate a textual output that linguistically describes at least a portion of the input data stream, wherein the textual output is displayable via a user interface.

18. An apparatus that is configured to transform an input data stream comprising data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: access a document plan containing one or more messages, wherein messages represent a phrase or a simple sentence and are created in an instance in which the input data stream comprises data that satisfies one or more message requirements; generate a text specification containing one or more phrase specifications that correspond to the one or more messages in the document plan; apply a set of lexicalization rules to each of the one or more messages to populate the one or more phrase specifications, wherein the set of lexicalization rules are specified using a microplanning rule specification language that is configured to hide linguistic complexities from a user and comprise a set of message-level rules and a set of slot-level rules; and realize the text specification to generate a textual output that linguistically describes at least a portion of the input data stream, wherein the textual output is displayable via a user interface. 25. The apparatus according to claim 18 , wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to at least: apply one or more reference strategies using one or more slot-level rules, wherein the microplanning rule specification language is configured to expresses reference strategies using at least one of a string value, named entity, numeric value, time value, enumerated value type or duration value.

14. A computer program product for detecting an influence caused by changing a source code of an application from which a document object model (DOM) tree and cascading style sheets (CSSs) are extracted, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: saving one or more input operations of a user of the application, a DOM tree, and a CSS for each of one or more times that an instruction is received to check a screen state; emulating, after the source code is changed, the one or more input operations in an operation order, for each of the one or more times; acquiring a DOM tree and CSS for each of the one or more times; comparing the saved DOM tree and CSS with the acquired DOM tree and CSS for each of the one or more times; and outputting a result of the comparison.

14. A computer program product for detecting an influence caused by changing a source code of an application from which a document object model (DOM) tree and cascading style sheets (CSSs) are extracted, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: saving one or more input operations of a user of the application, a DOM tree, and a CSS for each of one or more times that an instruction is received to check a screen state; emulating, after the source code is changed, the one or more input operations in an operation order, for each of the one or more times; acquiring a DOM tree and CSS for each of the one or more times; comparing the saved DOM tree and CSS with the acquired DOM tree and CSS for each of the one or more times; and outputting a result of the comparison. 15. The computer program product of claim 14 , wherein the comparing comprises: specifying, among CSS properties in at least one of the saved CSS and the acquired CSS, a first CSS property used for actual screen display at a specific time among the one or more times; specifying, among the CSS properties in the acquired CSS, a second CSS property used for actual screen display at the same time as the specific time; and comparing the first CSS property and the second CSS property.

19. At least one non-transitory computer-readable storage medium encoded with a plurality of computer-executable instructions that, when executed, perform a method for providing speech output for a speech-enabled application, the method comprising: receiving from the speech-enabled application a text input comprising a text transcription of a desired speech output; generating an audio speech output corresponding to at least a portion of the text input, the audio speech output comprising at least one portion carrying contrastive stress to contrast with at least one other portion of the audio speech output; and providing the audio speech output for the speech-enabled application; wherein the generating comprises: identifying a plurality of tokens of the text input of a same text normalization type for which a contrastive stress pattern is to be applied; identifying at least one token of the plurality of tokens to be rendered with contrastive stress; and assigning contrastive stress to be carried by at least one portion of the audio speech output corresponding to at least one portion of the at least one token of the text input; wherein the assigning comprises: identifying at least one first portion of the at least one token of the plurality of tokens that differs from at least one corresponding first portion of at least one other token of the plurality of tokens, and at least one second portion of the at least one token that does not differ from at least one corresponding second portion of the at least one other token; and assigning contrastive stress to be carried by at least one first portion of the audio speech output corresponding to the identified at least one first portion of the at least one token, but not to at least one second portion of the audio speech output corresponding to the identified at least one second portion of the at least one token.

