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9. A non-transitory computer readable medium having instruction stored thereon, wherein the instructions, when executed by a processor, cause the processor to: provide an associative mapping for a first communication protocol and a second communication protocol in a memory, wherein the second communication protocol is different from the first communication protocol, wherein a data message structured according to the first communication protocol comprises a serialized-binary message having a self-describing schema, the serialized-binary message comprising i) a data set comprising data values originating from a connected device, and ii) a metadata construct that includes one or more description values of the data set, and wherein the associative mapping includes one or more control parameters associated with transmission events of the data message to one or more devices in the network, wherein a configuration message structured according to the first communication protocol comprises a second serialized-binary message having the self-describing schema, the second serialized binary message comprising i) the one or more control parameters associated with the transmission events of the data message to the one or more devices in the network, and ii) a second metadata construct that includes one or more description values of the one or more control parameters; in response to receiving, from a given connected device, a first data message transmitted according to the second communication protocol, generate, according to the associative mapping, a second data message structured according to the first communication protocol and transmit, according to the associative mapping, the second data packet to a device in the network; in response to receiving, from the device in the network, a given configuration message structured according to the first communication protocol, wherein the given configuration message includes one or more control parameters associated with one or more transmission events of a given data message to one or more devices in the network, update the associative mapping with the one or more control parameters of the given configuration message; and in response to receiving, from the given connected device, a third data message transmitted according to the second communication protocol, generate, according to the updated associative mapping, a fourth data message structured according to the first communication protocol and transmit, according to the updated associative mapping, the fourth data message to a device in the network.

9. A non-transitory computer readable medium having instruction stored thereon, wherein the instructions, when executed by a processor, cause the processor to: provide an associative mapping for a first communication protocol and a second communication protocol in a memory, wherein the second communication protocol is different from the first communication protocol, wherein a data message structured according to the first communication protocol comprises a serialized-binary message having a self-describing schema, the serialized-binary message comprising i) a data set comprising data values originating from a connected device, and ii) a metadata construct that includes one or more description values of the data set, and wherein the associative mapping includes one or more control parameters associated with transmission events of the data message to one or more devices in the network, wherein a configuration message structured according to the first communication protocol comprises a second serialized-binary message having the self-describing schema, the second serialized binary message comprising i) the one or more control parameters associated with the transmission events of the data message to the one or more devices in the network, and ii) a second metadata construct that includes one or more description values of the one or more control parameters; in response to receiving, from a given connected device, a first data message transmitted according to the second communication protocol, generate, according to the associative mapping, a second data message structured according to the first communication protocol and transmit, according to the associative mapping, the second data packet to a device in the network; in response to receiving, from the device in the network, a given configuration message structured according to the first communication protocol, wherein the given configuration message includes one or more control parameters associated with one or more transmission events of a given data message to one or more devices in the network, update the associative mapping with the one or more control parameters of the given configuration message; and in response to receiving, from the given connected device, a third data message transmitted according to the second communication protocol, generate, according to the updated associative mapping, a fourth data message structured according to the first communication protocol and transmit, according to the updated associative mapping, the fourth data message to a device in the network. 10. The computer readable medium of claim 9 , wherein the first data message and the third data message are received via a wireless connection.

16. A machine-implemented method comprising: receiving, by a document archive server, a client request relating to an electronic document stored at the document archive server, wherein (a) the client request is for generation of an audit-enabled document, (b) the electronic document is associated with actions-taken information that exists separately from the electronic document, and (c) the actions-taken information describes actions taken with respect to the electronic document; retrieving, by the document archive server, from an audit information server and in response to the client request, the actions-taken information associated with the electronic document; generating, by the document archive server, an audit-enabled electronic document that includes the actions-taken information and the electronic document; and providing, by the document archive server, the audit-enabled electronic document.

16. A machine-implemented method comprising: receiving, by a document archive server, a client request relating to an electronic document stored at the document archive server, wherein (a) the client request is for generation of an audit-enabled document, (b) the electronic document is associated with actions-taken information that exists separately from the electronic document, and (c) the actions-taken information describes actions taken with respect to the electronic document; retrieving, by the document archive server, from an audit information server and in response to the client request, the actions-taken information associated with the electronic document; generating, by the document archive server, an audit-enabled electronic document that includes the actions-taken information and the electronic document; and providing, by the document archive server, the audit-enabled electronic document. 21. The method of claim 16 , wherein: the client request is triggered by attaching the electronic document to an email addressed to an email recipient; the audit-enabled electronic document further includes a specification of authorized actions to be associated with the electronic document; and the authorized actions are based on an identity of the email recipient.

