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16. The computing device of claim 11 , wherein the contextual features for a specific answer include a relevance to its corresponding question, and wherein a lack of relevance of the specific answer to its corresponding question is indicative of a deceptive answer.

16. The computing device of claim 11 , wherein the contextual features for a specific answer include a relevance to its corresponding question, and wherein a lack of relevance of the specific answer to its corresponding question is indicative of a deceptive answer. 17. The computing device of claim 16 , wherein the one or more processors are further configured to determine the relevance of each answer to its corresponding question by utilizing at least one of: (i) a vector space model; (ii) a translation model; and (iii) a topic model.

10. The computer-readable storage medium of claim 8 , wherein the computer-executable instructions further comprise: code for determining the association scores between the one or more keywords and their friend keywords based at least in part upon positions of the one or more keywords and their friend keywords within a hierarchy of keywords derived from the master keyword list.

10. The computer-readable storage medium of claim 8 , wherein the computer-executable instructions further comprise: code for determining the association scores between the one or more keywords and their friend keywords based at least in part upon positions of the one or more keywords and their friend keywords within a hierarchy of keywords derived from the master keyword list. 13. The computer-readable storage medium of claim 10 , wherein each of the association scores is a function of a distance between connected nodes within the hierarchy of keywords derived from the master keyword list.

1. A method comprising the steps of: receiving a request over a network from a user for data related to a context, wherein the request is a URL comprising a context query, wherein the context query comprises at least one context criteria; parsing and translating, via the network, the at least one context criteria, whereby the at least one context criteria is parsed and translated to a standardized format; disambiguating, via the network, the at least one parsed and translated context criteria, whereby the at least one parsed and translated context criteria is resolved to canonical values; formulating a network data query based on the at least one disambiguated context criteria so as to search, via the network, for user profile data, social network data, spatial data, temporal data and topical data that is available via the network and relates to the context query so as to identify at least one data object that relates to the at least one disambiguated context criteria; checking permissions, via the network, relating to the at least one data object to determine if the user is permitted to access the at least one data object; if the user is permitted to access the at least one data object, transmitting, over the network, a reference to the at least one data object over the network to the user, wherein the reference to the at least one data object contains sufficient information to enable the user to access the at least one data object over the network.

1. A method comprising the steps of: receiving a request over a network from a user for data related to a context, wherein the request is a URL comprising a context query, wherein the context query comprises at least one context criteria; parsing and translating, via the network, the at least one context criteria, whereby the at least one context criteria is parsed and translated to a standardized format; disambiguating, via the network, the at least one parsed and translated context criteria, whereby the at least one parsed and translated context criteria is resolved to canonical values; formulating a network data query based on the at least one disambiguated context criteria so as to search, via the network, for user profile data, social network data, spatial data, temporal data and topical data that is available via the network and relates to the context query so as to identify at least one data object that relates to the at least one disambiguated context criteria; checking permissions, via the network, relating to the at least one data object to determine if the user is permitted to access the at least one data object; if the user is permitted to access the at least one data object, transmitting, over the network, a reference to the at least one data object over the network to the user, wherein the reference to the at least one data object contains sufficient information to enable the user to access the at least one data object over the network. 10. The method of claim 1 wherein the reference to the at least one data object is a hyperlink embedded in a webpage, wherein the webpage is transmitted to the user.

3. The mobile application search system of claim 1 , wherein the mobile application search engine includes a mobile application database in which a plurality of applications are indexed.

3. The mobile application search system of claim 1 , wherein the mobile application search engine includes a mobile application database in which a plurality of applications are indexed. 4. The mobile application search system of claim 3 , wherein the mobile application database stores text information including a title, a description, and a comment of a mobile application registered in a mobile application market in a bag of words (BOW) format.

1. One or more computer-storage media embodying computer-useable instructions for performing a method comprising: displaying a textbox configured to receive input from a handheld writing device, wherein all input received from the handheld writing device in the textbox is interpreted as one or more standard textbox operations and not as handwriting input; based on one or more user actions, displaying an expanded textbox over the textbox, wherein the expanded textbox covers the textbox and is configured to receive input from the handheld writing device, wherein all input received from the handheld writing device in the expanded textbox is interpreted as handwriting input that is initially displayed as digital ink within the expanded textbox and then converted to text within the expanded textbox after the digital ink has been recognized as the text using a recognizer; and based on a location of the textbox, determining an alignment of the expanded textbox relative to the textbox.

1. One or more computer-storage media embodying computer-useable instructions for performing a method comprising: displaying a textbox configured to receive input from a handheld writing device, wherein all input received from the handheld writing device in the textbox is interpreted as one or more standard textbox operations and not as handwriting input; based on one or more user actions, displaying an expanded textbox over the textbox, wherein the expanded textbox covers the textbox and is configured to receive input from the handheld writing device, wherein all input received from the handheld writing device in the expanded textbox is interpreted as handwriting input that is initially displayed as digital ink within the expanded textbox and then converted to text within the expanded textbox after the digital ink has been recognized as the text using a recognizer; and based on a location of the textbox, determining an alignment of the expanded textbox relative to the textbox. 6. The one or more computer-storage media of claim 1 , wherein the one or more standard textbox operations comprise one or more of: text select, cut, copy, paste, delete, and undo.

9. At least one non-transitory computer-readable storage device storing computer-executable instructions for pausing a VoiceXML dialog being process by a multimodal application, the computer-executable instructions comprising a multimodal application capable of operating on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, the multimodal application operatively coupled to a VoiceXML interpreter, the VoiceXML interpreter capable of interpreting the VoiceXML dialog to be paused or resumed, the computer-executable instructions, when executed by at least one processor, performing a method of: providing a script variable to hold a pause keyword or a resume keyword that a script evaluates to when at least a portion of a user utterance is received via the multimodal application, and matches one or more words in a pause control grammar specified by the multimodal application; generating a pause event when the VoiceXML interpreter evaluates the script to the pause keyword; wherein generating the pause event is supported by utilizing a VoiceXML Form Interpretation Algorithm (FIA); wherein the FIA interprets the dialog instructions sequentially to identify the dialogs operating under one or more non-voice modes or one or more voice modes; responsive to the pause event, temporarily pausing the VoiceXML dialog by the VoiceXML interpreter; generating a resume event when the VoiceXML interpreter evaluates the script to the resume keyword; and responsive to the resume event, resuming the VoiceXML dialog.

9. At least one non-transitory computer-readable storage device storing computer-executable instructions for pausing a VoiceXML dialog being process by a multimodal application, the computer-executable instructions comprising a multimodal application capable of operating on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, the multimodal application operatively coupled to a VoiceXML interpreter, the VoiceXML interpreter capable of interpreting the VoiceXML dialog to be paused or resumed, the computer-executable instructions, when executed by at least one processor, performing a method of: providing a script variable to hold a pause keyword or a resume keyword that a script evaluates to when at least a portion of a user utterance is received via the multimodal application, and matches one or more words in a pause control grammar specified by the multimodal application; generating a pause event when the VoiceXML interpreter evaluates the script to the pause keyword; wherein generating the pause event is supported by utilizing a VoiceXML Form Interpretation Algorithm (FIA); wherein the FIA interprets the dialog instructions sequentially to identify the dialogs operating under one or more non-voice modes or one or more voice modes; responsive to the pause event, temporarily pausing the VoiceXML dialog by the VoiceXML interpreter; generating a resume event when the VoiceXML interpreter evaluates the script to the resume keyword; and responsive to the resume event, resuming the VoiceXML dialog. 12. The at least one non-transitory computer-readable storage device of claim 9 , wherein the method further comprises generating by the multimodal application a pause event when focus changes from a graphical user interface (GUI) window presented by the multimodal application to a different window.

65. The method of claim 60 , wherein step (A) includes selectively transmitting the one or more items of content from the first group of items to one or more nodes in the first set of nodes.

65. The method of claim 60 , wherein step (A) includes selectively transmitting the one or more items of content from the first group of items to one or more nodes in the first set of nodes. 66. The method of claim 65 , wherein step (A) includes selectively transmitting the one or more items of content from the first group of items to one or more nodes in the first set of nodes based on preferences defined for the respective nodes.

15. A computer system comprising: means for storing an acoustic description of each of a plurality of vocabulary words; means for receiving an acoustic description of one or more utterances to be recognized; recognition means for comparing the acoustic descriptions of utterances to be recognized against the acoustic descriptions of a recognition vocabulary comprised of one or more of said vocabulary words to select which of the words in said recognitino vocabulary most probably corresponds to said one or more utterances; a data structure representing one or more words, said data structure being other than a list of said vocabulary words; means for using said data structure for a purpose independent both of indicating which words are vocabulary words and of indicating the probability that individual vocabulary words will be recognized as corresponding to a given utterance; probability altering means for determining which of said vocabulary words are represented by said data structure and for using that determination to alter the probability that each of said vocabulary words will be selected as corresponding to a given utterance.

15. A computer system comprising: means for storing an acoustic description of each of a plurality of vocabulary words; means for receiving an acoustic description of one or more utterances to be recognized; recognition means for comparing the acoustic descriptions of utterances to be recognized against the acoustic descriptions of a recognition vocabulary comprised of one or more of said vocabulary words to select which of the words in said recognitino vocabulary most probably corresponds to said one or more utterances; a data structure representing one or more words, said data structure being other than a list of said vocabulary words; means for using said data structure for a purpose independent both of indicating which words are vocabulary words and of indicating the probability that individual vocabulary words will be recognized as corresponding to a given utterance; probability altering means for determining which of said vocabulary words are represented by said data structure and for using that determination to alter the probability that each of said vocabulary words will be selected as corresponding to a given utterance. 21. A computer system as described in claim 15 wherein said data structure represents a body of text.

9. The con device according to claim 6 , wherein the circuitry is further configured to obtain a recognition information of the target object, and control the display to display an indication of the recognition information associated with the target object.

9. The con device according to claim 6 , wherein the circuitry is further configured to obtain a recognition information of the target object, and control the display to display an indication of the recognition information associated with the target object. 10. The control device according to claim 9 , wherein the indication of the recognition information is a marker that is superimposed on the captured image and that is disposed adjacently to the target object.

6. The computer-implemented method of claim 3 , wherein the interaction involving outputs of performing the document capture process further comprises: determining that the electronic document exists in an archive of electronic documents maintained for the user; and providing the user with access to the electronic document.

6. The computer-implemented method of claim 3 , wherein the interaction involving outputs of performing the document capture process further comprises: determining that the electronic document exists in an archive of electronic documents maintained for the user; and providing the user with access to the electronic document. 7. The computer-implemented method of claim 6 , wherein the user is provided with access to the electronic document for a subscription period.

15. A computer program product residing on a storage disk having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: providing a framework for building a visual representation of a product concept, the visual representation including one or more of a textual component or a graphical component; receiving a designation of a first portion of at least one of the textual component or the graphical component as a dynamic element, a second portion of the at least one of the textual component or the graphical component not being designated as the dynamic element; associating the dynamic element with variants; receiving a selection of a first variant of the variants, the variants including the first variant, a second variant, and a third variant; in response to the selection, displaying a constraint indicator adjacent the second variant, the constraint indicator visually representing an undesirability of displaying the first variant and the second variant within a same visual representation; in response to receiving the selection, displaying an allowability indicator immediately adjacent the third variant, the allowability indicator visually representing a desirability of displaying the first variant and the third variant within the same visual representation; and generating a first instantiation of the visual representation including the first variant as the dynamic element.

15. A computer program product residing on a storage disk having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: providing a framework for building a visual representation of a product concept, the visual representation including one or more of a textual component or a graphical component; receiving a designation of a first portion of at least one of the textual component or the graphical component as a dynamic element, a second portion of the at least one of the textual component or the graphical component not being designated as the dynamic element; associating the dynamic element with variants; receiving a selection of a first variant of the variants, the variants including the first variant, a second variant, and a third variant; in response to the selection, displaying a constraint indicator adjacent the second variant, the constraint indicator visually representing an undesirability of displaying the first variant and the second variant within a same visual representation; in response to receiving the selection, displaying an allowability indicator immediately adjacent the third variant, the allowability indicator visually representing a desirability of displaying the first variant and the third variant within the same visual representation; and generating a first instantiation of the visual representation including the first variant as the dynamic element. 18. The computer program product of claim 15 , wherein the associating of the dynamic element with the variants includes receiving a user input including the variants.

1. A method for generating a representation of a document from eXtensible Markup Language (XML) code describing the document, comprising: executing by a processor the following steps: substitution-processing the XML code describing the document to generate substitution-processed XML code, comprising: identifying, within the XML code describing the document, a conditional logic portion that comprises an expression and data; determining a Boolean value of the expression; modifying, if the determined value is “true,” the XML code describing the document by replacing the conditional logic portion with the data; and modifying, if the determined value is “false,” the XML code describing the document by removing the conditional logic portion; composition-processing the substitution-processed XML code to generate composition-processed XML code, comprising: identifying, within the substitution-processed XML code, content that is to be flowed; identifying, within the substitution-processed XML code, a template through which the identified content is to be flowed; determining whether the identified content fits within one instance of the identified template; and modifying, if the identified content does not fit within one page of the identified template, the substitution-processed XML code in order to specify an additional instance of the identified template; imposition-processing the composition-processed XML code to generate imposition-processed XML code, wherein imposition-processing comprises: identifying a code portion within the composition-processed XML code that is specified as being a logical page; identifying a requested physical page size that represents a physical sheet of material; and modifying the composition-processed XML code in order to implement the requested physical page size by specifying one or more physical pages, wherein a physical page includes multiple logical pages, and wherein modifying the composition-processed XML code comprises changing a position of a <page> tag within the composition-processed XML code; and generating, based on the imposition-processed XML code, the representation of the document using a page description language.

1. A method for generating a representation of a document from eXtensible Markup Language (XML) code describing the document, comprising: executing by a processor the following steps: substitution-processing the XML code describing the document to generate substitution-processed XML code, comprising: identifying, within the XML code describing the document, a conditional logic portion that comprises an expression and data; determining a Boolean value of the expression; modifying, if the determined value is “true,” the XML code describing the document by replacing the conditional logic portion with the data; and modifying, if the determined value is “false,” the XML code describing the document by removing the conditional logic portion; composition-processing the substitution-processed XML code to generate composition-processed XML code, comprising: identifying, within the substitution-processed XML code, content that is to be flowed; identifying, within the substitution-processed XML code, a template through which the identified content is to be flowed; determining whether the identified content fits within one instance of the identified template; and modifying, if the identified content does not fit within one page of the identified template, the substitution-processed XML code in order to specify an additional instance of the identified template; imposition-processing the composition-processed XML code to generate imposition-processed XML code, wherein imposition-processing comprises: identifying a code portion within the composition-processed XML code that is specified as being a logical page; identifying a requested physical page size that represents a physical sheet of material; and modifying the composition-processed XML code in order to implement the requested physical page size by specifying one or more physical pages, wherein a physical page includes multiple logical pages, and wherein modifying the composition-processed XML code comprises changing a position of a <page> tag within the composition-processed XML code; and generating, based on the imposition-processed XML code, the representation of the document using a page description language. 12. The method of claim 1 , wherein imposition-processing the composition-processed XML code to generate imposition-processed XML code comprises modifying the composition-processed XML code in order to specify a “cut” mark.

1. A document administration system, comprising: a plurality of document storing apparatuses; and a server apparatus connected the plurality of document storing apparatuses via a network, wherein each of the plurality of document storing apparatuses is controlled by a processor and includes: a plurality of boxes for storing various information in a sorted manner; and a document storing device for making the document storing apparatus store a document in one of the boxes, wherein the server apparatus is controlled by another processor and includes: a document storing apparatus registering portion for registering information on each of the document storing apparatuses; a box information obtaining portion for obtaining information on the boxes from each of the document storing apparatuses; a storing request receiving portion for receiving a storing request of the document; a storing destination deciding portion for automatically deciding which one of the plurality of document storing apparatuses and which one of the plurality of boxes thereof for actually storing the document, based on any one or more of information including information on the document corresponding to the storing request received by the storing request receiving portion, information on the document storing apparatuses registered in the document storing apparatus registering portion, and information on the boxes obtained by the box information obtaining portion; and a controller for transmitting the document to the one of the document storing apparatuses having the one of the boxes selected by the storing destination deciding portion and making the one document storing apparatus store the document in the one of the boxes.

1. A document administration system, comprising: a plurality of document storing apparatuses; and a server apparatus connected the plurality of document storing apparatuses via a network, wherein each of the plurality of document storing apparatuses is controlled by a processor and includes: a plurality of boxes for storing various information in a sorted manner; and a document storing device for making the document storing apparatus store a document in one of the boxes, wherein the server apparatus is controlled by another processor and includes: a document storing apparatus registering portion for registering information on each of the document storing apparatuses; a box information obtaining portion for obtaining information on the boxes from each of the document storing apparatuses; a storing request receiving portion for receiving a storing request of the document; a storing destination deciding portion for automatically deciding which one of the plurality of document storing apparatuses and which one of the plurality of boxes thereof for actually storing the document, based on any one or more of information including information on the document corresponding to the storing request received by the storing request receiving portion, information on the document storing apparatuses registered in the document storing apparatus registering portion, and information on the boxes obtained by the box information obtaining portion; and a controller for transmitting the document to the one of the document storing apparatuses having the one of the boxes selected by the storing destination deciding portion and making the one document storing apparatus store the document in the one of the boxes. 3. The document administration system as recited in claim 1 , wherein the storing destination deciding portion of the server apparatus decides the one of the document storing apparatuses and the one of the boxes thereof as a storing destination based on a size of the document to be stored and a free space of each of the boxes of each of the document storing apparatuses.