19. At least one non-transitory computer-readable storage medium encoded with a plurality of computer-executable instructions that, when executed, perform a method for providing speech output for a speech-enabled application, the method comprising: receiving from the speech-enabled application a text input comprising a text transcription of a desired speech output; generating an audio speech output corresponding to at least a portion of the text input, the audio speech output comprising at least one portion carrying contrastive stress to contrast with at least one other portion of the audio speech output; and providing the audio speech output for the speech-enabled application; wherein the generating comprises: identifying a plurality of tokens of the text input of a same text normalization type for which a contrastive stress pattern is to be applied; identifying at least one token of the plurality of tokens to be rendered with contrastive stress; and assigning contrastive stress to be carried by at least one portion of the audio speech output corresponding to at least one portion of the at least one token of the text input; wherein the assigning comprises: identifying at least one first portion of the at least one token of the plurality of tokens that differs from at least one corresponding first portion of at least one other token of the plurality of tokens, and at least one second portion of the at least one token that does not differ from at least one corresponding second portion of the at least one other token; and assigning contrastive stress to be carried by at least one first portion of the audio speech output corresponding to the identified at least one first portion of the at least one token, but not to at least one second portion of the audio speech output corresponding to the identified at least one second portion of the at least one token. 21. The at least one non-transitory computer-readable storage medium of claim 19 , wherein the plurality of tokens are identified based at least in part on at least one indication in the text input that the contrastive stress pattern is desired in association with the plurality of tokens.

1. A method for creating one or more statistical classifiers for recommending one or more applications and one or more computing infrastructures for executing the one or more applications, the method comprising: extracting, by one or more processors, a first set of performance parameters corresponding to the one or more applications and the one or more computing infrastructures from a historical data pertaining to the execution of the one or more applications on the one or more computing infrastructures; selecting, by the one or more processors, a set of application-specific parameters corresponding to the one or more applications and a set of infrastructure-specific parameters corresponding to the one or more computing infrastructures, from the first set of performance parameters, based on one or more statistical techniques, wherein the one or more statistical techniques comprises at least one of Bayesian Information Criteria (BIC), Akaike Information Criteria (AIC), Deviance Information Criteria (DIC) or Gibb's Sampling Algorithm; determining, by the one or more processors: a similarity between each pair of applications from the one or more applications based on the set of application-specific parameters, a similarity between each pair of computing infrastructures from the one or more computing infrastructures based on the set of infrastructure-specific parameters, and a similarity between each combination of an application from the one or more applications and a computing infrastructure from the one or more computing infrastructures, based on the set of application-specific parameters and the set of infrastructure-specific parameters; and creating, by the one or more processors, the one or more statistical classifiers, based on the determined similarity.

1. A method for creating one or more statistical classifiers for recommending one or more applications and one or more computing infrastructures for executing the one or more applications, the method comprising: extracting, by one or more processors, a first set of performance parameters corresponding to the one or more applications and the one or more computing infrastructures from a historical data pertaining to the execution of the one or more applications on the one or more computing infrastructures; selecting, by the one or more processors, a set of application-specific parameters corresponding to the one or more applications and a set of infrastructure-specific parameters corresponding to the one or more computing infrastructures, from the first set of performance parameters, based on one or more statistical techniques, wherein the one or more statistical techniques comprises at least one of Bayesian Information Criteria (BIC), Akaike Information Criteria (AIC), Deviance Information Criteria (DIC) or Gibb's Sampling Algorithm; determining, by the one or more processors: a similarity between each pair of applications from the one or more applications based on the set of application-specific parameters, a similarity between each pair of computing infrastructures from the one or more computing infrastructures based on the set of infrastructure-specific parameters, and a similarity between each combination of an application from the one or more applications and a computing infrastructure from the one or more computing infrastructures, based on the set of application-specific parameters and the set of infrastructure-specific parameters; and creating, by the one or more processors, the one or more statistical classifiers, based on the determined similarity. 2. The method of claim 1 further comprising predicting, by the one or more processors, performance of the one or more applications on each of the one or more computing infrastructures, based on the one or more statistical classifiers.