9. The method of claim 7 further comprising: dynamically providing the at least one local suggested tag and/or the at least one external suggested tag for the at least one first file to the user via the computing interface in response to the one or more inputs by repeating the acts of determining based on additional inputs provided by the user.

9. The method of claim 7 further comprising: dynamically providing the at least one local suggested tag and/or the at least one external suggested tag for the at least one first file to the user via the computing interface in response to the one or more inputs by repeating the acts of determining based on additional inputs provided by the user. 10. The method of claim 9 further comprising: heuristically determining the at least one local suggested tag based on one or more of a selected file of the at least one first file, a tag associated with a similar file, a recently-utilized tag, a commonly-used tag, a rule-based criterion, or a heuristic-based criterion.

1. A computer-implemented method comprising: receiving, at a mobile computing device, ambiguous user voice input that indicates more than one of a plurality of commands; identifying one or more physical structures that are located within a threshold distance of the mobile computing device based on a presence of one or more wired or wireless connections that are currently available to the mobile computing device; determining a current context associated with the mobile computing device, wherein the context associated with the mobile device is determined based on, at least, the one or more physical structures; disambiguating the ambiguous user voice input by selecting a command from the plurality of commands based on the context associated with the mobile computing device; and causing output associated with performance of the selected command to be provided by the mobile computing device.

1. A computer-implemented method comprising: receiving, at a mobile computing device, ambiguous user voice input that indicates more than one of a plurality of commands; identifying one or more physical structures that are located within a threshold distance of the mobile computing device based on a presence of one or more wired or wireless connections that are currently available to the mobile computing device; determining a current context associated with the mobile computing device, wherein the context associated with the mobile device is determined based on, at least, the one or more physical structures; disambiguating the ambiguous user voice input by selecting a command from the plurality of commands based on the context associated with the mobile computing device; and causing output associated with performance of the selected command to be provided by the mobile computing device. 2. The computer-implemented method of claim 1 , further comprising identifying one or more other computing devices that are located nearby the mobile computing device; and wherein the context associated with the mobile computing device is determined further based on, at least, the identified other computing devices.

10. A computer-readable storage medium containing instructions for controlling a computer system to clean up handwriting, by a method comprising: receiving handwriting of a user that has been digitized; performing intra-stroke overtracing cleanup of the handwriting, an intra-stroke overtracing occurring when the user overtraces a portion of a stroke with another portion of the stroke, the intra-stroke overtracing cleanup including replacing the overtraced and overtracing portions with an averaged portion; performing inter-stroke overtracing cleanup of the handwriting, an inter-stroke overtracing occurring when the user overtraces one stroke with another stroke, the inter-stroke overtracing cleanup including replacing the overtraced and overtracing strokes with a merged stroke; performing correction cleanup of the handwriting, a correction occurring when the user overwrites one character with another character, the correction cleanup including replacing the overwritten character with the overwriting character; performing touch up stroke cleanup of the handwriting, a stroke touch up occurring when the user writes a stroke to complete an existing stroke, the touch up cleanup including merging the short and the existing stroke; and performing insertion cleanup of the handwriting, an insertion occurring when the user writes a character between two existing characters, the insertion cleanup including inserting the character between the two existing characters.

10. A computer-readable storage medium containing instructions for controlling a computer system to clean up handwriting, by a method comprising: receiving handwriting of a user that has been digitized; performing intra-stroke overtracing cleanup of the handwriting, an intra-stroke overtracing occurring when the user overtraces a portion of a stroke with another portion of the stroke, the intra-stroke overtracing cleanup including replacing the overtraced and overtracing portions with an averaged portion; performing inter-stroke overtracing cleanup of the handwriting, an inter-stroke overtracing occurring when the user overtraces one stroke with another stroke, the inter-stroke overtracing cleanup including replacing the overtraced and overtracing strokes with a merged stroke; performing correction cleanup of the handwriting, a correction occurring when the user overwrites one character with another character, the correction cleanup including replacing the overwritten character with the overwriting character; performing touch up stroke cleanup of the handwriting, a stroke touch up occurring when the user writes a stroke to complete an existing stroke, the touch up cleanup including merging the short and the existing stroke; and performing insertion cleanup of the handwriting, an insertion occurring when the user writes a character between two existing characters, the insertion cleanup including inserting the character between the two existing characters. 15. The computer-readable storage medium of claim 10 including temporally reordering late strokes.