1. A system comprising: a data store configured to store data items and probabilities; and a processor in communication with the data store, the processor configured to execute specific computer-executable instructions to at least: receive information regarding a first data item; determine a geographic location of the first data item; determine, based at least in part on a risk model, an event probability associated with a geographic region, the event probability indicating a probability that an event affecting the geographic region will occur, the geographic region including the geographic location of the first data item; obtain, from the data store, a plurality of data items, wherein each of the plurality of data items is associated with a respective geographic location in the geographic region; determine, based at least in part on the risk model, the event probability, and one or more attributes of the first data item, a probability that the event will change a first attribute of the first data item, and a predicted attribute change to the first attribute of the first data item; for individual data items of the plurality of data items, determine, based at least in part on the risk model, the event probability, and one or more attributes of the data item, a probability that the event will change the first attribute of the data item, and a predicted change to the first attribute of the data item; determine a probability associated with the geographic region based at least in part on the event probability, the probabilities that the event will change the first attributes, and the predicted changes to the first attributes; determine a probability category of the first data item based at least in part on: the probability associated with the geographic region, the probability that the event will change the first attribute of the first data item, and the probabilities that the event will change the first attribute of individual data items of the plurality of data items; generate for display a user interface, the user interface including at least: a geographic map identifying the geographic region, the geographic location of the first data item, and the geographic locations of the plurality of items, wherein a shading of an icon displayed at the geographic location of the first data item indicates the probability category of the first data item, and wherein a size of the icon indicates the predicted change to the first attribute of the first data item; and cause display of the user interface.

1. A system comprising: a data store configured to store data items and probabilities; and a processor in communication with the data store, the processor configured to execute specific computer-executable instructions to at least: receive information regarding a first data item; determine a geographic location of the first data item; determine, based at least in part on a risk model, an event probability associated with a geographic region, the event probability indicating a probability that an event affecting the geographic region will occur, the geographic region including the geographic location of the first data item; obtain, from the data store, a plurality of data items, wherein each of the plurality of data items is associated with a respective geographic location in the geographic region; determine, based at least in part on the risk model, the event probability, and one or more attributes of the first data item, a probability that the event will change a first attribute of the first data item, and a predicted attribute change to the first attribute of the first data item; for individual data items of the plurality of data items, determine, based at least in part on the risk model, the event probability, and one or more attributes of the data item, a probability that the event will change the first attribute of the data item, and a predicted change to the first attribute of the data item; determine a probability associated with the geographic region based at least in part on the event probability, the probabilities that the event will change the first attributes, and the predicted changes to the first attributes; determine a probability category of the first data item based at least in part on: the probability associated with the geographic region, the probability that the event will change the first attribute of the first data item, and the probabilities that the event will change the first attribute of individual data items of the plurality of data items; generate for display a user interface, the user interface including at least: a geographic map identifying the geographic region, the geographic location of the first data item, and the geographic locations of the plurality of items, wherein a shading of an icon displayed at the geographic location of the first data item indicates the probability category of the first data item, and wherein a size of the icon indicates the predicted change to the first attribute of the first data item; and cause display of the user interface. 3. The system of claim 1 , wherein the processor is configured to determine the probability associated with the geographic region based at least in part on one or more previous events associated with the geographic region.

25. A non-transitory computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause one or more computers to perform operations comprising: providing, to a client device, information for presenting a search engine user interface for a third party content provider; receiving, from the client device, a search query entered using the search engine user interface; processing the search query to determine a context identifier for a context file; retrieving a context file from the third party content provider identified by the context identifier; modifying the search query using one or more commands to produce a context processed search query, wherein the one or more commands are contained in the context file; providing the context processed search query to a search engine; obtaining, from the search engine, context processed search results responsive to the context processed search query; and providing the context processed search results to the client device.

25. A non-transitory computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause one or more computers to perform operations comprising: providing, to a client device, information for presenting a search engine user interface for a third party content provider; receiving, from the client device, a search query entered using the search engine user interface; processing the search query to determine a context identifier for a context file; retrieving a context file from the third party content provider identified by the context identifier; modifying the search query using one or more commands to produce a context processed search query, wherein the one or more commands are contained in the context file; providing the context processed search query to a search engine; obtaining, from the search engine, context processed search results responsive to the context processed search query; and providing the context processed search results to the client device. 31. The non-transitory computer-readable medium of claim 25 , wherein providing the context processed search results to the client device comprises performing post-processing operations on the context processed search results in accordance with the commands.

11. The computing device of claim 10 , wherein the processor is further configured to execute instructions to at least one of: determine a root node of the data structure, distinguish between a node identifiable as useful and a node identifiable as useless progressively from a lowest level of the data structure to the highest level thereof, and identify at least one path of the data structure for pruning of the connectivity descriptors.

11. The computing device of claim 10 , wherein the processor is further configured to execute instructions to at least one of: determine a root node of the data structure, distinguish between a node identifiable as useful and a node identifiable as useless progressively from a lowest level of the data structure to the highest level thereof, and identify at least one path of the data structure for pruning of the connectivity descriptors. 12. The computing device of claim 11 , wherein the processor is further configured to execute instructions to solely transmit a parent node of the data structure to a final list of regular expressions related to the text-matching of the strings with the elements of the electronic circuit if the parent node has all child nodes thereof deemed useless.

5. The apparatus of claim 2 wherein said identifying means further comprises: a new-speaker identifier, coupled to said status detector, for comparing each closed caption character in said sequence of closed caption characters to predefined criteria and for generating a control signal if said closed caption character meets said predefined criteria.

5. The apparatus of claim 2 wherein said identifying means further comprises: a new-speaker identifier, coupled to said status detector, for comparing each closed caption character in said sequence of closed caption characters to predefined criteria and for generating a control signal if said closed caption character meets said predefined criteria. 6. The apparatus of claim 5 wherein said predefined criteria is a set of special closed caption characters that identify new speakers.

7. A system for generating a database query based on a query template comprising a plurality of query language keywords, a plurality of variables, and a plurality of template-tokens, the system comprising: means for receiving one or more values each associated with a respective one of the plurality of variables; and means for transforming the query template into the database query based on the one or more values, the plurality of variables, and the plurality of template-tokens, wherein the template-tokens include an optional-section token defining a query-template-section and associated with one or more of the plurality of variables, and the means for transforming the template query into the database query comprises: means for processing each of said plurality of template-tokens, said means for processing performing processing including determining whether the template-token being processed is an optional-section token; in response to a determination that the template-token being processed is not an optional-section-token, replacing the token with a portion of a database query; and in response to a determination that the template-token being processed is an optional-section token, determining whether all of said plurality of variables associated with the query-template section are associated with a null value; means for replacing the token with a portion of a database query based on a value of one or more variables from among said plurality of variables associated with the query-template section in response to determining that not all of said plurality of variables associated with the query-template section are associated with a null value; and means for omitting the query-template-section from the database query in response to determining that all of said plurality of variables associated with the query-template section are associated with a null value.

7. A system for generating a database query based on a query template comprising a plurality of query language keywords, a plurality of variables, and a plurality of template-tokens, the system comprising: means for receiving one or more values each associated with a respective one of the plurality of variables; and means for transforming the query template into the database query based on the one or more values, the plurality of variables, and the plurality of template-tokens, wherein the template-tokens include an optional-section token defining a query-template-section and associated with one or more of the plurality of variables, and the means for transforming the template query into the database query comprises: means for processing each of said plurality of template-tokens, said means for processing performing processing including determining whether the template-token being processed is an optional-section token; in response to a determination that the template-token being processed is not an optional-section-token, replacing the token with a portion of a database query; and in response to a determination that the template-token being processed is an optional-section token, determining whether all of said plurality of variables associated with the query-template section are associated with a null value; means for replacing the token with a portion of a database query based on a value of one or more variables from among said plurality of variables associated with the query-template section in response to determining that not all of said plurality of variables associated with the query-template section are associated with a null value; and means for omitting the query-template-section from the database query in response to determining that all of said plurality of variables associated with the query-template section are associated with a null value. 10. The system of claim 7 , wherein the query template is associated with a metadata mapping associating the plurality of variables to a data model of the database.

1. A system, comprising: at least one processor; one or more memories, operatively coupled to the processor, for storing logical instructions wherein execution of the logical instructions by the processor results in the performing of at least the following operations: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign, identifying a change made to the paid portion of the search advertising campaign, determining, based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in the one or more memories in association with an indication of the change.

1. A system, comprising: at least one processor; one or more memories, operatively coupled to the processor, for storing logical instructions wherein execution of the logical instructions by the processor results in the performing of at least the following operations: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign, identifying a change made to the paid portion of the search advertising campaign, determining, based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in the one or more memories in association with an indication of the change. 3. The system of claim 1 wherein the first and second volumes of search traffic comprise traffic arising from unpaid search listings.

2. The non-transitory machine-readable storage medium of claim 1 , wherein: the feature is a feature that was previously determined to be a feature capable of distinguishing the document image or a document that comprises the document image, and the feature was previously identified by analysis of a plurality of training documents each having at least one unique feature different from at least one of the other training documents.

2. The non-transitory machine-readable storage medium of claim 1 , wherein: the feature is a feature that was previously determined to be a feature capable of distinguishing the document image or a document that comprises the document image, and the feature was previously identified by analysis of a plurality of training documents each having at least one unique feature different from at least one of the other training documents. 7. The non-transitory machine-readable storage medium of claim 2 , wherein: the associating the document image with the class further comprises: determining a value from the document image, and determining a reliability index of the decision tree, wherein the reliability index is based on the identified feature of the document image.

1. A method in a computer system for generating a shape feature probability matrix for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters each sample handwritten character representing a character and having a sequence of one or more strokes each stroke represented by one of a plurality of shape features that describes a shape of the stroke; determining for each sample handwritten character a shape feature string that represents that character, the shape feature string having the shape feature of each stroke in the sequence of one or more strokes for that character, each of the shape features in a shape feature string having a place within the shape feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible combination of pairs of the plurality of shape features, generating a match count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings, in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings, and in which each of the pair of shape feature strings represents the same character; generating a total count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings and in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the combination of the shape features in the shape feature probability matrix, so that the stored probability values can be used to recognize handwritten characters.

1. A method in a computer system for generating a shape feature probability matrix for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters each sample handwritten character representing a character and having a sequence of one or more strokes each stroke represented by one of a plurality of shape features that describes a shape of the stroke; determining for each sample handwritten character a shape feature string that represents that character, the shape feature string having the shape feature of each stroke in the sequence of one or more strokes for that character, each of the shape features in a shape feature string having a place within the shape feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible combination of pairs of the plurality of shape features, generating a match count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings, in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings, and in which each of the pair of shape feature strings represents the same character; generating a total count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings and in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the combination of the shape features in the shape feature probability matrix, so that the stored probability values can be used to recognize handwritten characters. 3. The method of claim 1 wherein each shape feature string has a feature length indicating the number of feature shapes in the shape feature string and wherein generating the match count includes: for each possible character, for each of the plurality of shape features, for each of a plurality of possible places within a feature string, for each of a plurality of possible feature lengths, generating a character/shape/place/length count of a number of times that the shape feature occurs at the place within a shape feature string representing the character and having the feature length; and for each possible combination of pairs of the plurality of shape features, for each of the plurality of possible places within a feature string, for each of the possible feature lengths, multiplying the character/shape/place/length count for one of the shape features of the combination by the character/shape/place/length count for the other shape feature of the combination for the place and the feature length to generate a product; and accumulating the generated products as the match count for the combination of shape features for the character; and totaling the accumulated products as the match count for the combination of shape features.

3. The method as claimed in claim 1 , wherein a portable controller is used for control or operation, the method further comprising picking up the spoken commands and forwarding the spoken commands to a speech recognition unit using the portable controller.

3. The method as claimed in claim 1 , wherein a portable controller is used for control or operation, the method further comprising picking up the spoken commands and forwarding the spoken commands to a speech recognition unit using the portable controller. 4. The method as claimed in claim 3 , further comprising identifying the portable controller using a unique ID for the portable controller.

8. The method of claim 1 , wherein the plurality of different parsers includes a location parser that outputs location parsed tokens and a synonym parser that outputs synonym parsed tokens.

8. The method of claim 1 , wherein the plurality of different parsers includes a location parser that outputs location parsed tokens and a synonym parser that outputs synonym parsed tokens. 9. The method of claim 8 , wherein: the location parsed tokens include a string identifying a known geographic location and one or more properties of the string, and each property includes geographic coordinates corresponding to the geographic location and a confidence value that indicates a degree of likelihood that the analyzed tokens analyzed by the location parser are describing the known geographic location.

9. The method as claimed in claim 1 , wherein the matching score is equal to the product of the column score and a fifth weighted value plus the product of the row score, a sixth weighted value and a normalization parameter.

9. The method as claimed in claim 1 , wherein the matching score is equal to the product of the column score and a fifth weighted value plus the product of the row score, a sixth weighted value and a normalization parameter. 10. The method as claimed in claim 9 , wherein the normalization parameter is equal to the amount of elements in each row of the matching matrix divided by the amount of elements in each column of the matching matrix.

15. The method of claim 12 , further comprising determining a new parser based on the plurality of updated counters.

15. The method of claim 12 , further comprising determining a new parser based on the plurality of updated counters. 16. The method of claim 15 , wherein determining a new parser comprises determining a change in states of at least one counter.

8. A method for detecting an anatomical object in a non-training medical device image, comprising: receiving a plurality of non-training medical device images produced by a medical imaging device, wherein the anatomical object has not yet been identified in the plurality of non-training medical device images when received; applying a non-training medical device image from the plurality of non-training medical device images to a classifier having a plurality of stages simultaneously, wherein a first stage of the plurality of stages and a second stage of the plurality of stages each includes a strong learner formed from a plurality of weak learners, and the weak learners in the second stage include a plurality of the weak learners included in the first stage; and identifying the non-training medical device image as being positive of showing the anatomical object based on the application the medical device image to the classifier.

8. A method for detecting an anatomical object in a non-training medical device image, comprising: receiving a plurality of non-training medical device images produced by a medical imaging device, wherein the anatomical object has not yet been identified in the plurality of non-training medical device images when received; applying a non-training medical device image from the plurality of non-training medical device images to a classifier having a plurality of stages simultaneously, wherein a first stage of the plurality of stages and a second stage of the plurality of stages each includes a strong learner formed from a plurality of weak learners, and the weak learners in the second stage include a plurality of the weak learners included in the first stage; and identifying the non-training medical device image as being positive of showing the anatomical object based on the application the medical device image to the classifier. 9. The method of claim 8 , wherein the classifier is an AdaBoost classifier.

50. The computerized composer set forth in claim 45 wherein said embedded control words include a define area control word and an activate area control word; said third indicia including define named area indicia for enabling said computer means to respond to said first indicia receipt of a define area control word to establish in a separate storage a plurality of parameter indicators of the typographic type relating to a named area for receiving diverted text/graphics signals; and further including activate area control word indicia responsive to the embedded activate area control words for selecting predetermined ones of said received unformatted text/graphics signals for diversion for separate storage in accordance with the defined named area and for enabling said computer means to utilize the second indicia for formatting such selected unformatted text/graphics signals to be formatted to said separate storage for later placement on a logical page.

50. The computerized composer set forth in claim 45 wherein said embedded control words include a define area control word and an activate area control word; said third indicia including define named area indicia for enabling said computer means to respond to said first indicia receipt of a define area control word to establish in a separate storage a plurality of parameter indicators of the typographic type relating to a named area for receiving diverted text/graphics signals; and further including activate area control word indicia responsive to the embedded activate area control words for selecting predetermined ones of said received unformatted text/graphics signals for diversion for separate storage in accordance with the defined named area and for enabling said computer means to utilize the second indicia for formatting such selected unformatted text/graphics signals to be formatted to said separate storage for later placement on a logical page. 51. The computerized composer set forth in claim 50, further including concatenating indicia within said define area indicia for logically linking named areas in a predetermined sequence such that said diverted text/graphics signals to the individual separate storages for the respective named areas are logically connected independent of the sequence of receipt in the unformatted text/graphics signals and independent of the time of diversion for separate storage for the respective named areas.

12. The computer program product of claim 11 wherein the one or more reference abstract syntax trees are representative of one or more source code listings, the computer program product further comprising instructions for: determining whether the compiled software module was compiled from the one or more source code listings.

12. The computer program product of claim 11 wherein the one or more reference abstract syntax trees are representative of one or more source code listings, the computer program product further comprising instructions for: determining whether the compiled software module was compiled from the one or more source code listings. 14. The computer program product of claim 12 further comprising instructions for: generating the one or more reference abstract syntax trees by partially compiling the one or more source code listings.

1. A method of monitoring an acoustic environment of a mobile device for voice commands when the mobile device is operating in an idle mode, the mobile device having a first processor and a second processor, the method comprising: receiving acoustic input while the mobile device is operating in the idle mode; performing at least one first processing stage on the acoustic input using the first processor, prior to engaging the second processor to process the acoustic input, to evaluate whether the acoustic input includes a voice command; performing at least one second processing stage on the acoustic input using the second processor to evaluate whether the acoustic input includes a voice command if further processing is needed to determine whether the acoustic input includes a voice command; wherein performing the at least one first processing stage or the at least one second processing stage includes, while the mobile device is operating in the idle mode, transmitting at least a portion of the acoustic input to at least one server via a network for processing by the at least one server at least to evaluate whether the acoustic input includes a voice command; and initiating responding to the voice command when either the at least one first processing stage or the at least one second processing stage determines that the acoustic input includes a voice command.