1. A method of processing documents including determining whether to convert the document into a printable electronic format using a local converter or a remote converter, wherein the remote converter is included in a cloud-based network, the method comprising: storing a decision mapping table cross-referencing three quality levels with three content levels; wherein the three quality levels are: functional quality level suitable for text only documents, normal office quality level for normal usage documents, and presentation quality level representing features of an underlying document; wherein the three content levels are: a first content level of the three content levels comprising content with at least one of a break, a specified font, a bullet, numbering, a specified page alignment, a field, a column, or a specified paragraph format, a second content level of the three content levels comprising content with at least one of a spreadsheet, a picture, a background, or a word art, and a third content level of the three content levels comprising content with at least one of a document comment, a tracked change, or content from a plug-in; wherein the decision mapping table indicates that a presentation quality level and a second content level, a normal quality level and a third content level, and a presentation quality level and a third content level correspond to the remote converter, and the decision mapping table further indicates that remaining quality levels and content levels correspond to the local converter; parsing content within a document associated with a mobile device to determine features of the content; determining a content level for the document based on the features of the content, wherein the content level for the document is indicative of processing resources required to convert the document to a printable electronic format, wherein the content level for the document consists of one of the three content levels: a first content level of the three content levels comprising content with at least one of a break, a specified font, a bullet, numbering, a specified page alignment, a field, a column, or a specified paragraph format, a second content level of the three content levels comprising content with at least one of a spreadsheet, a picture, a background, or a word art, and a third content level of the three content levels comprising content with at least one of a document comment, a tracked change, or content from a plug-in; receiving, at the mobile device, a user selection of an intended quality level relating to rendering the document, wherein the user selects one from among the three quality levels consisting of: functional quality level suitable for text only documents, normal office quality level for normal usage documents, and presentation quality level representing features of an underlying document; providing, by a processor and based on the content level for the document and the intended quality level, a determination on whether to use a local converter or a remote converter to convert the document into the printable electronic format, wherein the local converter is locally accessible by the mobile device and the remote converter is remotely accessible by the mobile device, wherein the providing a determination on whether to use a local converter or a remote converter comprises examining the decision mapping table.

1. A method of processing documents including determining whether to convert the document into a printable electronic format using a local converter or a remote converter, wherein the remote converter is included in a cloud-based network, the method comprising: storing a decision mapping table cross-referencing three quality levels with three content levels; wherein the three quality levels are: functional quality level suitable for text only documents, normal office quality level for normal usage documents, and presentation quality level representing features of an underlying document; wherein the three content levels are: a first content level of the three content levels comprising content with at least one of a break, a specified font, a bullet, numbering, a specified page alignment, a field, a column, or a specified paragraph format, a second content level of the three content levels comprising content with at least one of a spreadsheet, a picture, a background, or a word art, and a third content level of the three content levels comprising content with at least one of a document comment, a tracked change, or content from a plug-in; wherein the decision mapping table indicates that a presentation quality level and a second content level, a normal quality level and a third content level, and a presentation quality level and a third content level correspond to the remote converter, and the decision mapping table further indicates that remaining quality levels and content levels correspond to the local converter; parsing content within a document associated with a mobile device to determine features of the content; determining a content level for the document based on the features of the content, wherein the content level for the document is indicative of processing resources required to convert the document to a printable electronic format, wherein the content level for the document consists of one of the three content levels: a first content level of the three content levels comprising content with at least one of a break, a specified font, a bullet, numbering, a specified page alignment, a field, a column, or a specified paragraph format, a second content level of the three content levels comprising content with at least one of a spreadsheet, a picture, a background, or a word art, and a third content level of the three content levels comprising content with at least one of a document comment, a tracked change, or content from a plug-in; receiving, at the mobile device, a user selection of an intended quality level relating to rendering the document, wherein the user selects one from among the three quality levels consisting of: functional quality level suitable for text only documents, normal office quality level for normal usage documents, and presentation quality level representing features of an underlying document; providing, by a processor and based on the content level for the document and the intended quality level, a determination on whether to use a local converter or a remote converter to convert the document into the printable electronic format, wherein the local converter is locally accessible by the mobile device and the remote converter is remotely accessible by the mobile device, wherein the providing a determination on whether to use a local converter or a remote converter comprises examining the decision mapping table. 2. The method of claim 1 , wherein the local converter is included in at least one of the mobile device, a print engine locally accessible by the mobile device, or a third-party processing module locally accessible by the mobile device.