1. A method comprising: receiving one or more first search queries; processing fields in the one or more first search queries wherein the processing comprises at least one of address standardization, proximity boundaries, nickname interpretation, extraction of at least prefix, and generation of at least one non-literal key; constructing one or more second search queries associated with the one or more first search queries wherein the one or more second search queries are stack-based; sending the one or more second search queries to one or more search conductors wherein the one or more search conductors are associated with collections specified in the one or more second search queries; scoring a match of one or more fields of one or more records against the one or more second search queries; adding the one or more records to a results list based on the scoring; continually scoring the one or more records until all records in a partition have been processed; sorting the results list; receiving and collating the results list; performing aggregate analytics processing on the results list wherein the aggregate analytics processing comprises extracting, disambiguating, normalizing, grouping, and indexing a first set of facets from documents wherein the facets comprise different levels of specificity; returning results of the aggregate analytics processing; storing the results in a knowledge base wherein the knowledge base is part of an in-memory database system architecture; loading new documents into an in-memory database; extracting a second set of disambiguated facets from the new documents; and comparing the second set of disambiguated facets with the first set of disambiguated facets wherein the comparing comprises: updating the knowledge base and returning the ID of matching facets; and assigning a unique ID to unmatched facets, associating the unmatched facets with a cluster of defining features, and storing the unmatched facets and the cluster in the knowledge base.

1. A method comprising: receiving one or more first search queries; processing fields in the one or more first search queries wherein the processing comprises at least one of address standardization, proximity boundaries, nickname interpretation, extraction of at least prefix, and generation of at least one non-literal key; constructing one or more second search queries associated with the one or more first search queries wherein the one or more second search queries are stack-based; sending the one or more second search queries to one or more search conductors wherein the one or more search conductors are associated with collections specified in the one or more second search queries; scoring a match of one or more fields of one or more records against the one or more second search queries; adding the one or more records to a results list based on the scoring; continually scoring the one or more records until all records in a partition have been processed; sorting the results list; receiving and collating the results list; performing aggregate analytics processing on the results list wherein the aggregate analytics processing comprises extracting, disambiguating, normalizing, grouping, and indexing a first set of facets from documents wherein the facets comprise different levels of specificity; returning results of the aggregate analytics processing; storing the results in a knowledge base wherein the knowledge base is part of an in-memory database system architecture; loading new documents into an in-memory database; extracting a second set of disambiguated facets from the new documents; and comparing the second set of disambiguated facets with the first set of disambiguated facets wherein the comparing comprises: updating the knowledge base and returning the ID of matching facets; and assigning a unique ID to unmatched facets, associating the unmatched facets with a cluster of defining features, and storing the unmatched facets and the cluster in the knowledge base. 10. The method according to claim 1 , wherein the results list are returned asynchronously.

25. A method for validating the authenticity of an original document from a duplicate document of said original document, said method comprising the steps of: retrieving, by a processor, a duplicate file containing a duplicate document of an original document in an original file having an original format, said duplicate file having a canonical format, said duplicate file further having notary data associated with said original file embedded within said duplicate file; and authenticating, by said processor, said original file using at least said notary data associated with said original file.

25. A method for validating the authenticity of an original document from a duplicate document of said original document, said method comprising the steps of: retrieving, by a processor, a duplicate file containing a duplicate document of an original document in an original file having an original format, said duplicate file having a canonical format, said duplicate file further having notary data associated with said original file embedded within said duplicate file; and authenticating, by said processor, said original file using at least said notary data associated with said original file. 26. The method of claim 25 , wherein said step of authenticating further comprises the steps of: determining said original file from said duplicate file; extracting said notary data associated with said original file from said duplicate file; determining new notary data associated with said original file; and comparing said new notary data with said extracted notary data to authenticate said original file.

33. A method of improving automated recognition of proper nouns spoken by users, comprising: predicting pronunciation of a proper noun in text, based on information associated with the proper noun but not obtained from the text containing the proper noun; and generating a text string that, when pronounced as a word in a first natural language, sounds similar to the proper noun when pronounced in a second natural language selected based on said predicting.

33. A method of improving automated recognition of proper nouns spoken by users, comprising: predicting pronunciation of a proper noun in text, based on information associated with the proper noun but not obtained from the text containing the proper noun; and generating a text string that, when pronounced as a word in a first natural language, sounds similar to the proper noun when pronounced in a second natural language selected based on said predicting. 34. A method as recited in claim 33 , wherein said predicting is based on a country associated with the proper noun.