1. A method of monitoring an acoustic environment of a mobile device for voice commands when the mobile device is operating in an idle mode, the mobile device having a first processor and a second processor, the method comprising: receiving acoustic input while the mobile device is operating in the idle mode; performing at least one first processing stage on the acoustic input using the first processor, prior to engaging the second processor to process the acoustic input, to evaluate whether the acoustic input includes a voice command; performing at least one second processing stage on the acoustic input using the second processor to evaluate whether the acoustic input includes a voice command if further processing is needed to determine whether the acoustic input includes a voice command; wherein performing the at least one first processing stage or the at least one second processing stage includes, while the mobile device is operating in the idle mode, transmitting at least a portion of the acoustic input to at least one server via a network for processing by the at least one server at least to evaluate whether the acoustic input includes a voice command; and initiating responding to the voice command when either the at least one first processing stage or the at least one second processing stage determines that the acoustic input includes a voice command. 11. The method of claim 1 , further comprising performing one or more default actions when a specific task could not be ascertained from the acoustic input.

1. A system, comprising: a detection component configured to make a prediction that text is within proximity of a capture component based on proximity measurements from a proximity sub-component of the detection component and duration measurements related to the proximity measurements, wherein the prediction is based on a proximity and a minimum duration related to the proximity, and wherein the detection component is further configured to modify at least one of the proximity and the minimum duration based on the proximity measurements and the duration measurements; a device operation component, configured to generate information to modify a mode of operation in response to receiving the prediction that text is within proximity of the capture component based on the capture component being within the proximity to information to be captured for at least the minimum duration; the capture component, configured to capture an image of the information to be captured in response to receiving the information to modify the mode of operation; an identification component, wherein the identification component is configured to identify text within the captured image; and an action component, wherein the action component is programmed to perform an action associated with the identified text.

1. A system, comprising: a detection component configured to make a prediction that text is within proximity of a capture component based on proximity measurements from a proximity sub-component of the detection component and duration measurements related to the proximity measurements, wherein the prediction is based on a proximity and a minimum duration related to the proximity, and wherein the detection component is further configured to modify at least one of the proximity and the minimum duration based on the proximity measurements and the duration measurements; a device operation component, configured to generate information to modify a mode of operation in response to receiving the prediction that text is within proximity of the capture component based on the capture component being within the proximity to information to be captured for at least the minimum duration; the capture component, configured to capture an image of the information to be captured in response to receiving the information to modify the mode of operation; an identification component, wherein the identification component is configured to identify text within the captured image; and an action component, wherein the action component is programmed to perform an action associated with the identified text. 4. The system of claim 1 , wherein the detection component is further configured to determine that the system is within the proximity to an object that contains the information to be captured.

5. A method for analyzing queries, the method comprising: receiving a query from a user; dissecting the query into a plurality of words; assigning an ontological threshold score to each of the plurality of words based on a predetermined ontology; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech.

5. A method for analyzing queries, the method comprising: receiving a query from a user; dissecting the query into a plurality of words; assigning an ontological threshold score to each of the plurality of words based on a predetermined ontology; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech. 6. The method of claim 5 , wherein the enabling further comprises displaying, in a vertical drop-down menu orthogonal to the horizontal axis, a predetermined list of words relating to each word having an assigned ontological threshold score that is at or above the predetermined threshold.

1. A computer-implemented method for utilizing invisible junction features for performing an action, the method comprising: receiving, with one or more processors, an input image; detecting, with the one or more processors, a location for each of the invisible junction features in a skeleton by applying a distance transformation to a binary image of the input image; determining, with the one or more processors, a region surrounding each of the invisible junction features based on the skeleton, the region including pixels from one or more characters of the input image and the location for each of the invisible junction features being a center of the region; recognizing, with the one or more processors, an electronic document corresponding to the input image using the location for each of the invisible junction features and the region surrounding each of the invisible junction features; and performing, with the one or more processors, the action related to the electronic document in response to recognizing the electronic document.

1. A computer-implemented method for utilizing invisible junction features for performing an action, the method comprising: receiving, with one or more processors, an input image; detecting, with the one or more processors, a location for each of the invisible junction features in a skeleton by applying a distance transformation to a binary image of the input image; determining, with the one or more processors, a region surrounding each of the invisible junction features based on the skeleton, the region including pixels from one or more characters of the input image and the location for each of the invisible junction features being a center of the region; recognizing, with the one or more processors, an electronic document corresponding to the input image using the location for each of the invisible junction features and the region surrounding each of the invisible junction features; and performing, with the one or more processors, the action related to the electronic document in response to recognizing the electronic document. 22. The method of claim 1 , wherein recognizing the electronic document corresponding to the input image using the invisible junction features comprises preprocessing invisible junction features prior to generation of a patch map.

7. A system, comprising: a data processing apparatus; and a computer storage medium encoded with a computer program, the program comprising instructions that when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a joint image-audio query sent to the data processing apparatus from a client device separate from the data processing apparatus, the joint image-audio query including query image data defining a query image and query audio data defining query audio, wherein: the query image data is an image file; the query audio data is an audio recording file of speech; and the query image data and the query audio data are paired as the join-image audio query at the client device and then sent to the data processing apparatus; determining query image feature data from the query image data included in the received joint image-audio query, the query image feature data describing image features of the query image; determining query audio feature data from the audio data included in the received joint image-audio query, the query audio feature data including text derived from the audio recording of speech; providing the query image feature data and the query audio feature data to a joint image-audio relevance model that i) receives, as input, image feature data and audio feature data, and ii) is trained to generate relevance scores for a plurality of resources based on a combined relevance of the query image feature data to image feature data of the resource and the text derived from the audio recording of speech to text of the resource; identifying resources responsive to the joint image-audio query based, in part, on a corresponding relevance score that was determined by the joint image audio relevance model, wherein each identified resource includes resource image data defining a resource image for the identified resource and text data defining resource text for the identified resource, and wherein each relevance score for each identified resource is a measure of the relevance of the corresponding resource image data and text data defining the resource text to the query image feature data and the text derived from the audio recording of speech; ordering the identified resources according to the corresponding relevance scores; and providing data defining search results indicating the order of the identified resources to the client device.

7. A system, comprising: a data processing apparatus; and a computer storage medium encoded with a computer program, the program comprising instructions that when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a joint image-audio query sent to the data processing apparatus from a client device separate from the data processing apparatus, the joint image-audio query including query image data defining a query image and query audio data defining query audio, wherein: the query image data is an image file; the query audio data is an audio recording file of speech; and the query image data and the query audio data are paired as the join-image audio query at the client device and then sent to the data processing apparatus; determining query image feature data from the query image data included in the received joint image-audio query, the query image feature data describing image features of the query image; determining query audio feature data from the audio data included in the received joint image-audio query, the query audio feature data including text derived from the audio recording of speech; providing the query image feature data and the query audio feature data to a joint image-audio relevance model that i) receives, as input, image feature data and audio feature data, and ii) is trained to generate relevance scores for a plurality of resources based on a combined relevance of the query image feature data to image feature data of the resource and the text derived from the audio recording of speech to text of the resource; identifying resources responsive to the joint image-audio query based, in part, on a corresponding relevance score that was determined by the joint image audio relevance model, wherein each identified resource includes resource image data defining a resource image for the identified resource and text data defining resource text for the identified resource, and wherein each relevance score for each identified resource is a measure of the relevance of the corresponding resource image data and text data defining the resource text to the query image feature data and the text derived from the audio recording of speech; ordering the identified resources according to the corresponding relevance scores; and providing data defining search results indicating the order of the identified resources to the client device. 8. The system of claim 7 wherein the query audio feature data includes data that relates to a query object in the query image data by further describing the query object, the query object being a subset of the query image that includes image data that depicts an object of interest.

9. A system comprising: a non-transitory computer readable medium having instructions stored thereon; and at least one processor configured to execute the instructions to perform operations comprising: sending each proposal of a plurality of proposals at a different time to a client device of a user, the proposal comprising a respective request for the user to translate a respective text message and a respective incentive for the translation; receiving from the client device a plurality of translations authored by the user, each translation being associated with one of the proposals and being a translation of the text message of the associated proposal; for each proposal, comparing a plurality of features associated with the text message with a respective plurality of features associated with the translation to generate respective feature scores, the features comprising word-based features, language-based features, word alignment features, and combinations thereof, and calculating an accuracy based on a weighted combination of the respective feature scores wherein the weights are derived using a statistical regression to model accuracy of translations; identifying a deviation from a norm in user translation accuracy over a period of time based on the calculated accuracies; updating a confidence score for the user based on the deviation in user translation accuracy; and revoking the translation privileges of the user when the confidence score does not satisfy a threshold value.

9. A system comprising: a non-transitory computer readable medium having instructions stored thereon; and at least one processor configured to execute the instructions to perform operations comprising: sending each proposal of a plurality of proposals at a different time to a client device of a user, the proposal comprising a respective request for the user to translate a respective text message and a respective incentive for the translation; receiving from the client device a plurality of translations authored by the user, each translation being associated with one of the proposals and being a translation of the text message of the associated proposal; for each proposal, comparing a plurality of features associated with the text message with a respective plurality of features associated with the translation to generate respective feature scores, the features comprising word-based features, language-based features, word alignment features, and combinations thereof, and calculating an accuracy based on a weighted combination of the respective feature scores wherein the weights are derived using a statistical regression to model accuracy of translations; identifying a deviation from a norm in user translation accuracy over a period of time based on the calculated accuracies; updating a confidence score for the user based on the deviation in user translation accuracy; and revoking the translation privileges of the user when the confidence score does not satisfy a threshold value. 12. The system of claim 9 , further comprising: for a first translation of the translations, rewarding the user with the incentive of the proposal associated with the first translation when the first translation is determined to be accurate.

1. A method comprising: determining that one or more entities in visual content, which is displayed on a display of a processing system, are selected in accordance with an explicit scoping command from a user, the explicit scoping command identifying the one or more entities in the visual content to explicitly indicate a scope of an interaction between the user and the processing system; turning on speech understanding functionality of the processing system, using at least one processor of the processing system, in response to determining that the one or more entities are selected, the speech understanding functionality enabling the processing system to understand natural language requests; and automatically monitoring audio signals received via an audio interface of the processing system for speech requests from the user to be processed using the speech understanding functionality in response to determining that the one or more entities are selected.

1. A method comprising: determining that one or more entities in visual content, which is displayed on a display of a processing system, are selected in accordance with an explicit scoping command from a user, the explicit scoping command identifying the one or more entities in the visual content to explicitly indicate a scope of an interaction between the user and the processing system; turning on speech understanding functionality of the processing system, using at least one processor of the processing system, in response to determining that the one or more entities are selected, the speech understanding functionality enabling the processing system to understand natural language requests; and automatically monitoring audio signals received via an audio interface of the processing system for speech requests from the user to be processed using the speech understanding functionality in response to determining that the one or more entities are selected. 8. The method of claim 1 , wherein determining that the one or more entities in the visual content are selected comprises: determining that the one or more entities are included in an image that is received via a camera of the processing system.

8. The visualization system of claim 1 , wherein the computer-executable components further comprise an artificial intelligence (AI) component configured to take action regarding presentation of at least one of the first visual representation, the second visual representation, the received data, or the captured context information, based on an inference.

8. The visualization system of claim 1 , wherein the computer-executable components further comprise an artificial intelligence (AI) component configured to take action regarding presentation of at least one of the first visual representation, the second visual representation, the received data, or the captured context information, based on an inference. 9. The system of claim 8 , wherein the AI component is configured to take the action as a function of an expected cost of taking the action compared to an expected benefit of taking the action.

10. A method comprising: in response to a determination that an event occurs at an application, determining, by a computing device having a processor and memory, that the application uses a first concept name from an application dictionary to describe the event; adding an entry for the event to a data log for the application, wherein the entry includes the first concept name from the application dictionary; and generating a mapping of the first concept name from the application dictionary to a second concept name from a domain dictionary, wherein the domain dictionary is different from the application dictionary, wherein generating the mapping comprises generating a mapping file that identifies the domain dictionary, the first concept name from the application dictionary, and a concept identifier for the event, and wherein the mapping file comprises a JavaScript Object Notation for Linked Data (JSON-LD) file.

10. A method comprising: in response to a determination that an event occurs at an application, determining, by a computing device having a processor and memory, that the application uses a first concept name from an application dictionary to describe the event; adding an entry for the event to a data log for the application, wherein the entry includes the first concept name from the application dictionary; and generating a mapping of the first concept name from the application dictionary to a second concept name from a domain dictionary, wherein the domain dictionary is different from the application dictionary, wherein generating the mapping comprises generating a mapping file that identifies the domain dictionary, the first concept name from the application dictionary, and a concept identifier for the event, and wherein the mapping file comprises a JavaScript Object Notation for Linked Data (JSON-LD) file. 11. The method of claim 10 , further comprising: sending the data log to a data log analysis system, wherein the data log analysis system is capable of accessing the domain dictionary.

18. The method of claim 15 , wherein the action comprises at least one sub-task and the input comprises a sub-input for the at least one sub-task.

18. The method of claim 15 , wherein the action comprises at least one sub-task and the input comprises a sub-input for the at least one sub-task. 19. The method of claim 18 , wherein the action is not complete until the at least one sub-task is completed.

15. A text to speech system comprising: one or more processors configured to identify a word or phrase as a named entity, the one or more processors further configured to identify a language of origin associated with the named entity and transliterate the named entity to a script associated with the language of origin, if the TTS system is operating in the language of origin, the one or more processors further configured to pass the transliterated script to the TTS system, and if the TTS system is not operating in the language of origin, the one or more processors further configured to generate a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter.

15. A text to speech system comprising: one or more processors configured to identify a word or phrase as a named entity, the one or more processors further configured to identify a language of origin associated with the named entity and transliterate the named entity to a script associated with the language of origin, if the TTS system is operating in the language of origin, the one or more processors further configured to pass the transliterated script to the TTS system, and if the TTS system is not operating in the language of origin, the one or more processors further configured to generate a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter. 16. The system of claim 15 , wherein if the TTS system is not operating in the language of origin, mapping the phoneme sequence to a sequence of target language phonemes.

11. A computer-readable medium having computer program logic recorded thereon, execution of which, by a computing device, causes the computing device to perform operations comprising: initiating a connection with a remote system upon detection, by a speech recognition operation of a local system, of a keyword in a speech input; storing a portion of the speech input into a local memory at the local system; transmitting the stored portion of the speech input from the local system to the remote system; and updating or modifying a set of recognizable keywords stored by the local system based on updates or modifications received from the remote system responsive to analysis of the stored portion of the speech input performed by a speech recognition operation of the remote system.

11. A computer-readable medium having computer program logic recorded thereon, execution of which, by a computing device, causes the computing device to perform operations comprising: initiating a connection with a remote system upon detection, by a speech recognition operation of a local system, of a keyword in a speech input; storing a portion of the speech input into a local memory at the local system; transmitting the stored portion of the speech input from the local system to the remote system; and updating or modifying a set of recognizable keywords stored by the local system based on updates or modifications received from the remote system responsive to analysis of the stored portion of the speech input performed by a speech recognition operation of the remote system. 14. The computer-readable medium of claim 11 , the operations further comprising: receiving generated speech from the remote system; and outputting the generated speech.

16. A computer program product for managing advisories for complex model nodes comprising a non-transitory computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to determine at least one related node for a node of a complex model, wherein a relationship to the at least one related node is captured in a notation model and a semantic model associated with the complex model, and, wherein the complex model is presented within a graphical modeling application, wherein the complex model includes the notation model and the semantic model, which are two distinct entities that are digitally encoded in a storage medium in a manner distinct from each other, wherein the notational model defines graphical characteristics of the complex model including graphical representations for nodes of the complex model including a shape of the nodes and edges connecting nodes to each other, wherein the semantic model stores capability and requirements parameters of nodes and stores semantic relationships between related nodes used by an advisory manager to determine if existing notifications of related nodes are to be aggregated to or not based on values of the capability and requirements parameters and based on content of the existing notifications; computer usable program code configured to create an aggregate of notifications for the node from notifications of the at least one determined related node based on the semantic model information, wherein the notifications indicate problems or potential problems with a current state of the complex model, and wherein said notifications are generated by the graphical modeling application, wherein the graphical modeling application uses the graphical characteristics of the notational model to present the complex model within a graphical user interface; and computer usable program code configured to present said aggregate of notifications for the node in a distinct viewing area within a graphical user interface of the graphical modeling application in response to a user-selected command.

16. A computer program product for managing advisories for complex model nodes comprising a non-transitory computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to determine at least one related node for a node of a complex model, wherein a relationship to the at least one related node is captured in a notation model and a semantic model associated with the complex model, and, wherein the complex model is presented within a graphical modeling application, wherein the complex model includes the notation model and the semantic model, which are two distinct entities that are digitally encoded in a storage medium in a manner distinct from each other, wherein the notational model defines graphical characteristics of the complex model including graphical representations for nodes of the complex model including a shape of the nodes and edges connecting nodes to each other, wherein the semantic model stores capability and requirements parameters of nodes and stores semantic relationships between related nodes used by an advisory manager to determine if existing notifications of related nodes are to be aggregated to or not based on values of the capability and requirements parameters and based on content of the existing notifications; computer usable program code configured to create an aggregate of notifications for the node from notifications of the at least one determined related node based on the semantic model information, wherein the notifications indicate problems or potential problems with a current state of the complex model, and wherein said notifications are generated by the graphical modeling application, wherein the graphical modeling application uses the graphical characteristics of the notational model to present the complex model within a graphical user interface; and computer usable program code configured to present said aggregate of notifications for the node in a distinct viewing area within a graphical user interface of the graphical modeling application in response to a user-selected command. 20. The computer program product of claim 16 , wherein the computer program product utilizes at least one of an ECLIPSE Modeling Framework (EMF) and a Graphical Editing Framework (GEF).

4. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: upon receiving a request from a user to view a markup document, access user information to determine portions of the markup document that were previously displayed to the user; based at least in part on the accessed user information, determine one or more portions of a modified version of the markup document that have not been displayed to the user; accessing user activity tracking information to determine portions of the markup document that were previously displayed to the user; based on the one or more portions of the modified version of the markup document that have not been displayed to the user and the user activity tracking information, determining portions of a current version of the markup document that have not previously been displayed to the user; providing the markup document for display to the user at a client system, content of the markup document being modified to include one or more intra-page bookmarks, such that the portions of the modified version of the markup document that have not previously been displayed to the user are distinguished from the portion that was previously displayed in a manner enabling the user to locate and view the portions that have not previously displayed to the user; enabling the user to manually insert one or more intra-page bookmarks in the markup document allowing the user to start at a desired location after closing the markup document; and enabling the user to selectively choose to display the intra-page bookmarks.

4. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: upon receiving a request from a user to view a markup document, access user information to determine portions of the markup document that were previously displayed to the user; based at least in part on the accessed user information, determine one or more portions of a modified version of the markup document that have not been displayed to the user; accessing user activity tracking information to determine portions of the markup document that were previously displayed to the user; based on the one or more portions of the modified version of the markup document that have not been displayed to the user and the user activity tracking information, determining portions of a current version of the markup document that have not previously been displayed to the user; providing the markup document for display to the user at a client system, content of the markup document being modified to include one or more intra-page bookmarks, such that the portions of the modified version of the markup document that have not previously been displayed to the user are distinguished from the portion that was previously displayed in a manner enabling the user to locate and view the portions that have not previously displayed to the user; enabling the user to manually insert one or more intra-page bookmarks in the markup document allowing the user to start at a desired location after closing the markup document; and enabling the user to selectively choose to display the intra-page bookmarks. 11. The non-transitory computer-readable storage medium of claim 4 , wherein determining the one or more portions of the modified version of the markup document that have not been displayed to the user includes determining a difference between a version of the markup document previously displayed to the user and the modified version of the markup document.

16. A system for predicting financial instrument performance, the system comprising: a computer for receiving data values corresponding to a financial instrument, the data values comprising a plurality of common features; the computer for extracting, using at least a first prediction model, more than one first common feature from the received plurality of common features and a corresponding dependence value for each of the extracted first common features, each of the extracted first common features being an influential feature; the computer for building a plurality of second prediction models, each of the second prediction models corresponding to each of the extracted influential features and each of the second prediction models using a first random selection of the received data values corresponding to each of the extracted influential features to generate predicted data values corresponding to the financial instrument for each extracted influential feature; and the computer for combining each of the second prediction models in a series arrangement, wherein the predicted data values corresponding to one second prediction model is input to another second prediction model until all the second prediction models are involved, thereby creating a combined prediction model, and wherein the combined prediction model uses the dependence value identified in the first prediction model as a weighing value for each predicted data value from each second prediction model, and the combined prediction model generates a combined predicted data value corresponding to the financial instrument.

16. A system for predicting financial instrument performance, the system comprising: a computer for receiving data values corresponding to a financial instrument, the data values comprising a plurality of common features; the computer for extracting, using at least a first prediction model, more than one first common feature from the received plurality of common features and a corresponding dependence value for each of the extracted first common features, each of the extracted first common features being an influential feature; the computer for building a plurality of second prediction models, each of the second prediction models corresponding to each of the extracted influential features and each of the second prediction models using a first random selection of the received data values corresponding to each of the extracted influential features to generate predicted data values corresponding to the financial instrument for each extracted influential feature; and the computer for combining each of the second prediction models in a series arrangement, wherein the predicted data values corresponding to one second prediction model is input to another second prediction model until all the second prediction models are involved, thereby creating a combined prediction model, and wherein the combined prediction model uses the dependence value identified in the first prediction model as a weighing value for each predicted data value from each second prediction model, and the combined prediction model generates a combined predicted data value corresponding to the financial instrument. 22. The system according to claim 16 , wherein the first random selection of received data values are historic price values of the financial instrument.

13. A system according to claim 7 in which said analysis means employs the viterbi algorithm to establish the probability that particular signals are the electrical analog of a particular word and in which the lexical information is in the form of a trie structure that contains a dictionary of acceptable words and which is accessed each time the viterbi algorithm establishes said probability.

13. A system according to claim 7 in which said analysis means employs the viterbi algorithm to establish the probability that particular signals are the electrical analog of a particular word and in which the lexical information is in the form of a trie structure that contains a dictionary of acceptable words and which is accessed each time the viterbi algorithm establishes said probability. 14. A system according to claim 13 in which said viterbi algorithm selects the shortest path through a directed graph having nodes and edges, said nodes being established by selecting letter a posteriori probabilities that correspond to said signals and which are above a predetermined threshold, said edges being established by selecting transitional probabilities which correspond to said nodes.

4. The method of claim 3 wherein highlighting specific words within a web page based on said topic model, further comprises: extracting content of said newly selected web page; determining a probability score for each of said plurality of topics in said topic model for how well said each of said plurality of topics describes said content; selecting a set of said plurality of topics that meet a predefined criteria analyzing said content utilizing said set of topics; determining a weight for each of a plurality of keywords associated with said set of topics, wherein different weights are determined for different keywords among said plurality of keywords depending how significant said each of said plurality of keywords are determined to be; and differentially highlighting said plurality of keywords associated with said set of topics within said content of said newly selected web page according to said weight.

4. The method of claim 3 wherein highlighting specific words within a web page based on said topic model, further comprises: extracting content of said newly selected web page; determining a probability score for each of said plurality of topics in said topic model for how well said each of said plurality of topics describes said content; selecting a set of said plurality of topics that meet a predefined criteria analyzing said content utilizing said set of topics; determining a weight for each of a plurality of keywords associated with said set of topics, wherein different weights are determined for different keywords among said plurality of keywords depending how significant said each of said plurality of keywords are determined to be; and differentially highlighting said plurality of keywords associated with said set of topics within said content of said newly selected web page according to said weight. 6. The method of claim 4 evaluating said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of topics, further comprises utilizing natural language processing to map different forms of said keywords and synonyms to specific stem-words within said topic model.

1. An anchor assembly comprising: an anchor body with an anchor; an anchor head including a U-shaped yoke having two arms; a first aperture in the first arm and a second aperture in the second arm; and a shaft spanning a gap between the two arms of the yoke; a saddle mounting element mounted about said shaft; a saddle having a transverse bore and a longitudinal bore which intersects the transverse bore; the saddle mounting element being received in the transverse bore of the saddle such that a portion of the saddle extends around the saddle mounting element between the saddle mounting element and the anchor head such that the saddle is secured to the anchor head and can move relative to the anchor head; said saddle having a slot adapted to hold a member; a set that is received in said saddle and can be selectively advanced into the slot; whereby, with a member received in the slot, advancing the set into the slot forces the member against the saddle mounting element thereby securing the member to the saddle and fixing the saddle relative to the anchor head.

1. An anchor assembly comprising: an anchor body with an anchor; an anchor head including a U-shaped yoke having two arms; a first aperture in the first arm and a second aperture in the second arm; and a shaft spanning a gap between the two arms of the yoke; a saddle mounting element mounted about said shaft; a saddle having a transverse bore and a longitudinal bore which intersects the transverse bore; the saddle mounting element being received in the transverse bore of the saddle such that a portion of the saddle extends around the saddle mounting element between the saddle mounting element and the anchor head such that the saddle is secured to the anchor head and can move relative to the anchor head; said saddle having a slot adapted to hold a member; a set that is received in said saddle and can be selectively advanced into the slot; whereby, with a member received in the slot, advancing the set into the slot forces the member against the saddle mounting element thereby securing the member to the saddle and fixing the saddle relative to the anchor head. 4. The anchor assembly of claim 1 wherein said saddle-mounting element has a textured surface to enhance fixing the saddle relative to the anchor head.

1. A reminder system comprising: a computer program that includes a connection with a messaging system; a central database for storing a plurality of reminders, each reminder including reminder information including information relating to said messaging system, said reminder information including status of one or more actions; wherein a plurality of different system users are connected with said messaging system; wherein one or more actions relating to certain of said reminders are assignable to one or more of said system users; and wherein said computer program updates said status in said database upon receipt of appropriate input from any system user assigned to an action.

1. A reminder system comprising: a computer program that includes a connection with a messaging system; a central database for storing a plurality of reminders, each reminder including reminder information including information relating to said messaging system, said reminder information including status of one or more actions; wherein a plurality of different system users are connected with said messaging system; wherein one or more actions relating to certain of said reminders are assignable to one or more of said system users; and wherein said computer program updates said status in said database upon receipt of appropriate input from any system user assigned to an action. 13. The system as claimed in claim 1 further including a report generator, wherein reminder information is sortable by a plurality of fields.

13. The computer system of claim 12 , wherein the one or more processors further configured to: determine whether any of the plurality of message templates stored in the message template database are associated with the primary first language of the first recipient; and when a first particular message template of the plurality of message templates is associated with the primary first language of the first recipient, obtain the retrieved first message template by retrieving the first particular message template from the message template database.

13. The computer system of claim 12 , wherein the one or more processors further configured to: determine whether any of the plurality of message templates stored in the message template database are associated with the primary first language of the first recipient; and when a first particular message template of the plurality of message templates is associated with the primary first language of the first recipient, obtain the retrieved first message template by retrieving the first particular message template from the message template database. 14. The computer system of claim 13 , wherein the one or more processors are further configured to, when (i) none of the plurality of message templates are associated with the primary first language of the first recipient and (ii) the one or more first languages understood by the first recipient include at least two first languages: determine a non-primary language of the first recipient by selecting another first language from the at least two first languages understood by the first recipient; determine whether any of the plurality of message templates stored in the message template database are associated with the non-primary language of the first recipient; and when a second particular message template of the plurality of message templates is associated with the non-primary language of the first recipient, obtain the retrieved first message template by retrieving the second particular message template from the message template database.

6. The method according to claim 1 , wherein said calculating the pair semantic similarity score value includes submitting a query to the at least one electronic information source and processing a query result from each electronic information source queried.

6. The method according to claim 1 , wherein said calculating the pair semantic similarity score value includes submitting a query to the at least one electronic information source and processing a query result from each electronic information source queried. 7. The method according to claim 6 , wherein the at least one electronic information source includes at least one of search engines and electronic encyclopedias.

1. A computer implemented method for optimizing database queries, the method comprising: receiving, by a database system, a database query for optimization, the database query comprising a first subquery and a second subquery, the first subquery specifying a first where clause comprising a first condition and the second subquery specifying a second where clause comprising a second condition, wherein the first where clause is distinct from the second where clause and wherein the first condition evaluates to true for a first set of input rows and the second condition evaluates to true for a second set of input rows; comparing the first subquery and the second subquery based on input tables processed by each of the first and second subqueries; responsive to determining that the first subquery and the second subquery match based on the comparison: generating a first database query specifying a where clause comprising a condition that evaluates to true for a superset of the first set of input rows and the second set of input rows; generating a statement comprising the first database query, the statement storing result of execution of the first database query in a result table; generating a first expression equivalent to the first subquery and a second expression equivalent to the second subquery, the first and the second expressions based on the result table; modifying the database query to use the result table, the modifying comprising, replacing the first subquery with the first expression and the second subquery with the second expression; and replacing an execution of the database query with an execution of the statement followed by an execution of the modified database query.

1. A computer implemented method for optimizing database queries, the method comprising: receiving, by a database system, a database query for optimization, the database query comprising a first subquery and a second subquery, the first subquery specifying a first where clause comprising a first condition and the second subquery specifying a second where clause comprising a second condition, wherein the first where clause is distinct from the second where clause and wherein the first condition evaluates to true for a first set of input rows and the second condition evaluates to true for a second set of input rows; comparing the first subquery and the second subquery based on input tables processed by each of the first and second subqueries; responsive to determining that the first subquery and the second subquery match based on the comparison: generating a first database query specifying a where clause comprising a condition that evaluates to true for a superset of the first set of input rows and the second set of input rows; generating a statement comprising the first database query, the statement storing result of execution of the first database query in a result table; generating a first expression equivalent to the first subquery and a second expression equivalent to the second subquery, the first and the second expressions based on the result table; modifying the database query to use the result table, the modifying comprising, replacing the first subquery with the first expression and the second subquery with the second expression; and replacing an execution of the database query with an execution of the statement followed by an execution of the modified database query. 6. The method of claim 1 , wherein the first subquery specifies an order by clause and the second subquery also specifies the order by clause, wherein generating the statement comprises generating a query having the order by clause.

8. A computer-implemented method comprising: transforming data into a uniform format that is compatible with a plurality of interfaces by transforming the data into a normalized and tagged format and into a searchable and mashed format; saving the transformed data to a file by saving the data, the transformed data in the normalized and tagged format, and the transformed data in the searchable and mashed format in the file; generating one or more grammatical phrases in an interface-specific format from the transformed data.

8. A computer-implemented method comprising: transforming data into a uniform format that is compatible with a plurality of interfaces by transforming the data into a normalized and tagged format and into a searchable and mashed format; saving the transformed data to a file by saving the data, the transformed data in the normalized and tagged format, and the transformed data in the searchable and mashed format in the file; generating one or more grammatical phrases in an interface-specific format from the transformed data. 13. The computer-implemented method of claim 8 , further comprising generating a voice command for input into a communication portal using the one or more grammatical phrases.

15. An apparatus comprising: a set of one or more processing units; and a deployment modeling language tool unit operable to, read a stereotype of a first profile, wherein the stereotype defines constraints to be applied to a model associated with the first profile; determine that the stereotype indicates a second profile and a third profile; access the second profile and the third profile; and aggregate a plurality of constraints from across the second profile and the third profile for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language.

15. An apparatus comprising: a set of one or more processing units; and a deployment modeling language tool unit operable to, read a stereotype of a first profile, wherein the stereotype defines constraints to be applied to a model associated with the first profile; determine that the stereotype indicates a second profile and a third profile; access the second profile and the third profile; and aggregate a plurality of constraints from across the second profile and the third profile for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language. 16. The apparatus of claim 15 , wherein the deployment modeling language tool unit being operable to aggregate comprises the deployment modeling language tool being operable to copy the plurality of constraints into a definition of the stereotype of the first profile.

11. A computer program product for use at a computer system, the computer program product for implementing a method for reconstructing control flow for higher level code from the contents of lower level code, the computer program product comprising one or more non-volatile computer storage devices having stored thereon computer-executable instructions that, when executed at a processor, cause the computer system to perform the method, including the following: access a plurality of instructions of lower level code that were translated from corresponding statements and expressions of first higher level code, the first higher level code in a first format, the plurality of instructions of lower level code representing a control flow of the first higher level code, a portion of the control flow defined by one or more branch instructions, the branch instructions selected from among conditional branch instructions and unconditional branch instructions; and translate the plurality of instructions of lower level code into a corresponding plurality of statements and expressions of second higher level code that have control flow equivalent to the control flow of the first higher level code, the second higher level code in a second different higher level format, the translation including the following: identify a plurality of basic blocks within the lower level code based on the arrangement of the one or more branch instructions within the plurality of instructions of lower level code, each basic block including one or more instructions of the lower level code configured to execute as a group; define a block guard variable for each basic block in the plurality of basic blocks; for each basic block in the plurality of basic blocks subsequent to defining the block guard variables: generate statements and expressions in the second higher level format to represent the functionality expressed in the basic block; generate statements and expressions in the second higher level format to represent assignment of values to a plurality of the block guard variables, the plurality of block guard variables including the block guard variable for the basic block and a block guard variable for at least one other basic block, assignments to the plurality of block guard variables for implementing the control flow of the first higher level code, including the portion of the control flow defined by the one or more branch instructions; generate statements and expressions in the second higher level format to represent a conditional statement, satisfying the conditional statement dependent on the value assigned to the block guard variable for the basic block; and nest the functionality expressed in the basic block and the assignment of values to the plurality of the block guard variables within the conditional statement; generate statements and expressions in the second higher level format representing a while statement, the condition on the while statement set to TRUE; and nest any conditional statements within the while statement.

11. A computer program product for use at a computer system, the computer program product for implementing a method for reconstructing control flow for higher level code from the contents of lower level code, the computer program product comprising one or more non-volatile computer storage devices having stored thereon computer-executable instructions that, when executed at a processor, cause the computer system to perform the method, including the following: access a plurality of instructions of lower level code that were translated from corresponding statements and expressions of first higher level code, the first higher level code in a first format, the plurality of instructions of lower level code representing a control flow of the first higher level code, a portion of the control flow defined by one or more branch instructions, the branch instructions selected from among conditional branch instructions and unconditional branch instructions; and translate the plurality of instructions of lower level code into a corresponding plurality of statements and expressions of second higher level code that have control flow equivalent to the control flow of the first higher level code, the second higher level code in a second different higher level format, the translation including the following: identify a plurality of basic blocks within the lower level code based on the arrangement of the one or more branch instructions within the plurality of instructions of lower level code, each basic block including one or more instructions of the lower level code configured to execute as a group; define a block guard variable for each basic block in the plurality of basic blocks; for each basic block in the plurality of basic blocks subsequent to defining the block guard variables: generate statements and expressions in the second higher level format to represent the functionality expressed in the basic block; generate statements and expressions in the second higher level format to represent assignment of values to a plurality of the block guard variables, the plurality of block guard variables including the block guard variable for the basic block and a block guard variable for at least one other basic block, assignments to the plurality of block guard variables for implementing the control flow of the first higher level code, including the portion of the control flow defined by the one or more branch instructions; generate statements and expressions in the second higher level format to represent a conditional statement, satisfying the conditional statement dependent on the value assigned to the block guard variable for the basic block; and nest the functionality expressed in the basic block and the assignment of values to the plurality of the block guard variables within the conditional statement; generate statements and expressions in the second higher level format representing a while statement, the condition on the while statement set to TRUE; and nest any conditional statements within the while statement. 18. The computer program product as recited in claim 11 , wherein computer-executable instructions that, when executed, cause the computer system to translate the plurality of instructions of lower level code into a corresponding plurality of statements and expressions of second higher level code further comprise computer-executable instructions that, when executed, cause the computer system to inline at least one basic block.