15. A method, comprising: obtaining, by a device, text to be processed to extract one or more constraints corresponding to an object in the text, the one or more constraints defining values permitted to be associated with the object; associating, by the device, part-of-speech tags with words in the text; extracting, by the device, the one or more constraints based on associating the part-of-speech tags with the words and identifying one or more patterns in the text, generating, by the device, one or more equations based on the one or more constraints; generating, by the device and based on the one or more constraints, positive test data and negative test data for testing values for the object, the positive test data including a first value that satisfies each of the one or more constraints based on the one or more equations, and the negative test data including a second value that violates at least one of the one or more constraints based on the one or more equations; receiving, by the device, existing test data from a memory location; applying, by the device, the positive test data, the negative test data, and the existing test data to a system that is designed based on the text for at least one of: improving software accuracy, reducing security issues, or conserving processing resources; validating, by the device, a classification of the existing test data as having a positive classification or a negative classification; and providing, by the device, for display on a user interface and based on applying the positive test data, the negative test data, and the existing test data, information that identifies: a first particular constraint that the positive test data satisfies, a second particular constraint that the negative test data violates, and the validation of the classification of the existing test data.

15. A method, comprising: obtaining, by a device, text to be processed to extract one or more constraints corresponding to an object in the text, the one or more constraints defining values permitted to be associated with the object; associating, by the device, part-of-speech tags with words in the text; extracting, by the device, the one or more constraints based on associating the part-of-speech tags with the words and identifying one or more patterns in the text, generating, by the device, one or more equations based on the one or more constraints; generating, by the device and based on the one or more constraints, positive test data and negative test data for testing values for the object, the positive test data including a first value that satisfies each of the one or more constraints based on the one or more equations, and the negative test data including a second value that violates at least one of the one or more constraints based on the one or more equations; receiving, by the device, existing test data from a memory location; applying, by the device, the positive test data, the negative test data, and the existing test data to a system that is designed based on the text for at least one of: improving software accuracy, reducing security issues, or conserving processing resources; validating, by the device, a classification of the existing test data as having a positive classification or a negative classification; and providing, by the device, for display on a user interface and based on applying the positive test data, the negative test data, and the existing test data, information that identifies: a first particular constraint that the positive test data satisfies, a second particular constraint that the negative test data violates, and the validation of the classification of the existing test data. 16. The method of claim 15 , further comprising: determining whether the existing test data satisfies the one or more constraints; and where providing the information comprises: providing information that indicates whether the existing test data satisfies the one or more constraints.

11. A method comprising: at a first client computer, opening a master copy of an electronic document in a local editor; at the first client computer, maintaining a first queue, the first queue associated with the local editor; at the first client computer, maintaining a second queue, the second queue associated with a remote editor, the remote editor provided at a second client computer; at the first client computer, detecting a request from the remote editor to perform an edit operation on the electronic document, the remote copy of the electronic document being opened by the remote editor; at the first client computer, performing the edit operation on the master copy of the electronic document in response to the request from the remote editor to perform the edit operation on the remote copy of the electronic document; at the first client computer, updating the second queue with the edit operation; and propagating, by the first client computer, the edit operation to the remote copy of the electronic document.