11. A non-transitory computer-readable storage medium including instructions for performing contextual classification of objects, which, when executed by at least one processor, cause the processor to perform steps comprising: collecting supervised training data from at least one content reviewer, the supervised training data comprising at least one comment and at least one tag specifying whether the at least one comment is abusive; preprocessing the supervised training data to form at least one vectorized object; training a plurality of models by applying a plurality of machine learning algorithms to each vectorized object in parallel; identifying an optimal model from the plurality of models; and filtering at least one abusive comment using the identified optimal model.

11. A non-transitory computer-readable storage medium including instructions for performing contextual classification of objects, which, when executed by at least one processor, cause the processor to perform steps comprising: collecting supervised training data from at least one content reviewer, the supervised training data comprising at least one comment and at least one tag specifying whether the at least one comment is abusive; preprocessing the supervised training data to form at least one vectorized object; training a plurality of models by applying a plurality of machine learning algorithms to each vectorized object in parallel; identifying an optimal model from the plurality of models; and filtering at least one abusive comment using the identified optimal model. 13. The non-transitory computer-readable storage medium of claim 11 , wherein the step of preprocessing the supervised training data comprises performing at least one operation selected from the group consisting of stemming, tokenization, and n-gram analysis.

1. A computer-implemented method for organizing a plurality of pages of an electronic tax document based on a plurality of tax preparation categories, comprising: defining a bookmark profile comprising a plurality of tax preparation categories listed in a predefined bookmark order; defining a first bookmark and a second bookmark, the first bookmark and the second bookmark each containing at least one tax preparation category; associating the first bookmark with a first page of the electronic tax document; associating the second bookmark with a second page of the electronic tax document, the second page subsequent in order to the first page in the electronic tax document; associating the first bookmark with a first plurality of pages corresponding to all pages of the electronic tax document between the first page and the second page; associating the second bookmark with a second plurality of pages corresponding to all pages of the electronic tax document subsequent to the second page; displaying the first bookmark and the second bookmark; and arranging the first and second plurality of pages of the electronic tax document into the predefined bookmark order based on the plurality of tax preparation categories, the predefined bookmark order different than a previous order of the pages of the electronic tax document.

1. A computer-implemented method for organizing a plurality of pages of an electronic tax document based on a plurality of tax preparation categories, comprising: defining a bookmark profile comprising a plurality of tax preparation categories listed in a predefined bookmark order; defining a first bookmark and a second bookmark, the first bookmark and the second bookmark each containing at least one tax preparation category; associating the first bookmark with a first page of the electronic tax document; associating the second bookmark with a second page of the electronic tax document, the second page subsequent in order to the first page in the electronic tax document; associating the first bookmark with a first plurality of pages corresponding to all pages of the electronic tax document between the first page and the second page; associating the second bookmark with a second plurality of pages corresponding to all pages of the electronic tax document subsequent to the second page; displaying the first bookmark and the second bookmark; and arranging the first and second plurality of pages of the electronic tax document into the predefined bookmark order based on the plurality of tax preparation categories, the predefined bookmark order different than a previous order of the pages of the electronic tax document. 8. The method of claim 1 , further comprising: generating a table of contents using a bookmark profile; determining the number of pages of the table of contents; shifting the plurality of pages to accommodate for the table of contents; and inserting the table of contents before the plurality of pages.

12. A device comprising: a database storing a test phrase pair including a test source phrase and a test target phrase; a processor in connection with said database, said processor configured to: receive said test phrase pair including a test source phrase and a test target phrase; determine at least one primary phrase including at least one of a primary source phrase, a primary target phrase, or both, based upon a primary source score, a primary target score, or both, wherein the primary source phrase with the test target phrase comprises a primary source phrase pair that has a score equal to at least the primary source score, and the primary target phrase with the test source phrase comprises a primary target phrase pair that has a score equal to at least the primary target score; compare the at least one primary phrase with the at least one test phrase; and modify a machine translation system based upon the results of the comparison of the at least one primary phrase with the at least one test phrase.

12. A device comprising: a database storing a test phrase pair including a test source phrase and a test target phrase; a processor in connection with said database, said processor configured to: receive said test phrase pair including a test source phrase and a test target phrase; determine at least one primary phrase including at least one of a primary source phrase, a primary target phrase, or both, based upon a primary source score, a primary target score, or both, wherein the primary source phrase with the test target phrase comprises a primary source phrase pair that has a score equal to at least the primary source score, and the primary target phrase with the test source phrase comprises a primary target phrase pair that has a score equal to at least the primary target score; compare the at least one primary phrase with the at least one test phrase; and modify a machine translation system based upon the results of the comparison of the at least one primary phrase with the at least one test phrase. 13. The device of claim 12 , wherein the comparison of the at least one primary phrase with the at least one test phrase comprises a comparison of the primary source phrase with the test source phrase.