1. A method of customizing and executing an application software program that during execution communicates with an electronic database of product data, the method comprising: receiving an input for customizing an application software program indicating a user selection of one of a plurality of predefined database attributes that are each defined to be an identifier type of attribute that identifies to a user an identity of a defined product, wherein the product has a plurality of attributes to identify the product, and wherein the selected attribute is associated with a category of products for which data relating to products that are members of the product category are stored in the electronic database; customizing the application software, stored upon a computer readable storage medium, including activating the selected attribute for use during execution of a selected procedure of the application software program, wherein the attribute was previously inactive during the selected procedure of the application software program, and wherein the procedure is defined generically to use an attribute defined as an identifier type of attribute, and wherein the selected procedure includes a product-identifying function; and executing the selected procedure of the application software program, and in so doing, using the selected attribute where the procedure is generically defined to use an attribute defined as an identifier type of attribute, wherein executing the selected procedure of the application software program includes generating a display using information about the selected attribute.

1. A method of customizing and executing an application software program that during execution communicates with an electronic database of product data, the method comprising: receiving an input for customizing an application software program indicating a user selection of one of a plurality of predefined database attributes that are each defined to be an identifier type of attribute that identifies to a user an identity of a defined product, wherein the product has a plurality of attributes to identify the product, and wherein the selected attribute is associated with a category of products for which data relating to products that are members of the product category are stored in the electronic database; customizing the application software, stored upon a computer readable storage medium, including activating the selected attribute for use during execution of a selected procedure of the application software program, wherein the attribute was previously inactive during the selected procedure of the application software program, and wherein the procedure is defined generically to use an attribute defined as an identifier type of attribute, and wherein the selected procedure includes a product-identifying function; and executing the selected procedure of the application software program, and in so doing, using the selected attribute where the procedure is generically defined to use an attribute defined as an identifier type of attribute, wherein executing the selected procedure of the application software program includes generating a display using information about the selected attribute. 4. The method of claim 1 wherein the selected attribute is further defined as a main identifier type that is used in a product record header display procedure.

11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a goal based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve presentation information indicative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and that provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that her motivates accomplishment of the goal.

11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a goal based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve presentation information indicative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and that provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that her motivates accomplishment of the goal. 16. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component to provide a goal based educational environment as recited in claim 11, wherein the information includes video conference information.

1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed.

1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed. 2. The apparatus according to claim 1 , wherein said apparatus is caused to, in an initial state, before receiving any text entry, causing the precursor to be initialized by defining the precursor as a predefined word.

1. One or more non-transitory computer-readable media holding executable instructions that when executed on a processing device replaces functions in model code, the media holding one or more instructions for: identifying a pattern in model code, where: the model code is associated with a graphical model having executable semantics, the pattern is associated with a function in the model code, and the function performs operations when the model code is executed; selecting, for the identified pattern, a hardware specific function that performs an operation equivalent to an operation performed by the function in the model code; replacing the function in the model code with the selected hardware specific function, wherein conceptual arguments of the selected hardware specific function match argument properties of the function, and wherein argument properties of the selected hardware specific function do not exactly match function properties of the function; and storing the model code.

1. One or more non-transitory computer-readable media holding executable instructions that when executed on a processing device replaces functions in model code, the media holding one or more instructions for: identifying a pattern in model code, where: the model code is associated with a graphical model having executable semantics, the pattern is associated with a function in the model code, and the function performs operations when the model code is executed; selecting, for the identified pattern, a hardware specific function that performs an operation equivalent to an operation performed by the function in the model code; replacing the function in the model code with the selected hardware specific function, wherein conceptual arguments of the selected hardware specific function match argument properties of the function, and wherein argument properties of the selected hardware specific function do not exactly match function properties of the function; and storing the model code. 5. The media of claim 1 , wherein the pattern is identified in an intermediate representation of the model code.

9. The method of claim 5 , wherein: the configuring comprises receiving a first answer to a first question; the first received challenge request includes the first question; the retrieving comprises obtaining the first answer; and the first corresponding challenge response includes the first answer.

9. The method of claim 5 , wherein: the configuring comprises receiving a first answer to a first question; the first received challenge request includes the first question; the retrieving comprises obtaining the first answer; and the first corresponding challenge response includes the first answer. 13. The method of claim 9 , further comprising: deleting the first answer and the first question; and creating a different answer to a different question.

12. The computer readable storage medium of claim 10 , wherein the program instructions for assigning one of the available factories to process the annotation based on the annotation present in the file being supported by the one of the available factories includes, program instructions for matching the annotation present in the file with an annotation supported by one of the available factories.

12. The computer readable storage medium of claim 10 , wherein the program instructions for assigning one of the available factories to process the annotation based on the annotation present in the file being supported by the one of the available factories includes, program instructions for matching the annotation present in the file with an annotation supported by one of the available factories. 13. The computer readable storage medium of claim 12 , wherein the program instructions for matching the annotation present in the file with an annotation supported by one of the available factories includes, program instructions for comparing names representing the annotation present in the file with the annotation supported by one of the available factories.

21. Data encoding apparatus for encoding a digital data signal to be transmitted to permit correction of errors occurring in the signal during transmission, the data being formed as a plurality of sequences of words of a predetermined bit length m, each such series occurring in a respective input channel, so that the transmitted signal includes check words to enable said correction of errors, comprising input means to which said digital data signal is applied for providing a first block of words, one from each sequence of words, and having a first arrangement state; first encoder means coupled to said input means for generating a series of k first check words; interleaving means coupled to said input means and said first encoder means for delaying each of the words in said first block and each of said first check words by a respective different delay time to provide a resulting second block of words having a second arrangement state; second encoder means coupled to said interleaving means for generating a series of k second check words; and output means coupled to said second encoder means and said interleaving means for providing for transmission of the encoded digital data signal as a third block formed of said digital words, said first check words, and said second check words; wherein each of said first and second encoder means generates said first and second check words, respectively, to satisfy a parity check matrix having n columns and k rows, and in which each element of one predetermined row is selected from digital values from zero to 2.sup.m -1, so that the same value does not appear twice in said predetermined row, and wherein the elements in the remaining rows are selected to be a given power, for all the elements in each respective row, of the corresponding elements in said predetermined row, where m is the bit length of said data words and n is the number of words in each block formed of the words of the digital data signal together with the associated check words.

21. Data encoding apparatus for encoding a digital data signal to be transmitted to permit correction of errors occurring in the signal during transmission, the data being formed as a plurality of sequences of words of a predetermined bit length m, each such series occurring in a respective input channel, so that the transmitted signal includes check words to enable said correction of errors, comprising input means to which said digital data signal is applied for providing a first block of words, one from each sequence of words, and having a first arrangement state; first encoder means coupled to said input means for generating a series of k first check words; interleaving means coupled to said input means and said first encoder means for delaying each of the words in said first block and each of said first check words by a respective different delay time to provide a resulting second block of words having a second arrangement state; second encoder means coupled to said interleaving means for generating a series of k second check words; and output means coupled to said second encoder means and said interleaving means for providing for transmission of the encoded digital data signal as a third block formed of said digital words, said first check words, and said second check words; wherein each of said first and second encoder means generates said first and second check words, respectively, to satisfy a parity check matrix having n columns and k rows, and in which each element of one predetermined row is selected from digital values from zero to 2.sup.m -1, so that the same value does not appear twice in said predetermined row, and wherein the elements in the remaining rows are selected to be a given power, for all the elements in each respective row, of the corresponding elements in said predetermined row, where m is the bit length of said data words and n is the number of words in each block formed of the words of the digital data signal together with the associated check words. 23. Data encoding apparatus according to claim 21, wherein said input means includes interleaving means for changing the arrangement state of said digital words prior to application to said first encoder means and the first-mentioned interleaving means.

1. A method, with a decoder, for decompressing results of a join query, the method comprising: receiving, from a result set encoder, a result set from the join query; receiving a plurality of encoded tuples associated with the result set, wherein each encoded tuple of the plurality of encoded tuples is received with a set of dictionary entry information, the set of dictionary entry information comprising a value from a dictionary entry generated by the result set encoder and a location within a set of nested hierarchy of dictionaries to store the value and wherein each value at each position in said each encoded tuple of the plurality of encoded tuples identifying a location of an entry within the set of nested hierarchy of dictionaries; determining a join order of the result set from the join query; creating the set of nested hierarchy of dictionaries based on the join order and the set of dictionary entry information, wherein a nesting order of the dictionaries in the set of nested hierarchy of dictionaries corresponds to the join order of the result set, and wherein the creating comprising storing the value comprised within the set of dictionary entry information at the location within a dictionary of the set of corresponding nested hierarchy of dictionaries as identified by the dictionary entry information; using, by a processor, the set of nested hierarchy of dictionaries and values from the set of dictionary entry information stored within the set of nested hierarchy of dictionaries to decode the plurality of encoded tuples so as to produce a plurality of decoded tuples of the result set, wherein each position in said each encoded tuple of the plurality of encoded tuples is associated with a table identifier within the set of nested hierarchy of dictionaries, each identifier of the table identifiers being associated with a different table used to create the result set; and decompressing the result set of the join query with the decoder.

1. A method, with a decoder, for decompressing results of a join query, the method comprising: receiving, from a result set encoder, a result set from the join query; receiving a plurality of encoded tuples associated with the result set, wherein each encoded tuple of the plurality of encoded tuples is received with a set of dictionary entry information, the set of dictionary entry information comprising a value from a dictionary entry generated by the result set encoder and a location within a set of nested hierarchy of dictionaries to store the value and wherein each value at each position in said each encoded tuple of the plurality of encoded tuples identifying a location of an entry within the set of nested hierarchy of dictionaries; determining a join order of the result set from the join query; creating the set of nested hierarchy of dictionaries based on the join order and the set of dictionary entry information, wherein a nesting order of the dictionaries in the set of nested hierarchy of dictionaries corresponds to the join order of the result set, and wherein the creating comprising storing the value comprised within the set of dictionary entry information at the location within a dictionary of the set of corresponding nested hierarchy of dictionaries as identified by the dictionary entry information; using, by a processor, the set of nested hierarchy of dictionaries and values from the set of dictionary entry information stored within the set of nested hierarchy of dictionaries to decode the plurality of encoded tuples so as to produce a plurality of decoded tuples of the result set, wherein each position in said each encoded tuple of the plurality of encoded tuples is associated with a table identifier within the set of nested hierarchy of dictionaries, each identifier of the table identifiers being associated with a different table used to create the result set; and decompressing the result set of the join query with the decoder. 4. The method of claim 1 , wherein the set of nested hierarchy of dictionaries comprises a set of leaf level dictionaries and a set of intermediate level dictionaries, the set of leaf level dictionaries mapping data tuple fragments to a first set of code, and the set of intermediate level dictionaries mapping a tuple created from the first set of code to a second set of code that is smaller than the first set of code.

3. The character input apparatus according to claim 2 , further comprising a voice control unit configured to be operable when the setting unit sets to perform the completion of the input character string, to read aloud the character string input by the user and the character string added by the completing unit in a manner distinguishable therebetween.

3. The character input apparatus according to claim 2 , further comprising a voice control unit configured to be operable when the setting unit sets to perform the completion of the input character string, to read aloud the character string input by the user and the character string added by the completing unit in a manner distinguishable therebetween. 4. The character input apparatus according to claim 3 , wherein when the setting unit sets to perform the completion of the input character string, said voice control unit reads aloud the character string input by the user and the character string added by the completing unit, by respective voices different in one of sound timbre, tone, and volume.

1. A smart knowledge discovery and augmentation system, comprising: an electronic device having a display screen operable to display a portion of a reference document using a first display layer and augmented content using a second display layer, the electronic device operable (i) to allow user interaction with the portion of the reference document for selection of a reference topic to be augmented, and (ii) to communicate with a remote server, wherein the reference document includes digital data information stored locally on the electronic device or via the remote server; and a ranking engine configured to prune out a portion of a set of features extracted from the reference document, wherein the augmented content is generated using a set of discovery patterns and a causality graph, wherein the set of discovery patterns is dynamically generated based on context aware competency questions relevant to content of the reference document, and wherein the causality graph is generated using (i) a set of prior topics that are relevant to content of the reference document, (ii) the reference topic to be augmented, (iii) a set of at least two causal relationships, (iv) a set of actors relevant to the set of at least two causal relationships, (v) a set of topics and a set of categories associated with the set of topics, and (vi) the set of discovery patterns.

1. A smart knowledge discovery and augmentation system, comprising: an electronic device having a display screen operable to display a portion of a reference document using a first display layer and augmented content using a second display layer, the electronic device operable (i) to allow user interaction with the portion of the reference document for selection of a reference topic to be augmented, and (ii) to communicate with a remote server, wherein the reference document includes digital data information stored locally on the electronic device or via the remote server; and a ranking engine configured to prune out a portion of a set of features extracted from the reference document, wherein the augmented content is generated using a set of discovery patterns and a causality graph, wherein the set of discovery patterns is dynamically generated based on context aware competency questions relevant to content of the reference document, and wherein the causality graph is generated using (i) a set of prior topics that are relevant to content of the reference document, (ii) the reference topic to be augmented, (iii) a set of at least two causal relationships, (iv) a set of actors relevant to the set of at least two causal relationships, (v) a set of topics and a set of categories associated with the set of topics, and (vi) the set of discovery patterns. 6. The smart knowledge discovery and augmentation system of claim 1 , wherein the user interaction with the portion of the reference document includes at least one of a manipulation of a region of the first display layer, and a manipulation of a region of the second display layer.

20. A computer system for synthesizing relevant messaging from one or more domains of information, underpinned by non-promoted content, using a consumer-generated context over a computer network linked to a plurality of computing devices, the system comprising: a) a first set of computing devices, and a second set of computing devices for obtaining non-promoted content associated with the first set of computing devices, wherein the non-promoted content is linked to at least one promoter, and wherein the second set of computing devices is further configured to receive advertising material from the at least one promoter; b) a third set of computing devices for obtaining, receiving or generating the consumer-generated context and providing the consumer-generated context to the second set of computing devices; and c) a semantic analyzing means and a semantic synthesizing means linked to the second set of computing devices for synthesizing relevant messaging based on the non-promoted content and the consumer-generated context, wherein the relevant messaging is traceable to the at least one promoter, the synthesizing comprising: deconstructing the advertising material received from the at least one promoter into a plurality of messaging leads; and selecting at least some of the plurality of messaging leads and assembling the selected messaging leads into a message based on the consumer-generated context, the message having relevant non-promoted content interspersed between the selected messaging leads from the received advertising material.

20. A computer system for synthesizing relevant messaging from one or more domains of information, underpinned by non-promoted content, using a consumer-generated context over a computer network linked to a plurality of computing devices, the system comprising: a) a first set of computing devices, and a second set of computing devices for obtaining non-promoted content associated with the first set of computing devices, wherein the non-promoted content is linked to at least one promoter, and wherein the second set of computing devices is further configured to receive advertising material from the at least one promoter; b) a third set of computing devices for obtaining, receiving or generating the consumer-generated context and providing the consumer-generated context to the second set of computing devices; and c) a semantic analyzing means and a semantic synthesizing means linked to the second set of computing devices for synthesizing relevant messaging based on the non-promoted content and the consumer-generated context, wherein the relevant messaging is traceable to the at least one promoter, the synthesizing comprising: deconstructing the advertising material received from the at least one promoter into a plurality of messaging leads; and selecting at least some of the plurality of messaging leads and assembling the selected messaging leads into a message based on the consumer-generated context, the message having relevant non-promoted content interspersed between the selected messaging leads from the received advertising material. 27. The system of claim 20 , wherein the relevant messaging matches the non-promoted content to a consumer based on the consumer-generated context.

4. The method of claim 3, wherein the generating accessibility graph step comprises: generating at least one of at least one first accessibility node corresponding to all pairs of ones of the input nodes of the separated portion and ones of the groups of matching patterns, and at least one second accessibility node corresponding to all pairs of ones of the output nodes of the separated portion and one of the groups of matching patterns; generating at least one of at least one third accessibility node corresponding to all input nodes of the separated portion and at least one fourth accessibility node corresponding to all output nodes of the separated portion; and connecting the first and third accessibility nodes to the second and the fourth accessibility nodes with at least one directed graph edge based on results of the matching step.

4. The method of claim 3, wherein the generating accessibility graph step comprises: generating at least one of at least one first accessibility node corresponding to all pairs of ones of the input nodes of the separated portion and ones of the groups of matching patterns, and at least one second accessibility node corresponding to all pairs of ones of the output nodes of the separated portion and one of the groups of matching patterns; generating at least one of at least one third accessibility node corresponding to all input nodes of the separated portion and at least one fourth accessibility node corresponding to all output nodes of the separated portion; and connecting the first and third accessibility nodes to the second and the fourth accessibility nodes with at least one directed graph edge based on results of the matching step. 5. The method of claim 4, wherein the combining step comprises connecting first, second, third, and fourth accessibility nodes of each of the accessibility graphs to first, second, third and fourth accessibility nodes of accessibility graphs of other separated portions based on the cross links of corresponding input nodes and corresponding output nodes to form the single graph.