11. A method comprising: at a first client computer, opening a master copy of an electronic document in a local editor; at the first client computer, maintaining a first queue, the first queue associated with the local editor; at the first client computer, maintaining a second queue, the second queue associated with a remote editor, the remote editor provided at a second client computer; at the first client computer, detecting a request from the remote editor to perform an edit operation on the electronic document, the remote copy of the electronic document being opened by the remote editor; at the first client computer, performing the edit operation on the master copy of the electronic document in response to the request from the remote editor to perform the edit operation on the remote copy of the electronic document; at the first client computer, updating the second queue with the edit operation; and propagating, by the first client computer, the edit operation to the remote copy of the electronic document. 12. The method of claim 11 , wherein the first queue and the second queue are interleaved by time.

87. The data signal in a carrier wave as recited in claim 80 further comprising: second voice signals, the second voice signals being output by the voice user interface with personality.

87. The data signal in a carrier wave as recited in claim 80 further comprising: second voice signals, the second voice signals being output by the voice user interface with personality. 91. The data signal in a carrier wave as recited in claim 87 wherein the second voice signals comprise synthesized voice signals.

47. A method for programming an entirely declarative language program manifesting an entirely declarative system for creating a computer software program, using a computer programming interface, the method comprising: providing a library of declarative elements consisting of descriptions of logic and data in predefined declarative lattice structures configured to instantiate and execute, either alone or in relation to other declarative lattice structures of said declarative language program, wherein each of said declarative lattice structures has one or more configurable meta data properties from the set of properties comprising attributes and sites; obtaining a container programming structure from said library; selecting a logical behavior associated with said container programming structure by setting one or more attributes of said container programming structure; nesting one or more declarative elements within said container programming structure for sequential execution within a context of said container programming structure; selecting a declarative structure type for one or more of said declarative elements, said declarative structure type determining a range of logical behaviors available to a respective declarative lattice structure; and selecting respective logical behaviors of said one or more declarative elements by setting one or more attributes of said one or more declarative elements.

47. A method for programming an entirely declarative language program manifesting an entirely declarative system for creating a computer software program, using a computer programming interface, the method comprising: providing a library of declarative elements consisting of descriptions of logic and data in predefined declarative lattice structures configured to instantiate and execute, either alone or in relation to other declarative lattice structures of said declarative language program, wherein each of said declarative lattice structures has one or more configurable meta data properties from the set of properties comprising attributes and sites; obtaining a container programming structure from said library; selecting a logical behavior associated with said container programming structure by setting one or more attributes of said container programming structure; nesting one or more declarative elements within said container programming structure for sequential execution within a context of said container programming structure; selecting a declarative structure type for one or more of said declarative elements, said declarative structure type determining a range of logical behaviors available to a respective declarative lattice structure; and selecting respective logical behaviors of said one or more declarative elements by setting one or more attributes of said one or more declarative elements. 68. The method of claim 47 , further comprising: said one or more declarative elements transforming into an executable construct.

14. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: obtaining data identifying a set of seed fact pairs, wherein each seed fact pair associates a fact subject phrase with an information phrase; determining that a first sentence matches a first seed fact pair in the set of seed fact pairs, wherein determining that the first sentence matches the first seed fact pair comprises determining that the fact subject phrase and the information phrase from the first seed pair fact both occur in the first sentence separated by one or more terms; extracting, from the first sentence a basic infix-only pattern that includes the one or more terms that separate the fact subject phrase from the information phrase in the first sentence; generating a generalized infix-only extraction pattern from the basic infix-only pattern, wherein generating the generalized infix-only extraction pattern from the basic infix-only pattern comprises: determining that a first term of the one or more terms that separate the fact subject phrase from the information phrase in the first sentence belongs to a first distributionally similar class, and substituting the first distributionally similar class for the first term in the basic infix-only pattern; determining that a second sentence matches the generalized infix-only pattern, comprising determining that the second sentence includes a term that belongs to the first distributionally similar class; and applying the generalized infix-only pattern to the second sentence to extract a candidate fact pair from the second sentence.

14. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: obtaining data identifying a set of seed fact pairs, wherein each seed fact pair associates a fact subject phrase with an information phrase; determining that a first sentence matches a first seed fact pair in the set of seed fact pairs, wherein determining that the first sentence matches the first seed fact pair comprises determining that the fact subject phrase and the information phrase from the first seed pair fact both occur in the first sentence separated by one or more terms; extracting, from the first sentence a basic infix-only pattern that includes the one or more terms that separate the fact subject phrase from the information phrase in the first sentence; generating a generalized infix-only extraction pattern from the basic infix-only pattern, wherein generating the generalized infix-only extraction pattern from the basic infix-only pattern comprises: determining that a first term of the one or more terms that separate the fact subject phrase from the information phrase in the first sentence belongs to a first distributionally similar class, and substituting the first distributionally similar class for the first term in the basic infix-only pattern; determining that a second sentence matches the generalized infix-only pattern, comprising determining that the second sentence includes a term that belongs to the first distributionally similar class; and applying the generalized infix-only pattern to the second sentence to extract a candidate fact pair from the second sentence. 16. The system of claim 14 , the operations further comprising: tagging each word in the fact subject phrase and the information phrase from the first seed fact pair with a respective part-of-speech tag; generating a first sequence of part-of-speech tags for the fact subject phrase of the first seed fact pair and a second sequence of part-of-speech tags for the information phrase of the first seed fact pair, wherein applying the generalized infix-only pattern to the second sentence to extract the candidate fact pair comprises: beginning with a word adjacent to a first end of the infix-only pattern and proceeding away from the pattern in the second sentence, adding a word from the second sentence to a first phrase for each tag in the second sequence, the first phrase being the portion of the second sentence between the last word added and the pattern, each word added to the phrase having a part of speech that matches the part of speech of the corresponding tag in the first sequence; and beginning with a word adjacent to a second end of the infix-only pattern and proceeding away from the pattern in the second sentence, adding a word from the second sentence to a second phrase for each tag in the second sequence, the second phrase being the portion of the second sentence between the last word added and the pattern, each word added to the phrase having a part of speech that matches the part of speech of the corresponding tag in the second sequence; wherein the candidate fact pair comprises the first phrase and the second phrase.

8. A computer-implemented system comprising one or more processor-based devices configured to: access a plurality of computer-implemented directionally distinct relationships among a plurality of computer-implemented objects, wherein the plurality of computer-implemented objects do not represent users of a computer-implemented system; infer automatically a first expertise level of a first person who is a first user of a computer-implemented system from one or more usage behaviors; select one or more computer-implemented objects of the plurality of computer-implemented objects, wherein the selecting is performed in accordance with the first expertise level and at least one of the plurality of the computer-implemented directionally distinct relationships; and deliver the one or more computer-implemented objects to the first person.

8. A computer-implemented system comprising one or more processor-based devices configured to: access a plurality of computer-implemented directionally distinct relationships among a plurality of computer-implemented objects, wherein the plurality of computer-implemented objects do not represent users of a computer-implemented system; infer automatically a first expertise level of a first person who is a first user of a computer-implemented system from one or more usage behaviors; select one or more computer-implemented objects of the plurality of computer-implemented objects, wherein the selecting is performed in accordance with the first expertise level and at least one of the plurality of the computer-implemented directionally distinct relationships; and deliver the one or more computer-implemented objects to the first person. 9. The system of claim 8 , further comprising the one or more processor-based devices configured to: access the plurality of computer-implemented directionally distinct relationships among the plurality of computer-implemented objects in accordance with a first computer-implemented object of the plurality of computer-implemented objects being identified as a context for the access.