1. A method for dynamically detecting topics during one of a speech and a call center conversation, comprising: predefining one or more keywords; associating information with the one or more keywords; detecting at least one of the one or more keywords during the speech or the call center conversation; after the predefining, the associating and detecting, checking whether one or more rules are associated with the one or more detected keywords; if so, processing the one or more rules; and further comprising one of: during the speech, utilizing an intelligent teleprompter and displaying the detected keywords and the information associated with the keywords and dynamically altering one or more panes of information of the intelligent teleprompter based upon the detected one or more keywords; and during the call center conversation, displaying the detected keywords and the information associated with the keywords uttered by a caller to a call center agent and displaying an indication that a topic area has been covered by removing or graying out a displayed word.

1. A method for dynamically detecting topics during one of a speech and a call center conversation, comprising: predefining one or more keywords; associating information with the one or more keywords; detecting at least one of the one or more keywords during the speech or the call center conversation; after the predefining, the associating and detecting, checking whether one or more rules are associated with the one or more detected keywords; if so, processing the one or more rules; and further comprising one of: during the speech, utilizing an intelligent teleprompter and displaying the detected keywords and the information associated with the keywords and dynamically altering one or more panes of information of the intelligent teleprompter based upon the detected one or more keywords; and during the call center conversation, displaying the detected keywords and the information associated with the keywords uttered by a caller to a call center agent and displaying an indication that a topic area has been covered by removing or graying out a displayed word. 4. The method of claim 1 , further comprising monitoring at least any one of a telephone call, an audio input, and a recording as a source of the speech.

1. A method comprising: prompting for first input to identify a plurality of activities and a number of repetitions of each of the activities; for each of the activities, prompting for second input specifying a duration and intensity, and of whether to automatically proceed to a subsequent one of the activities upon determining completion of a previous one of the activities; receiving the first input and the second input; and generating, by a processor, an electronic training script defining a sequence in which to perform the plurality of activities.

1. A method comprising: prompting for first input to identify a plurality of activities and a number of repetitions of each of the activities; for each of the activities, prompting for second input specifying a duration and intensity, and of whether to automatically proceed to a subsequent one of the activities upon determining completion of a previous one of the activities; receiving the first input and the second input; and generating, by a processor, an electronic training script defining a sequence in which to perform the plurality of activities. 4. The method recited in claim 1 , wherein the intensity is an indication of heart rate or pace.

5. A method executed by one or more computers for identifying free-text documents, the method comprising: maintaining a knowledge source storing a plurality of concepts formed based on one or more words in a predefined vocabulary set, the knowledge source maintaining a plurality of relationship links wherein each relationship link defines a relationship between a first semantic grouping of the concepts and a second semantic grouping of the concepts; generating under control of the one or more computers, indexing concepts for the free-text documents stored in a database, the indexing concepts being generated based on one or more words from the predefined vocabulary set, wherein the generating of the indexing concepts includes: maintaining a plurality of data structures mapping each of the plurality of concepts in the knowledge source to all words appearing in the concept; receiving a particular one of the free-text documents; identifying based on the plurality of data structures, one or more of the plurality of concepts in the knowledge source mapped to a set of words appearing in the particular one of the free-text documents; and returning the one or more identified concepts as candidate index concepts for the particular one of the free-text documents; receiving, under control of the one or more computers, an input query including an original query concept and at least one scenario identifier; automatically generating, under control of the one or more computers, an expanded input query including both the original query concept and one or more additional query concepts, the one or more additional query concepts being selected from one or more first particular semantic groupings of the concepts in the knowledge source that have a specific relationship link with a second particular semantic grouping of the concepts containing the original query concept, the specific relationship link being identified by the at least one scenario identifier, wherein the automatically generating of the expanded input query further includes: filtering candidate expansion concepts not included in the one or more first particular semantic groupings of the concepts in the knowledge source; and returning the one or more additional query concepts based on the filtering; accessing the database of free-text documents; comparing the expanded input query with the indexing concepts for the free-text documents; and returning one or more of the free-text documents that satisfy the expanded input query based on the comparison.