1. A method of delivering a search result comprising: receiving a query; identifying a first term in the query that is a first portion of a first abbreviation pair, wherein the first abbreviation pair includes a second portion; identifying a second term in the query; identifying a topic corresponding to the second term; identifying that the first term in the query is also present in a second abbreviation pair as a third portion of the second abbreviation pair, wherein the second abbreviation pair includes a fourth portion and wherein the fourth portion of the second abbreviation pair is different from the second portion of the first abbreviation pair; revising the query by selectively including as additional parameters in the query, one of: (1) the second portion, (2) the fourth portion, or (3) both the second and fourth portions, wherein the fourth portion comprises a plurality of terms representing an acronym expansion of the third portion and wherein the selection is based at least in part on a topical score associated with each of the second portion and the fourth portion, respectively, the topical scores corresponding to relevance of the second and fourth portions to the topic and calculated according to both of relevance of a plurality of constituent terms of the second portion and the plurality of terms of the fourth portion to the topic and relevance of the combined constituent terms of the second portion and the plurality of terms of the fourth portion to the topic, respectively; locating one or more search results for the revised query; and returning the one or more search results.

1. A method of delivering a search result comprising: receiving a query; identifying a first term in the query that is a first portion of a first abbreviation pair, wherein the first abbreviation pair includes a second portion; identifying a second term in the query; identifying a topic corresponding to the second term; identifying that the first term in the query is also present in a second abbreviation pair as a third portion of the second abbreviation pair, wherein the second abbreviation pair includes a fourth portion and wherein the fourth portion of the second abbreviation pair is different from the second portion of the first abbreviation pair; revising the query by selectively including as additional parameters in the query, one of: (1) the second portion, (2) the fourth portion, or (3) both the second and fourth portions, wherein the fourth portion comprises a plurality of terms representing an acronym expansion of the third portion and wherein the selection is based at least in part on a topical score associated with each of the second portion and the fourth portion, respectively, the topical scores corresponding to relevance of the second and fourth portions to the topic and calculated according to both of relevance of a plurality of constituent terms of the second portion and the plurality of terms of the fourth portion to the topic and relevance of the combined constituent terms of the second portion and the plurality of terms of the fourth portion to the topic, respectively; locating one or more search results for the revised query; and returning the one or more search results. 9. The method of claim 1 further comprising receiving an indication from a user that the second portion should be included in the received query.

18. The system of claim 16 , wherein the expert is provided with the document from said training management unit and the expert provides information concerning the characteristics of the document type and goals of content understanding.

18. The system of claim 16 , wherein the expert is provided with the document from said training management unit and the expert provides information concerning the characteristics of the document type and goals of content understanding. 19. The system of claim 18 , further comprising a knowledge generator for receiving information concerning the characteristics of the document type and goals of content understanding and organizing the information so provided into rules and formatted knowledge.

6. A computer-implemented method for calculating a value score for a domain name, the method comprising: at a computer, receiving a domain name to be scored; measuring, by a processor of the computer, a plurality of domain name registration criteria for the received domain name; for each of the plurality of domain name registration criteria, assigning a sub-score to the domain name; calculating a combined domain name score based on the sub-scores; identifying a technique for increasing the combined domain name score; and providing the domain name and the identified technique to the user.

6. A computer-implemented method for calculating a value score for a domain name, the method comprising: at a computer, receiving a domain name to be scored; measuring, by a processor of the computer, a plurality of domain name registration criteria for the received domain name; for each of the plurality of domain name registration criteria, assigning a sub-score to the domain name; calculating a combined domain name score based on the sub-scores; identifying a technique for increasing the combined domain name score; and providing the domain name and the identified technique to the user. 7. The method of claim 6 , wherein the domain name registration criteria include the number of equivalent top-level domain names corresponding to the received domain name that are registered in the domain name system.

1. A computer-readable, non-transitory medium storing the system analysis program, said system analysis program makes the computer execute processing comprising: collecting a message transmitted or received through said network; analyzing contents of said collected message; determining a process type requested by said message and whether or not the message is a request message or a response message; storing the message in a protocol-log storage unit as a protocol log information which indicates the determined process type; identifying at least one process corresponding to the determined process type based on a correspondence relationship between a request message and a response message corresponding to the process type which is indicated in said protocol log when receiving an instruction for generating a model; generating a transaction model which satisfies a limiting condition related to caller-called relationships between processes, from a set of messages selected in accordance with a selection criterion based on certainty of existence of caller-called relationships, the transaction model containing a list of messages to be transmitted until a completion of a transaction; storing the generated transaction model in a transaction model storage unit; extracting from said protocol-log storage unit a record item of said protocol log conforming to a caller-called relationship indicated by said transaction model stored in said transaction-model storage unit when receiving an instruction for analyzing; and analyzing a processing status of a transaction constituted by a message indicated by the extracted record item, wherein when there are a plurality of processes which are possible to call a process to be called, the generating uniformly determines a probability of a call from each of the plurality of processes, integrates probabilities of calls from the plurality of processes to other processes into probabilities on a process type basis, and calculates the likelihoods of caller-called relationships.

1. A computer-readable, non-transitory medium storing the system analysis program, said system analysis program makes the computer execute processing comprising: collecting a message transmitted or received through said network; analyzing contents of said collected message; determining a process type requested by said message and whether or not the message is a request message or a response message; storing the message in a protocol-log storage unit as a protocol log information which indicates the determined process type; identifying at least one process corresponding to the determined process type based on a correspondence relationship between a request message and a response message corresponding to the process type which is indicated in said protocol log when receiving an instruction for generating a model; generating a transaction model which satisfies a limiting condition related to caller-called relationships between processes, from a set of messages selected in accordance with a selection criterion based on certainty of existence of caller-called relationships, the transaction model containing a list of messages to be transmitted until a completion of a transaction; storing the generated transaction model in a transaction model storage unit; extracting from said protocol-log storage unit a record item of said protocol log conforming to a caller-called relationship indicated by said transaction model stored in said transaction-model storage unit when receiving an instruction for analyzing; and analyzing a processing status of a transaction constituted by a message indicated by the extracted record item, wherein when there are a plurality of processes which are possible to call a process to be called, the generating uniformly determines a probability of a call from each of the plurality of processes, integrates probabilities of calls from the plurality of processes to other processes into probabilities on a process type basis, and calculates the likelihoods of caller-called relationships. 5. The computer-readable, non-transitory medium storing the system analysis program according to claim 1 , wherein directions of calls between the plurality of servers are defined in the limiting condition.

6. The method of claim 1 , wherein said performing said requested social bookmarking operation comprises sending resource information contained in said element in said document object model (DOM) of said currently loaded Web page that identifies said corresponding one of said socially bookmarkable resources visually indicated by said one of said resource selection user interface display objects clicked on by the user to said external social bookmarking system.

6. The method of claim 1 , wherein said performing said requested social bookmarking operation comprises sending resource information contained in said element in said document object model (DOM) of said currently loaded Web page that identifies said corresponding one of said socially bookmarkable resources visually indicated by said one of said resource selection user interface display objects clicked on by the user to said external social bookmarking system. 7. The method of claim 6 , wherein said performing said requested social bookmarking operation further comprises tagging, in said external social bookmarking system, said corresponding one of said socially bookmarkable resources indicated by said one of said resource selection user interface objects clicked on by the user with at least one suggested tag contained in said element identifying said corresponding one of said socially bookmarkable resources indicated by said resource selection user interface object clicked on by the user; and wherein said information contained in said element identifying said corresponding one of said socially bookmarkable resources indicated by said resource selection user interface object clicked on by the user and sent to said external social bookmarking system includes said at least one suggested tag.

11. The method according to claim 1 further comprising the steps of: receiving data from which information is to be extracted; finding, from the data, a character string part acceptable by the second parser associated with the second grammar description (P 2 ), by use of the second parser; parsing a character string part of the data by use of the first parser associated with the first grammar description (P 1 ); parsing the found character string part by use of the second parser; creating a syntax tree on the basis of a first analysis result obtained by the parsing done by the first parser and a second analysis result obtained by the parsing performed by the second parser; and wherein all the steps of the method are carried out using the computer device.

11. The method according to claim 1 further comprising the steps of: receiving data from which information is to be extracted; finding, from the data, a character string part acceptable by the second parser associated with the second grammar description (P 2 ), by use of the second parser; parsing a character string part of the data by use of the first parser associated with the first grammar description (P 1 ); parsing the found character string part by use of the second parser; creating a syntax tree on the basis of a first analysis result obtained by the parsing done by the first parser and a second analysis result obtained by the parsing performed by the second parser; and wherein all the steps of the method are carried out using the computer device. 22. A non-transitory computer readable storage medium tangibly embodying a computer readable program code having computer readable instructions which, when implemented, cause a computer to carry out the steps of the method according to claim 11 .

12. The system of claim 9 , wherein the system is configured to generate the prediction model by: generating a plurality of training phrases from a collection of recorded audio; calculating a target value for each of the training phrases; calculating a plurality of features of each of the training phrases; training the prediction model based on the features; and setting a filtering threshold.

12. The system of claim 9 , wherein the system is configured to generate the prediction model by: generating a plurality of training phrases from a collection of recorded audio; calculating a target value for each of the training phrases; calculating a plurality of features of each of the training phrases; training the prediction model based on the features; and setting a filtering threshold. 13. The system of claim 12 , wherein the system is configured to generate the plurality of training phrases by: segmenting a plurality of true transcriptions into a plurality of true phrases; processing the collection of recorded audio using an automatic speech recognition system to generate a recognizer output; comparing the recognizer output to the true phrases to identify matches between the recognizer output and the true phrases; based on the comparison, tagging the true phrases that match the recognizer output as hits; determining tagged phrases with a number of hits greater than a threshold value as training phrases; and returning the plurality of training phrases.

30. An apparatus according to claim 29, wherein said apparatus further includes instruction means for instructing whether character data or coordinate data is to be output from said recognition control means.

30. An apparatus according to claim 29, wherein said apparatus further includes instruction means for instructing whether character data or coordinate data is to be output from said recognition control means. 31. An apparatus according to claim 30, wherein said recognition control means outputs, to a document data processing apparatus which is externally connected to said handheld data input apparatus via said interface means, coordinate data when said instruction means instructs output of the coordinate data, and character data when said instruction means instructs output of the character data.

1. A method comprising: receiving a plurality of data objects at a user device, said plurality of data objects including program guide data; parsing search data from the plurality of data objects at the user device to form a search index different than the program guide data, said search index comprising search string objects, token objects and word objects, said word objects each having a first word and a second word associated therewith, said search string objects each having at least one token identifier associated therewith; storing the search index within the user device separate from the program guide data; in response to a search query, searching the search index stored within the user device by identifying the word object from the search query alphabetically until a second space is entered in a user interface, and, after the second space is entered performing: identifying token objects from the word object, identifying a string object from the token object, and obtaining a token list having token objects and thereafter storing the token list to one of the token objects; generating search results from the search index; and displaying search results.

1. A method comprising: receiving a plurality of data objects at a user device, said plurality of data objects including program guide data; parsing search data from the plurality of data objects at the user device to form a search index different than the program guide data, said search index comprising search string objects, token objects and word objects, said word objects each having a first word and a second word associated therewith, said search string objects each having at least one token identifier associated therewith; storing the search index within the user device separate from the program guide data; in response to a search query, searching the search index stored within the user device by identifying the word object from the search query alphabetically until a second space is entered in a user interface, and, after the second space is entered performing: identifying token objects from the word object, identifying a string object from the token object, and obtaining a token list having token objects and thereafter storing the token list to one of the token objects; generating search results from the search index; and displaying search results. 2. A method as recited in claim 1 wherein receiving a plurality of data objects comprises receiving a plurality of program guide objects.

9. A system for copying annotated documents from one location to another location in an electronic medium or between electronic media, the system comprising: a display unit for displaying a document to a user, the document including objects, the objects including text objects and graphic objects; an input unit for receiving, from the user, at least one annotation on the document, the annotation being a visible object created by user interaction; a grouping unit for automatically grouping at least some of the at least one annotation with the an object of the document to obtain a grouped annotation, the object of the document being an underlying object of the annotation; wherein the input unit is further operable for receiving from the user a selection of either the at least one annotation, or the underlying object of the annotation, or the grouped annotation; a modifying unit for modifying the underlying object responsive to a type of the at least one annotation to obtain a modified selection; and a copying unit for copying the modified selection to at least one of a different part of the electronic media and another media, wherein the modifying unit is further operable for replacing portions of the underlying object in the grouped annotation with ellipses.

9. A system for copying annotated documents from one location to another location in an electronic medium or between electronic media, the system comprising: a display unit for displaying a document to a user, the document including objects, the objects including text objects and graphic objects; an input unit for receiving, from the user, at least one annotation on the document, the annotation being a visible object created by user interaction; a grouping unit for automatically grouping at least some of the at least one annotation with the an object of the document to obtain a grouped annotation, the object of the document being an underlying object of the annotation; wherein the input unit is further operable for receiving from the user a selection of either the at least one annotation, or the underlying object of the annotation, or the grouped annotation; a modifying unit for modifying the underlying object responsive to a type of the at least one annotation to obtain a modified selection; and a copying unit for copying the modified selection to at least one of a different part of the electronic media and another media, wherein the modifying unit is further operable for replacing portions of the underlying object in the grouped annotation with ellipses. 14. The system of claim 9 further comprising: a determining unit for determining reference information in the underlying object; a retrieving unit for retrieving a reference cited in the reference information; and an associating unit for associating the reference information with the underlying object.

4. The method as claimed in claim 3 , wherein the providing a target framework model automatically generates a target framework model based on a logical metadata model of the data warehouse.

4. The method as claimed in claim 3 , wherein the providing a target framework model automatically generates a target framework model based on a logical metadata model of the data warehouse. 5. The method as claimed in claim 4 , wherein the providing a target framework model automatically generates the target framework model using applicable business rules including general rules, database layer rules, business view rules, dimensional view rules, and metadata rules.

16. The method of claim 1 , further comprising: displaying the estimated similarity value through a user interface.

16. The method of claim 1 , further comprising: displaying the estimated similarity value through a user interface. 17. The method of claim 16 , wherein said displaying the similarity value includes: determining that the similarity value exceeds a similarity threshold value.

1. A computer-implemented method, comprising: receiving first input audio data corresponding to an utterance; performing automatic speech recognition processing on the first input audio data to create first reference text data; in a database associated with a first user profile, storing a first association between the first input audio data and the first reference text data; receiving, from a first device associated with the first user profile, a message intended for a second device, the message including first text data; determining the first text data corresponds to the first reference text data; identifying the first input audio data in the database based at least in part on the first association; causing the first device to output a visual indication representing that the first text data corresponds to the first reference text data; generating, after causing the first device to output the visual indication, output audio data including the first input audio data; and sending, to the second device, the output audio data.

1. A computer-implemented method, comprising: receiving first input audio data corresponding to an utterance; performing automatic speech recognition processing on the first input audio data to create first reference text data; in a database associated with a first user profile, storing a first association between the first input audio data and the first reference text data; receiving, from a first device associated with the first user profile, a message intended for a second device, the message including first text data; determining the first text data corresponds to the first reference text data; identifying the first input audio data in the database based at least in part on the first association; causing the first device to output a visual indication representing that the first text data corresponds to the first reference text data; generating, after causing the first device to output the visual indication, output audio data including the first input audio data; and sending, to the second device, the output audio data. 2. The computer-implemented method of claim 1 , further comprising: receiving second input audio data corresponding to a second utterance; performing automatic speech recognition processing on the second input audio data to create second reference text data; in the database, storing a second association between the second input audio data and the second reference text data; determining a pronunciation of the first text data; determining a first diphone identifier associated with the first reference text data; determining a second diphone identifier associated with the second reference text data; and determining the first diphone identifier and the second diphone identifier correspond to the pronunciation, wherein generating the output audio data comprises concatenating the first input audio data to the second input audio data.

11. A system, comprising: at least one processor; and a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the following operations: extracting an audio track from an electronic media content; detecting, based on a speech model, a speaker segment within the extracted audio track; determining, by the processor, a first probability of the detected speaker segment being associated with an individual speaker by using both a speaker speech model and a non-speaker speech model, wherein the speaker speech model represents an individual speaker and the non-speaker speech model represents common characteristics from one or more speakers; determining a first ranking value of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment and probabilities for detected speaker segments within the other electronic media content; receiving a search query from a user; determining a second ranking value of the electronic media content based on relevancy between the query and the individual speaker; and determining a final ranking value of the electronic media content based on the first ranking value and the second ranking value.

11. A system, comprising: at least one processor; and a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the following operations: extracting an audio track from an electronic media content; detecting, based on a speech model, a speaker segment within the extracted audio track; determining, by the processor, a first probability of the detected speaker segment being associated with an individual speaker by using both a speaker speech model and a non-speaker speech model, wherein the speaker speech model represents an individual speaker and the non-speaker speech model represents common characteristics from one or more speakers; determining a first ranking value of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment and probabilities for detected speaker segments within the other electronic media content; receiving a search query from a user; determining a second ranking value of the electronic media content based on relevancy between the query and the individual speaker; and determining a final ranking value of the electronic media content based on the first ranking value and the second ranking value. 18. The system of claim 11 , further comprising: detecting, based on the speaker segments, duplicate videos among the electronic media content.