1. A tangible computer-readable medium having recorded thereon statements and instructions for execution by a computer of a method to generate at least one mathematical expression describing a performance characteristic of a system, the system associated with variables and with pre-determined data related to the performance characteristic of the system, the method comprising steps of: generating at least one initial mathematical expression having a pre-defined canonical form and being a function of the variables, the at least one initial mathematical expression having operators operating on the variables, the operators being selected from a pre-defined group of operators, the at least one initial mathematical expression describing the performance characteristic of the system; wherein, the variables of the system are representable as a vector {right arrow over (x)} and the canonical form of an expression F({right arrow over (x)}) is representable as F ⁡ ( x ) = w offset + ∑ i = 0 n ⁢ w i × f i ⁡ ( x ) × NL i ⁡ ( x ) , “n” being an integer, w offset , being an offset value, w i being weights, f i (x) including at least one of a polynomial function of the variables and a rational function of the variables, and NL i ({right arrow over (x)}) being a non-linear function of the variables, with NL 0 (x)=1; generating calculated data using the at least one initial mathematical expression; calculating an output of a goal function in accordance with the pre-determined data and the calculated data; determining that the goal function is outside a pre-defined range; and iteratively performing the following steps a-c until an additional output of the goal function is within the pre-defined range: a. modifying at least one input mathematical expression in accordance with a search algorithm to produce at least one modified mathematical expression having the canonical form and being a function of the variables, the search algorithm to search at least the pre-defined group of operators to identify operators with which to modify the at least one input mathematical expression, the at least one input mathematical expression being the at least one initial mathematical expression in a first iteration of steps a-c, the at least one input mathematical expression being the at least one modified mathematical expression in subsequent iterations of steps a-c; b. generating additional calculated data using the at least one modified mathematical expression; and c. calculating the additional output of the goal function based on the additional calculated data and the pre-determined data.

1. A tangible computer-readable medium having recorded thereon statements and instructions for execution by a computer of a method to generate at least one mathematical expression describing a performance characteristic of a system, the system associated with variables and with pre-determined data related to the performance characteristic of the system, the method comprising steps of: generating at least one initial mathematical expression having a pre-defined canonical form and being a function of the variables, the at least one initial mathematical expression having operators operating on the variables, the operators being selected from a pre-defined group of operators, the at least one initial mathematical expression describing the performance characteristic of the system; wherein, the variables of the system are representable as a vector {right arrow over (x)} and the canonical form of an expression F({right arrow over (x)}) is representable as F ⁡ ( x ) = w offset + ∑ i = 0 n ⁢ w i × f i ⁡ ( x ) × NL i ⁡ ( x ) , “n” being an integer, w offset , being an offset value, w i being weights, f i (x) including at least one of a polynomial function of the variables and a rational function of the variables, and NL i ({right arrow over (x)}) being a non-linear function of the variables, with NL 0 (x)=1; generating calculated data using the at least one initial mathematical expression; calculating an output of a goal function in accordance with the pre-determined data and the calculated data; determining that the goal function is outside a pre-defined range; and iteratively performing the following steps a-c until an additional output of the goal function is within the pre-defined range: a. modifying at least one input mathematical expression in accordance with a search algorithm to produce at least one modified mathematical expression having the canonical form and being a function of the variables, the search algorithm to search at least the pre-defined group of operators to identify operators with which to modify the at least one input mathematical expression, the at least one input mathematical expression being the at least one initial mathematical expression in a first iteration of steps a-c, the at least one input mathematical expression being the at least one modified mathematical expression in subsequent iterations of steps a-c; b. generating additional calculated data using the at least one modified mathematical expression; and c. calculating the additional output of the goal function based on the additional calculated data and the pre-determined data. 4. The tangible computer-readable medium of claim 1 wherein, the goal function is a multi-objective goal function for minimizing error and for constraining complexity.

7. The method of claim 6 , wherein the RNN iteratively predicts a sequence of words to combine as the caption for the target image based upon probability distributions computed in accordance with weight factors in multiple iterations.

7. The method of claim 6 , wherein the RNN iteratively predicts a sequence of words to combine as the caption for the target image based upon probability distributions computed in accordance with weight factors in multiple iterations. 8. The method of claim 7 , wherein the collection of keywords is injected in the RNN for each of the multiple iterations to modulate the weight factors used to predict the sequence.