5. A method executed by one or more computers for identifying free-text documents, the method comprising: maintaining a knowledge source storing a plurality of concepts formed based on one or more words in a predefined vocabulary set, the knowledge source maintaining a plurality of relationship links wherein each relationship link defines a relationship between a first semantic grouping of the concepts and a second semantic grouping of the concepts; generating under control of the one or more computers, indexing concepts for the free-text documents stored in a database, the indexing concepts being generated based on one or more words from the predefined vocabulary set, wherein the generating of the indexing concepts includes: maintaining a plurality of data structures mapping each of the plurality of concepts in the knowledge source to all words appearing in the concept; receiving a particular one of the free-text documents; identifying based on the plurality of data structures, one or more of the plurality of concepts in the knowledge source mapped to a set of words appearing in the particular one of the free-text documents; and returning the one or more identified concepts as candidate index concepts for the particular one of the free-text documents; receiving, under control of the one or more computers, an input query including an original query concept and at least one scenario identifier; automatically generating, under control of the one or more computers, an expanded input query including both the original query concept and one or more additional query concepts, the one or more additional query concepts being selected from one or more first particular semantic groupings of the concepts in the knowledge source that have a specific relationship link with a second particular semantic grouping of the concepts containing the original query concept, the specific relationship link being identified by the at least one scenario identifier, wherein the automatically generating of the expanded input query further includes: filtering candidate expansion concepts not included in the one or more first particular semantic groupings of the concepts in the knowledge source; and returning the one or more additional query concepts based on the filtering; accessing the database of free-text documents; comparing the expanded input query with the indexing concepts for the free-text documents; and returning one or more of the free-text documents that satisfy the expanded input query based on the comparison. 8. The method of claim 5 , wherein the input query includes a plurality of query concepts, the method further comprising automatically extracting a key query concept from the input query and set the extracted key query concept as the original query concept.

1. A computationally-implemented system, comprising: means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document, wherein said means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item, wherein said means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user that was obtained based, at least in part, on one or more physical characteristics of the first authoring user sensed during or proximate to an action executed in connection with the particular item and performed, at least in part, by the first authoring user; means for acquiring a second inference data indicative of an inferred mental state of a second authoring user in connection with the particular item of the electronic document; means for comparing the first inference data with the second inference data; and means for presenting data indicative of an extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user based, at least in part, on said comparing.

1. A computationally-implemented system, comprising: means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document, wherein said means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item, wherein said means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user that was obtained based, at least in part, on one or more physical characteristics of the first authoring user sensed during or proximate to an action executed in connection with the particular item and performed, at least in part, by the first authoring user; means for acquiring a second inference data indicative of an inferred mental state of a second authoring user in connection with the particular item of the electronic document; means for comparing the first inference data with the second inference data; and means for presenting data indicative of an extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user based, at least in part, on said comparing. 31. The computationally-implemented system of claim 1 , wherein said means for presenting data indicative of an extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user based, at least in part, on said comparing comprises: means for presenting a first icon indicative of an inferred mental state of the first authoring user in proximity with a second icon indicative of an inferred mental state of the second authoring user.

1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification.

1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification. 6. The method of claim 1 wherein determining the at least one topic based on the at least one term further comprises determining the at least one topic based on an ontology.

4. The method of claim 1 , wherein the access differentiating syntax comprises symbols that distinguish between members in the secondary object model.

4. The method of claim 1 , wherein the access differentiating syntax comprises symbols that distinguish between members in the secondary object model. 6. The method of claim 4 , wherein the syntax .@name corresponds to accessing attributes in the secondary object model.

1. A method programmed in a non-transitory memory of a device comprising: a. automatically generating narrative information by analyzing at least one first data source including extracting a first set of data from the at least one first data source and organizing the first set of data from the at least one first data source into a narrative, wherein the first set of data includes a plurality of different perspectives, wherein the plurality of different perspectives are based on a plurality of different languages, further wherein a first perspective of the plurality of perspectives is a first content in a first language, and a second perspective of the plurality of perspectives is a second content in a second language, wherein the first language and the second language are different; b. automatically fact checking, with the device, the narrative information by comparing the narrative information with source information to generate a result, wherein the narrative information includes the first content in the first language and the second content in the second language, wherein fact checking the first content comprises fact checking using sources in the second language translated into the first language, and fact checking the second content translated into the first language comprises fact checking using sources in the first language; and c. automatically providing a status of the narrative information in real-time based on the result of the comparison of the narrative information with the source information.