1. A computer implemented method of program compilation to improve parallelism during the linking of the program by a compiler, the method comprising: converting statements of the program to canonical form; constructing a traversable representation for each procedure in the program; and traversing the program to construct a functional dataflow graph, in which an assignment statement or function call is represented as a node, a control flow decision is represented by a first set of nodes, an array or set is represented as a second set of nodes, and edges of the functional dataflow graph represent typed data; identifying at least one loop in the functional dataflow graph that can be executed in parallel; and transforming the at least one loop to a set operation by retyping connections between nodes of the functional dataflow graph.

1. A computer implemented method of program compilation to improve parallelism during the linking of the program by a compiler, the method comprising: converting statements of the program to canonical form; constructing a traversable representation for each procedure in the program; and traversing the program to construct a functional dataflow graph, in which an assignment statement or function call is represented as a node, a control flow decision is represented by a first set of nodes, an array or set is represented as a second set of nodes, and edges of the functional dataflow graph represent typed data; identifying at least one loop in the functional dataflow graph that can be executed in parallel; and transforming the at least one loop to a set operation by retyping connections between nodes of the functional dataflow graph. 5. The method of claim 1 , further comprising: creating a table of initial values for global variables.

4. A computer-readable medium encoded with a program for processing information on a nucleotide sequence which allows a computer to execute processes including: (a) receiving, via a communication network, request information of an object or service, wherein the object or service is provided for an individual based on one or more genetic differences between individuals, and wherein the request information does not include genetic information; (b) searching a first memory area for positional information, and wherein the positional information corresponds to information on classification of the object or service, and wherein the positional information represents a position in a nucleotide sequence, and retrieving the positional information, wherein the first memory area is permitted to be accessed by a first processor; (c) transmitting, via a communication network, the positional information retrieved in process (b) to a second processor which is permitted to access a second memory area storing polymorphism information regarding the individual; (d) receiving, via a communication network, polymorphism information based on the positional information transmitted in process (c); and (e) outputting, via a communication network, the polymorphism information received in process (d) to a user, and wherein the user includes a third processor which is permitted to access a third memory area storing semantic information, and which searches the third memory area to retrieve, in response to said transmission of the polymorphism information, semantic information based on the transmitted polymorphism information, and outputs the semantic information to a device that utilizes the semantic information or information corresponding to the semantic information, which is used for a provision of the object or service substantially included in the request information, wherein processes (a)-(e) are conducted under the control of the first processor.

4. A computer-readable medium encoded with a program for processing information on a nucleotide sequence which allows a computer to execute processes including: (a) receiving, via a communication network, request information of an object or service, wherein the object or service is provided for an individual based on one or more genetic differences between individuals, and wherein the request information does not include genetic information; (b) searching a first memory area for positional information, and wherein the positional information corresponds to information on classification of the object or service, and wherein the positional information represents a position in a nucleotide sequence, and retrieving the positional information, wherein the first memory area is permitted to be accessed by a first processor; (c) transmitting, via a communication network, the positional information retrieved in process (b) to a second processor which is permitted to access a second memory area storing polymorphism information regarding the individual; (d) receiving, via a communication network, polymorphism information based on the positional information transmitted in process (c); and (e) outputting, via a communication network, the polymorphism information received in process (d) to a user, and wherein the user includes a third processor which is permitted to access a third memory area storing semantic information, and which searches the third memory area to retrieve, in response to said transmission of the polymorphism information, semantic information based on the transmitted polymorphism information, and outputs the semantic information to a device that utilizes the semantic information or information corresponding to the semantic information, which is used for a provision of the object or service substantially included in the request information, wherein processes (a)-(e) are conducted under the control of the first processor. 5. The computer-readable medium according to claim 4 , wherein the processes further comprise: in advance of process (c), receiving, via a communication network, consent information regarding the provision of polymorphism information from a provider of the request information; or in advance of process (e), receiving, via a communication network, consent information regarding the content of semantic information or information corresponding to the semantic information from the provider of the request information.

1. A method of providing a real time preview of changes to fonts in a computer system operating a document editing program having a document display window, comprising: storing an active document in a memory medium; displaying at least part of the active document in the document display window including text having an associated font command code, the document display window for editing the active document therein; tracking a cursor position controlled by a user in the document editing program; identifying a font by hovering of the cursor for a predetermined period of time over the font displayed in a menu or toolbar option of the document display window, the menu or toolbar option providing one or more available fonts, each of the available fonts associated with a respective font command codes that can be applied to the active document; inserting the font command code corresponding to the identified font into the memory medium storing the active document and updating the display of the active document in the document display windows to show the impact of the inserted font command code on the display of the text of the active document, without confirmation being received from the user; pushing the font command code corresponding to the identified font to the undo stack when a subsequent confirmation is received from the user; and removing the font command code corresponding to the identified font from the memory medium when subsequent confirmation is not received from the user or when another font command code is identified.

1. A method of providing a real time preview of changes to fonts in a computer system operating a document editing program having a document display window, comprising: storing an active document in a memory medium; displaying at least part of the active document in the document display window including text having an associated font command code, the document display window for editing the active document therein; tracking a cursor position controlled by a user in the document editing program; identifying a font by hovering of the cursor for a predetermined period of time over the font displayed in a menu or toolbar option of the document display window, the menu or toolbar option providing one or more available fonts, each of the available fonts associated with a respective font command codes that can be applied to the active document; inserting the font command code corresponding to the identified font into the memory medium storing the active document and updating the display of the active document in the document display windows to show the impact of the inserted font command code on the display of the text of the active document, without confirmation being received from the user; pushing the font command code corresponding to the identified font to the undo stack when a subsequent confirmation is received from the user; and removing the font command code corresponding to the identified font from the memory medium when subsequent confirmation is not received from the user or when another font command code is identified. 2. The method of claim 1 wherein the font comprises a font face.

21. The method of claim 18 , wherein the act of generating the plurality of marketing campaigns comprises an act of taking a cross-product of the positive keywords and the geographical modifier keywords.

21. The method of claim 18 , wherein the act of generating the plurality of marketing campaigns comprises an act of taking a cross-product of the positive keywords and the geographical modifier keywords. 22. The method of claim 21 , wherein the act of generating the plurality of marketing campaigns further comprises placing a bid with a search engine for each concatenation of a positive keyword and geographical modifier keyword.

1. A method implemented in computer-executable instructions that, when executed by a computer processor, opens a new application view and associates the application view with an application instance, the method comprising utilizing a data type recognizer to identify a document as containing an application's view logic that defines a graphical layout of one or more user interface components utilized by the application; instantiating a view object in-memory on a client computing device that causes at least one user interface component to be visually rendered on the client computing, device in accordance with the application's view logic; binding data displayed by the at least one user interface component to a set of data in a data model, the set of data identified by an XPath expression of an XBind; utilizing the data type recognizer to connect the view object to an application instance, wherein a plurality of view objects may be connected to the same application instance; and in response to a trigger event; identifying an emitter view object associated with the application instance as a source of the trigger event based on an indicator included with an XBind; identifying the application instance associated with the emitter view object; and using a context of the identified application instance and the emitter view object to execute the application's process code on the client computing device, the process code including at least one Action URL for submission to a communicator.

1. A method implemented in computer-executable instructions that, when executed by a computer processor, opens a new application view and associates the application view with an application instance, the method comprising utilizing a data type recognizer to identify a document as containing an application's view logic that defines a graphical layout of one or more user interface components utilized by the application; instantiating a view object in-memory on a client computing device that causes at least one user interface component to be visually rendered on the client computing, device in accordance with the application's view logic; binding data displayed by the at least one user interface component to a set of data in a data model, the set of data identified by an XPath expression of an XBind; utilizing the data type recognizer to connect the view object to an application instance, wherein a plurality of view objects may be connected to the same application instance; and in response to a trigger event; identifying an emitter view object associated with the application instance as a source of the trigger event based on an indicator included with an XBind; identifying the application instance associated with the emitter view object; and using a context of the identified application instance and the emitter view object to execute the application's process code on the client computing device, the process code including at least one Action URL for submission to a communicator. 8. The method as recited in claim 1 , wherein the application's view logic is described in a UI XML document adhering to a first schema, and wherein the application's process logic is described in a process XML document that adheres to a second schema.

1. A method for mapping an XML (eXtensible Markup Language) data structure to an ontology, wherein the method is encoded in program instructions that are recorded on and executed by at least one of a computing device and a co-processor device, the method comprising: providing an XML document with a corresponding XML schema definition; a) mapping XML schema declarations and definitions to ontology schema definitions by: mapping XML element and attribute declarations to ontology property definition; and mapping XML complexType definitions to ontology class definitions; a1) validating the XML document by the XML schema to generate a PSVI (post schema validation info set) annotation of the XML document; b) using the PSVI annotation from the validation of the XML document by the XML schema for mapping XML nodes with known PSVI-type to ontology instances by: mapping PSVI complexType annotations to ontology class instances; mapping element and attribute nodes to ontology property instances; and mapping XML nodes with a known PSVI-type in the following way to ontology instances: b1) for each XML element node with a complexType annotation an instance of a class of the ontology is generated, the class of this instance is the class to which this complexType definition is mapped; b2) mapping an XML simpleType element node to a datatype property instance of the ontology, the domain class instance of the datatype property instance being the instance which is generated for the PSVI type annotation where the element node is used; b3) mapping an XML simpleContent element node with an attribute to an object property instance of the ontology, the object property having a domain class instance and a range class instance, the domain class instance of the object property instance being the instance which is generated for the type annotation where the element is used, the range class instance of the object property instance being the class instance which is generated for the PSVI type annotation of the XML simpleContent element node; b4) mapping an XML complexContent element node to an object property instance of the ontology, the object property having a domain class instance and a range class instance, the domain class instance of the object property instance being the instance which is generated for the PSVI type annotation where the element is used, and the range class instance of the object property instance being the class instance which is generated for the PSVI type annotation of the XML complexContent element node; b5) mapping an XML simpleType attribute node to a datatype property instance of the ontology, the domain class instance of the datatype property instance being the instance which is generated for the PSVI type annotation where the attribute node is used; c) defining predefined ontology schema definitions by defining a predefined ontology class definition and a predefined ontology datatype property definition and a predefined object property definition; d) mapping XML nodes without PSVI-type annotation to ontology instances and to ontology definitions by mapping XML element and attribute nodes to ontology property instances of the predefined ontology property definitions and ontology class instances of the predefined ontology class definitions; e) wherein this mapping is performed dynamically while evaluating a query inquiring data from the XML document.

1. A method for mapping an XML (eXtensible Markup Language) data structure to an ontology, wherein the method is encoded in program instructions that are recorded on and executed by at least one of a computing device and a co-processor device, the method comprising: providing an XML document with a corresponding XML schema definition; a) mapping XML schema declarations and definitions to ontology schema definitions by: mapping XML element and attribute declarations to ontology property definition; and mapping XML complexType definitions to ontology class definitions; a1) validating the XML document by the XML schema to generate a PSVI (post schema validation info set) annotation of the XML document; b) using the PSVI annotation from the validation of the XML document by the XML schema for mapping XML nodes with known PSVI-type to ontology instances by: mapping PSVI complexType annotations to ontology class instances; mapping element and attribute nodes to ontology property instances; and mapping XML nodes with a known PSVI-type in the following way to ontology instances: b1) for each XML element node with a complexType annotation an instance of a class of the ontology is generated, the class of this instance is the class to which this complexType definition is mapped; b2) mapping an XML simpleType element node to a datatype property instance of the ontology, the domain class instance of the datatype property instance being the instance which is generated for the PSVI type annotation where the element node is used; b3) mapping an XML simpleContent element node with an attribute to an object property instance of the ontology, the object property having a domain class instance and a range class instance, the domain class instance of the object property instance being the instance which is generated for the type annotation where the element is used, the range class instance of the object property instance being the class instance which is generated for the PSVI type annotation of the XML simpleContent element node; b4) mapping an XML complexContent element node to an object property instance of the ontology, the object property having a domain class instance and a range class instance, the domain class instance of the object property instance being the instance which is generated for the PSVI type annotation where the element is used, and the range class instance of the object property instance being the class instance which is generated for the PSVI type annotation of the XML complexContent element node; b5) mapping an XML simpleType attribute node to a datatype property instance of the ontology, the domain class instance of the datatype property instance being the instance which is generated for the PSVI type annotation where the attribute node is used; c) defining predefined ontology schema definitions by defining a predefined ontology class definition and a predefined ontology datatype property definition and a predefined object property definition; d) mapping XML nodes without PSVI-type annotation to ontology instances and to ontology definitions by mapping XML element and attribute nodes to ontology property instances of the predefined ontology property definitions and ontology class instances of the predefined ontology class definitions; e) wherein this mapping is performed dynamically while evaluating a query inquiring data from the XML document. 2. The method according to claim 1 comprising the steps of: a) mapping XML schema declarations and definitions to ontology schema definitions in the following way: a1) mapping an XSD (XML Schema Definition) complexType definition to a class definition of the ontology; a2) mapping an XSD complexContent element declaration of an XSD complexType definition to an object property definition of the ontology, the object property having a domain class and a range class, the domain class being the class where the element is used, and the range class of the object property being the class to which the complexType of the complexContent element is mapped; a3) mapping an XSD simpleType element declaration to a datatype property definition of the ontology, the datatype property having a domain class, the domain class being the class where the element is used, and the range type being the XML schema type of the simpleType element declaration; a4) mapping an XSD simpleContent element declaration with an attribute to an object property definition of the ontology, the object property having a domain class and a range class, the domain class being the class where the element is used, and the range class of the object property being the class to which the complexType of the simpleContent element is mapped; a5) mapping an XSD attribute declaration to a datatype property definition of the ontology, the datatype property having a domain class, the domain class being the class where the element is used, and the range type being the XML schema type of the attribute declaration.

1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user.

1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. 35. The method of claim 1 , wherein receiving at least one query includes receiving at least one query for at least one time percentage report.

20. A system for estimating a cardinality of a multiple-join query of relational database tables, comprising: means for calculating data representing a join graph of the multiple-join query of the relational database tables, the join graph having a set of vertices and a set of edges, the set of vertices corresponding one-to-one with the relational database tables in the multiple-join query, the set of edges corresponding one-to-one with join predicates expressed and implied in the query; eliminating tail vertices from the join graph to form a reduced graph; and means for using the data representing the reduced join graph to estimate the cardinality of the multiple-join query of the relational database tables to select a join order for the multiple-join query.

20. A system for estimating a cardinality of a multiple-join query of relational database tables, comprising: means for calculating data representing a join graph of the multiple-join query of the relational database tables, the join graph having a set of vertices and a set of edges, the set of vertices corresponding one-to-one with the relational database tables in the multiple-join query, the set of edges corresponding one-to-one with join predicates expressed and implied in the query; eliminating tail vertices from the join graph to form a reduced graph; and means for using the data representing the reduced join graph to estimate the cardinality of the multiple-join query of the relational database tables to select a join order for the multiple-join query. 22. The system of claim 20, wherein the means for estimating the cardinality of the multiple-join query comprises means for multiplying a selectivity of the join represented by each edge, the cardinality of each relational database table represented by each vertex, and an individual selectivity of the table represented by each vertex.

5. A system for a service registry for web services, the service registry comprising a plurality of different environments for the web services, the service registry configured to: detect the creation of a first endpoint definition document for a specific web service, the first endpoint definition document defining address data for the specific web service in one environment, wherein the first endpoint definition document was created manually by an author of the web service; and based on the detecting of the creation of the first endpoint definition document for the specific web service, automatically perform: query the service registry to determine all environments that are defined in the service registry; determine the plurality of different environments based on the determination of all environments that are defined in the service registry, wherein the plurality of different environments comprise any environment for which no endpoint definition document for the specific web service exists in the service registry; access data defining each of the plurality of different environments associated with the service registry; create endpoint definition document for each of the plurality of different environments for the specific web service from the first endpoint definition document and the accessed data; and store the created respective endpoint definition document for each of the plurality of different environments using the service registry.

5. A system for a service registry for web services, the service registry comprising a plurality of different environments for the web services, the service registry configured to: detect the creation of a first endpoint definition document for a specific web service, the first endpoint definition document defining address data for the specific web service in one environment, wherein the first endpoint definition document was created manually by an author of the web service; and based on the detecting of the creation of the first endpoint definition document for the specific web service, automatically perform: query the service registry to determine all environments that are defined in the service registry; determine the plurality of different environments based on the determination of all environments that are defined in the service registry, wherein the plurality of different environments comprise any environment for which no endpoint definition document for the specific web service exists in the service registry; access data defining each of the plurality of different environments associated with the service registry; create endpoint definition document for each of the plurality of different environments for the specific web service from the first endpoint definition document and the accessed data; and store the created respective endpoint definition document for each of the plurality of different environments using the service registry. 7. A system according to claim 5 , wherein the service registry is configured to create the one or more additional endpoint definition documents for the specific web service by accessing a template for each environment and modify the first endpoint definition document according to an accessed template.

23. The non-transitory computer readable storage medium of claim 22 wherein generating a first set of tokens from the first portion of the information content using the abstract data structure comprises: finding a token candidate in the first portion of the information content using a token delimiter indicator from a corresponding token identified in the abstract data structure; generating a signature of the token candidate; comparing the signature of the token candidate with a signature of the corresponding token from the abstract data structure; and adding the token candidate to the first set of tokens if the signature of the token candidate matches the signature of the corresponding token from the abstract data structure.

23. The non-transitory computer readable storage medium of claim 22 wherein generating a first set of tokens from the first portion of the information content using the abstract data structure comprises: finding a token candidate in the first portion of the information content using a token delimiter indicator from a corresponding token identified in the abstract data structure; generating a signature of the token candidate; comparing the signature of the token candidate with a signature of the corresponding token from the abstract data structure; and adding the token candidate to the first set of tokens if the signature of the token candidate matches the signature of the corresponding token from the abstract data structure. 24. The non-transitory computer readable storage medium of claim 23 wherein the token delimiter indicator comprises a value of a first character of the relevant token and the length of the relevant token.