1. A method programmed in a non-transitory memory of a device comprising: a. automatically generating narrative information by analyzing at least one first data source including extracting a first set of data from the at least one first data source and organizing the first set of data from the at least one first data source into a narrative, wherein the first set of data includes a plurality of different perspectives, wherein the plurality of different perspectives are based on a plurality of different languages, further wherein a first perspective of the plurality of perspectives is a first content in a first language, and a second perspective of the plurality of perspectives is a second content in a second language, wherein the first language and the second language are different; b. automatically fact checking, with the device, the narrative information by comparing the narrative information with source information to generate a result, wherein the narrative information includes the first content in the first language and the second content in the second language, wherein fact checking the first content comprises fact checking using sources in the second language translated into the first language, and fact checking the second content translated into the first language comprises fact checking using sources in the first language; and c. automatically providing a status of the narrative information in real-time based on the result of the comparison of the narrative information with the source information. 7. The method of claim 1 further comprising summarizing the source information using lexical chaining to generate summarized source information, and using the summarized source information for a preliminary comparison of the narrative information with the source information, and then using full source information corresponding to the summarized source information for the comparison to generate the result.

157. A method of indexing and searching timed media files, as recited in claim 150 , wherein said virtual documents are displayed.

157. A method of indexing and searching timed media files, as recited in claim 150 , wherein said virtual documents are displayed. 158. A method of indexing and searching timed media files, as recited in claim 157 , wherein said display of said virtual documents includes playing the said collection of relevance intervals back-to-back.

1. A method comprising: generating a sequence of tokens, each token being an integer representation of a respective sequence of characters that is included in a style sheet, each token corresponding to a respective character position that indicates a position of that token in the style sheet; identifying a designated token in the sequence of tokens that includes a user-initiated change, the designated token following a first subset of the tokens in the sequence of tokens and preceding a second subset of the tokens in the sequence of tokens; determining whether the user-initiated change is identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens; and determining whether the second subset of the tokens is to be re-tokenized, including: determining that the second subset of the tokens is not to be re-tokenized if the user-initiated change is identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens, but determining that the second subset of the tokens is to be re-tokenized if the user-initiated change is not identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens.

1. A method comprising: generating a sequence of tokens, each token being an integer representation of a respective sequence of characters that is included in a style sheet, each token corresponding to a respective character position that indicates a position of that token in the style sheet; identifying a designated token in the sequence of tokens that includes a user-initiated change, the designated token following a first subset of the tokens in the sequence of tokens and preceding a second subset of the tokens in the sequence of tokens; determining whether the user-initiated change is identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens; and determining whether the second subset of the tokens is to be re-tokenized, including: determining that the second subset of the tokens is not to be re-tokenized if the user-initiated change is identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens, but determining that the second subset of the tokens is to be re-tokenized if the user-initiated change is not identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens. 9. The method of claim 1 , further comprising: assigning a plurality of specified subsets of the tokens that are included in the sequence of tokens to a plurality of respective hierarchical node trees, each hierarchical node tree defined by a plurality of hierarchical levels that includes a plurality of respective subsets of a plurality of nodes among which the tokens in the respective specified subset are included, each node in the plurality of nodes having a respective character position that indicates a position of that node in the style sheet.

8. A computer program product for identifying code changes, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, wherein the one or more computer-readable storage media are not transitory signals, the program instructions comprising: program instructions to retrieve a first changeset that is associated with a program based, at least in part, on a search parameter that includes a range of time and a first area of interest that indicates a first portion of a source code of the program; program instructions to identify a first set of changes included in the first changeset based on a time stamp of a change, wherein a time of the time stamp is included within the range of time, and wherein first set of changes includes a change to a region of the source code that is included in the first area of interest, the computer determining whether the change included in the first set of changes is a textual change or a syntactical change to the region of the source code, based on textual matching, and syntactical matching, wherein syntactical matching includes a comparison of a first valid syntax of the first set of changes to a second valid syntax of the region of the source code of the program that corresponds to the first set of changes, and wherein the comparison reveals that a syntax of the source code of the program was changed by the first set of changes from second valid syntax to the first valid syntax; program instructions to generate a second area of interest that includes a second portion of the source code of the program by updating the first area of interest based, at least in part, on i) the change being a textual change or a syntactical change and ii) an inverse of an operation included in the change, such that the second area of interest includes a third portion of source code that is not indicated by the first area of interest; program instructions to search for a second set of changes based, at least in part, on the second area of interest; program instructions to identify a possible source of an error based, at least in part, on a result of an analysis of a syntax of the second set of changes; and program instructions to generate a result that includes, at least in part, the second set of changes and an indication of the possible source of the error.