5. A computer-implemented method comprising: executing code of a network crawler, the executing launching the network crawler, the network crawler configured to access a network document and to perform a test for an object of the network document based at least in part on a test document, the test document stored separately from the code and specifying the test for the object of the network document, the test document further specifying a user state for accessing the network document, and the test identifying an expected outcome associated with performing an action on the object; providing a network location of the network document and an identifier of the network document to the network crawler, wherein the network crawler accesses the test document from the network location, accesses the network document based at least in part on the identifier and the user state, identifies the object from the test document, and performs the action on the object based at least in part on the test document; accessing a result of the test performed by the network crawler, the result comprising an indication that an outcome different from the expected outcome occurred based at least in part on the action being performed on the object, the result further identifying a second object of the network document not identified in the test document; generating a report associated with the network document based at least in part on the result of the test, the report identifying a correction to the object such that the expected outcome occurs when the action is performed, the report further comprising a metric for the second object based at least in part on the result, wherein the network document is updated by at least updating the object according to the correction; and receiving a second test document for testing the second object based at least in part on the metric.

5. A computer-implemented method comprising: executing code of a network crawler, the executing launching the network crawler, the network crawler configured to access a network document and to perform a test for an object of the network document based at least in part on a test document, the test document stored separately from the code and specifying the test for the object of the network document, the test document further specifying a user state for accessing the network document, and the test identifying an expected outcome associated with performing an action on the object; providing a network location of the network document and an identifier of the network document to the network crawler, wherein the network crawler accesses the test document from the network location, accesses the network document based at least in part on the identifier and the user state, identifies the object from the test document, and performs the action on the object based at least in part on the test document; accessing a result of the test performed by the network crawler, the result comprising an indication that an outcome different from the expected outcome occurred based at least in part on the action being performed on the object, the result further identifying a second object of the network document not identified in the test document; generating a report associated with the network document based at least in part on the result of the test, the report identifying a correction to the object such that the expected outcome occurs when the action is performed, the report further comprising a metric for the second object based at least in part on the result, wherein the network document is updated by at least updating the object according to the correction; and receiving a second test document for testing the second object based at least in part on the metric. 8. The computer-implemented method of claim 5 , further comprising: tracking testing of the network document based at least in part on the network crawler; determining that the network document was previously tested; determining a previous test result of the object; and generating an indication of a bug based at least in part on a comparison of the result of the test with the previous test result.

8. A system for determining solutions to a problem experienced by a user with respect to a data processing system, comprising: a processor; a memory storing instructions operable to be executed by the processor, wherein the instructions include instructions to: select a collection of documents; analyze the text in each document using plain text analysis and an unstructured information management application containing text analytics rules to identify problems and associated solutions, the plain text analysis using a problem dictionary containing words and phrases that identify sentences describing problems and a solution dictionary containing words and phrases that identify sentences describing solutions to problems; create a searchable index of problems and associated solutions and storing the index in a database; receive a problem description from a user of the problem experienced by the user with respect to the data processing system, after creating the searchable index; analyze the received problem description using plain text analysis to extract one or more keywords from the problem description; search the index of problems and associated solutions using the one or more extracted keywords; return one or more documents containing words or phrases that are similar to the one or more extracted keywords; and present the documents relevant for the problem and associated solutions to the user.

8. A system for determining solutions to a problem experienced by a user with respect to a data processing system, comprising: a processor; a memory storing instructions operable to be executed by the processor, wherein the instructions include instructions to: select a collection of documents; analyze the text in each document using plain text analysis and an unstructured information management application containing text analytics rules to identify problems and associated solutions, the plain text analysis using a problem dictionary containing words and phrases that identify sentences describing problems and a solution dictionary containing words and phrases that identify sentences describing solutions to problems; create a searchable index of problems and associated solutions and storing the index in a database; receive a problem description from a user of the problem experienced by the user with respect to the data processing system, after creating the searchable index; analyze the received problem description using plain text analysis to extract one or more keywords from the problem description; search the index of problems and associated solutions using the one or more extracted keywords; return one or more documents containing words or phrases that are similar to the one or more extracted keywords; and present the documents relevant for the problem and associated solutions to the user. 13. The system of claim 8 , wherein the memory further comprises instructions to: receive a user input identifying erroneous solutions to a problem; and remove erroneous solutions from the index of problems and associated solutions, based on the received user input.

10. The system for generating data describing concepts from data describing schema of claim 8 , wherein the deriving of the respective graph representations further comprises determining a respective type and a respective similarity class for each vertice of the graph representations, and using the type and similarity class during mining of the set of graphs.

10. The system for generating data describing concepts from data describing schema of claim 8 , wherein the deriving of the respective graph representations further comprises determining a respective type and a respective similarity class for each vertice of the graph representations, and using the type and similarity class during mining of the set of graphs. 11. The system for generating data describing concepts from data describing schema of claim 10 , wherein the similarity class of each vertex is determined according to a type of data represented by the vertex and a pairwise comparison of name similarity of the vertexes in the similarity class, the pairwise comparison the name similarity conditioned on the similarity being greater than a threshold.

32. A non-transitory computer readable storage medium comprising program instructions, wherein the program instructions are computer-executable to implement an event message gate unit on a client platform in a distributed computing system, wherein the program instructions are configured to: obtain, from a remote location, a markup language schema on a client platform, wherein said markup language schema defines a message interface of a remote service for a plurality of events generated by the remote service and indicates the plurality of events to be published by the remote service; obtain an address for said remote service within a distributed computing system; automatically construct, using computer-executable message endpoint construction code on the client platform, an event message endpoint on the client platform according to the markup language schema and the obtained address for the remote service, wherein said automatically constructing is performed within a runtime system of the client platform, and wherein the event message endpoint implements an API to send and receive event messages to and from the service; receive indications from one or more client processes registering interest in receiving one or more of a plurality of events generated by the remote service in the distributed computing system; automatically subscribe to the one or more events with the remote service in response to said indications registering interest in the one or more events received from the one or more client processes such that the event message endpoint becomes subscribed to the one or more events; receive over a network a message in a markup language sent to the client platform in the distributed computing system from the service in the distributed computing system, wherein the message is received at the event message endpoint from the service over the network in the distributed computing system, and wherein the message includes a markup language representation of one of the one or more events generated by the service to which the event message endpoint is subscribed; and send the markup language representation of the event from the event message endpoint to at least one of the one or more client processes registered with the event message endpoint to receive the event, wherein said markup language representation is in a data representation format which is independent of said client platform.

32. A non-transitory computer readable storage medium comprising program instructions, wherein the program instructions are computer-executable to implement an event message gate unit on a client platform in a distributed computing system, wherein the program instructions are configured to: obtain, from a remote location, a markup language schema on a client platform, wherein said markup language schema defines a message interface of a remote service for a plurality of events generated by the remote service and indicates the plurality of events to be published by the remote service; obtain an address for said remote service within a distributed computing system; automatically construct, using computer-executable message endpoint construction code on the client platform, an event message endpoint on the client platform according to the markup language schema and the obtained address for the remote service, wherein said automatically constructing is performed within a runtime system of the client platform, and wherein the event message endpoint implements an API to send and receive event messages to and from the service; receive indications from one or more client processes registering interest in receiving one or more of a plurality of events generated by the remote service in the distributed computing system; automatically subscribe to the one or more events with the remote service in response to said indications registering interest in the one or more events received from the one or more client processes such that the event message endpoint becomes subscribed to the one or more events; receive over a network a message in a markup language sent to the client platform in the distributed computing system from the service in the distributed computing system, wherein the message is received at the event message endpoint from the service over the network in the distributed computing system, and wherein the message includes a markup language representation of one of the one or more events generated by the service to which the event message endpoint is subscribed; and send the markup language representation of the event from the event message endpoint to at least one of the one or more client processes registered with the event message endpoint to receive the event, wherein said markup language representation is in a data representation format which is independent of said client platform. 36. The non-transitory computer readable storage medium as recited in claim 32 , wherein the markup language schema defines a plurality of messages including markup language representations of the plurality of events generated by the service, wherein the event message endpoint is configured to verify correctness of the markup language message from the service according to the markup language schema prior to said sending the markup language representation of the event to the at least one of the one or more client processes.

15. A volatile or non-volatile computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, cause: executing an index generation statement identifying a plurality of path expressions and a plurality of columns of a first table for indexing a collection of documents wherein said plurality of path expressions identify less than all nodes in the collection of documents wherein for each column of said plurality of columns, said index generation statement specifies an association between said each column and a respective path expression of said plurality of path expressions; wherein execution of said index generation statement causes generation of said first table, wherein the first table comprises a first set of entries; wherein for each column of the plurality of columns of said first table, each entry of the first set of entries contains a node value of a node identified by the respective path expression of said each column, said node value being from a document of said collection of documents; wherein the collection of documents is also indexed by a second table, wherein the second table comprises a second set of entries, each entry in the second set of entries: being associated with a given node of a document in the collection of documents, and including location data for locating content in the document, wherein the content is associated with the given node and path data that corresponds to a path to the given node in the document; and intercepting, by a database system, a query for first information from a collection of documents, wherein the query for first information does not reference said first table and said second table; said database system rewriting the query for first information to generate a rewritten query that references said first table and said second table; wherein the query comprises one or more predicates; based on the rewritten query, said database system generating a first query plan using both the first table and the second table, wherein the first query plan, when executed by the database system, causes the database system to perform: identifying one or more first entries from the first table that contain a node value that satisfies the one or more predicates; extracting second information from the one or more first entries identified from the first table; extracting, using the second information, the first information from one or more second entries in the second table wherein the first table and the second table are two different tables.

15. A volatile or non-volatile computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, cause: executing an index generation statement identifying a plurality of path expressions and a plurality of columns of a first table for indexing a collection of documents wherein said plurality of path expressions identify less than all nodes in the collection of documents wherein for each column of said plurality of columns, said index generation statement specifies an association between said each column and a respective path expression of said plurality of path expressions; wherein execution of said index generation statement causes generation of said first table, wherein the first table comprises a first set of entries; wherein for each column of the plurality of columns of said first table, each entry of the first set of entries contains a node value of a node identified by the respective path expression of said each column, said node value being from a document of said collection of documents; wherein the collection of documents is also indexed by a second table, wherein the second table comprises a second set of entries, each entry in the second set of entries: being associated with a given node of a document in the collection of documents, and including location data for locating content in the document, wherein the content is associated with the given node and path data that corresponds to a path to the given node in the document; and intercepting, by a database system, a query for first information from a collection of documents, wherein the query for first information does not reference said first table and said second table; said database system rewriting the query for first information to generate a rewritten query that references said first table and said second table; wherein the query comprises one or more predicates; based on the rewritten query, said database system generating a first query plan using both the first table and the second table, wherein the first query plan, when executed by the database system, causes the database system to perform: identifying one or more first entries from the first table that contain a node value that satisfies the one or more predicates; extracting second information from the one or more first entries identified from the first table; extracting, using the second information, the first information from one or more second entries in the second table wherein the first table and the second table are two different tables. 24. The medium of claim 15 , wherein at least one document in the collection of documents is stored in a tree form.

12. An apparatus of claim 11 , wherein the one or more semantic information brokers comprise one or more information spaces, and the apparatus is further caused to: compute a stability factor corresponding to each of the one or more semantic information brokers; and select one or more of the semantic information brokers as master semantic information brokers for a respective one of the information spaces based on the computed stability factors, wherein the one or more master semantic information brokers manage communication among the semantic information brokers within the respective information space.

12. An apparatus of claim 11 , wherein the one or more semantic information brokers comprise one or more information spaces, and the apparatus is further caused to: compute a stability factor corresponding to each of the one or more semantic information brokers; and select one or more of the semantic information brokers as master semantic information brokers for a respective one of the information spaces based on the computed stability factors, wherein the one or more master semantic information brokers manage communication among the semantic information brokers within the respective information space. 17. An apparatus of claim 12 , wherein the apparatus is further caused to: periodically compute a new stability factor for each of the semantic information brokers; determine whether one or more of the new stability factors is below a predetermined stability threshold; and optimize the semantic information brokers based on the determination.

1. A method for controlling an application based on a handwriting input, the method comprising: displaying a first screen on a touch screen display of a terminal; receiving a message associated with an application, the message being received while displaying the first screen; displaying a notification indicating the message receipt on the touch screen display while displaying a portion of the first screen; if the notification is displayed on the touch screen display, activating a handwriting recognition module to recognize a handwriting input to be associated with the application; recognizing the handwriting input received on the touch screen display of the terminal; determining a symbol corresponding to the handwriting input; selecting the application capable of being associated with the symbol; associating the symbol with a function of the application; and processing the associated symbol through the application executed in a background state.

1. A method for controlling an application based on a handwriting input, the method comprising: displaying a first screen on a touch screen display of a terminal; receiving a message associated with an application, the message being received while displaying the first screen; displaying a notification indicating the message receipt on the touch screen display while displaying a portion of the first screen; if the notification is displayed on the touch screen display, activating a handwriting recognition module to recognize a handwriting input to be associated with the application; recognizing the handwriting input received on the touch screen display of the terminal; determining a symbol corresponding to the handwriting input; selecting the application capable of being associated with the symbol; associating the symbol with a function of the application; and processing the associated symbol through the application executed in a background state. 10. The method of claim 1 , further comprising: displaying a first application associated with a number if the determined symbol includes the number without including a character; and displaying a second application associated with a character if the determined symbol includes the character.

6. A computer-implemented method comprising: presenting an electronic document at a first client computer; receiving a notification from a server computer, the notification indicating that a new comment object associated with the electronic document exists; requesting the new comment object from the server computer for automatic propagation thereto, the new comment object being associated with the electronic document concurrently accessed from a second client computer and having a data structure that includes a reference specification field containing a numeric identification that describes at least one of a beginning or an ending of a commented portion in a numerical format and containing context information that identifies at least one of the beginning or the ending of the commented portion using text from the beginning or the ending of the commented portion; presenting a revised electronic document having the new comment object merged therein on the first client computer; and saving, using a processor of the first client computer, the electronic document to provide a saved electronic document, the saving causing removal of the new comment object from a queue of the server computer.

6. A computer-implemented method comprising: presenting an electronic document at a first client computer; receiving a notification from a server computer, the notification indicating that a new comment object associated with the electronic document exists; requesting the new comment object from the server computer for automatic propagation thereto, the new comment object being associated with the electronic document concurrently accessed from a second client computer and having a data structure that includes a reference specification field containing a numeric identification that describes at least one of a beginning or an ending of a commented portion in a numerical format and containing context information that identifies at least one of the beginning or the ending of the commented portion using text from the beginning or the ending of the commented portion; presenting a revised electronic document having the new comment object merged therein on the first client computer; and saving, using a processor of the first client computer, the electronic document to provide a saved electronic document, the saving causing removal of the new comment object from a queue of the server computer. 10. The computer-implemented method of claim 6 , wherein presenting the revised electronic document comprises: determining an action associated with the new comment object; and presenting comment content associated with the new comment object when the action is an add operation or a modify operation.

14. A system including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: identify a message that is associated with two or more users, wherein the users include a sender and one or more recipients, and wherein the message includes one or more terms; determine a vague term of the terms, wherein the vague term includes a plurality of consecutive words, the consecutive words including at least a word and an additional word; determine that at least the word of the vague term is a reference to a given user of the users, the given user being the sender or one of the recipients; identify, based on determining that the word is a reference to the given user, a user-restricted database associated with the given user, wherein the user-restricted database includes content personal to the given user, and wherein access to the user-restricted database is limitable by the given user; determine, based on the user-restricted database, additional information that is related to the vague term, wherein the user-restricted database is used in determining the additional information that is related to the vague term based on the user-restricted database being associated with the given user and based on the given user being referenced by the word of the vague term; and provide the additional information to at least one of the users.

14. A system including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: identify a message that is associated with two or more users, wherein the users include a sender and one or more recipients, and wherein the message includes one or more terms; determine a vague term of the terms, wherein the vague term includes a plurality of consecutive words, the consecutive words including at least a word and an additional word; determine that at least the word of the vague term is a reference to a given user of the users, the given user being the sender or one of the recipients; identify, based on determining that the word is a reference to the given user, a user-restricted database associated with the given user, wherein the user-restricted database includes content personal to the given user, and wherein access to the user-restricted database is limitable by the given user; determine, based on the user-restricted database, additional information that is related to the vague term, wherein the user-restricted database is used in determining the additional information that is related to the vague term based on the user-restricted database being associated with the given user and based on the given user being referenced by the word of the vague term; and provide the additional information to at least one of the users. 19. The system of claim 14 , wherein the instructions to provide the additional information include instructions to provide a notification to the sender and wherein the sender is the creator of the message.

4. The video editor of claim 1 , wherein the query parameter comprises a sample media query parameter based on a sample media clip selected by the user.

4. The video editor of claim 1 , wherein the query parameter comprises a sample media query parameter based on a sample media clip selected by the user. 5. The video editor of claim 4 , wherein the sample media query parameter comprises a sample media query parameter selected from: a face detection matching option, an object detection matching option, a text detection matching option, a color matching option, or an audio tune matching option.

3. The method of claim 1 , wherein the contextual information further comprises location information from a device.

3. The method of claim 1 , wherein the contextual information further comprises location information from a device. 4. The method of claim 3 , wherein the step of presenting, by one or more processors, one or more hyperlinks further comprises: determining, by one or more processors, that the received location information from the device matches, within a predetermined threshold, a location at which a second hyperlink was previously accessed by the device; and presenting, by one or more processors, the second hyperlink.