8. A computer program product for identifying code changes, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, wherein the one or more computer-readable storage media are not transitory signals, the program instructions comprising: program instructions to retrieve a first changeset that is associated with a program based, at least in part, on a search parameter that includes a range of time and a first area of interest that indicates a first portion of a source code of the program; program instructions to identify a first set of changes included in the first changeset based on a time stamp of a change, wherein a time of the time stamp is included within the range of time, and wherein first set of changes includes a change to a region of the source code that is included in the first area of interest, the computer determining whether the change included in the first set of changes is a textual change or a syntactical change to the region of the source code, based on textual matching, and syntactical matching, wherein syntactical matching includes a comparison of a first valid syntax of the first set of changes to a second valid syntax of the region of the source code of the program that corresponds to the first set of changes, and wherein the comparison reveals that a syntax of the source code of the program was changed by the first set of changes from second valid syntax to the first valid syntax; program instructions to generate a second area of interest that includes a second portion of the source code of the program by updating the first area of interest based, at least in part, on i) the change being a textual change or a syntactical change and ii) an inverse of an operation included in the change, such that the second area of interest includes a third portion of source code that is not indicated by the first area of interest; program instructions to search for a second set of changes based, at least in part, on the second area of interest; program instructions to identify a possible source of an error based, at least in part, on a result of an analysis of a syntax of the second set of changes; and program instructions to generate a result that includes, at least in part, the second set of changes and an indication of the possible source of the error. 10. The computer program product of claim 8 , wherein one or both of the first set of changes and the second set of changes include changes that have been made to a program.

15. A computer system for enabling a user to select one or more items from a plurality of items, comprising: a processor; a storage system for storing the plurality of items; and a display having a user interface controlled by the processor for enabling the user to access the plurality of items in the storage system, the user interface presenting the user with one or more selectable mood identifiers for selection by the user, wherein each selectable mood identifier among the one or more selectable mood identifiers includes a first range of intensities of at least one mood and enabling the user to select a first point within the first range, the processor automatically generating a first span around the first point, the first span including a first subrange of additional points within at least the first range on at least one side of the first point, in response to the user selection, the processor searching the plurality of items in the storage system, each item among the plurality of items having been assigned one or more pre-determined mood identifiers by an entity other than the user, wherein each pre-determined mood identifier among the one or more pre-determined mood identifiers includes a second span representing a set of additional points within at least a second range of intensities of at least one mood, as a result of the searching, the processor generating a list of items corresponding to the one or more items where the order of the list of items is based on a level of correspondence between the at least the first span of one or more selectable mood identifiers selected by the user and at least the second span of the pre-determined mood identifiers assigned to the items, and the processor presenting to the user through the user interface the list of items.

15. A computer system for enabling a user to select one or more items from a plurality of items, comprising: a processor; a storage system for storing the plurality of items; and a display having a user interface controlled by the processor for enabling the user to access the plurality of items in the storage system, the user interface presenting the user with one or more selectable mood identifiers for selection by the user, wherein each selectable mood identifier among the one or more selectable mood identifiers includes a first range of intensities of at least one mood and enabling the user to select a first point within the first range, the processor automatically generating a first span around the first point, the first span including a first subrange of additional points within at least the first range on at least one side of the first point, in response to the user selection, the processor searching the plurality of items in the storage system, each item among the plurality of items having been assigned one or more pre-determined mood identifiers by an entity other than the user, wherein each pre-determined mood identifier among the one or more pre-determined mood identifiers includes a second span representing a set of additional points within at least a second range of intensities of at least one mood, as a result of the searching, the processor generating a list of items corresponding to the one or more items where the order of the list of items is based on a level of correspondence between the at least the first span of one or more selectable mood identifiers selected by the user and at least the second span of the pre-determined mood identifiers assigned to the items, and the processor presenting to the user through the user interface the list of items. 19. The computer system as recited in claim 15 , wherein the plurality of items are representations of items within an inventory.

1. A computer automated method for identifying an unknown language used to create a document, including the steps of: defining a set of training documents in a variety of known languages and formed from a variety of text styles; forming black and white pixel images of text material defining said training documents and said document in said unknown language; locating a plurality of seed black pixels from a region growing algorithm; progressively locating black pixels having a selected relationship with said seed pixels to define a plurality of line stroke segments that connect to form a line stroke; identifying black pixels to define a head and a tail black pixel for each said line stroke; extracting point features from said line stroke segments, where the point features include a vertical position and slope of individual line stroke segments, and locally-averaged radius of curvature that are effective to characterize each of said languages; forming feature profiles from said point features for an unknown language and each of said known languages; and comparing said feature profile from said unknown language with each of said feature profiles from said known languages to identify one of said known languages that best represents said unknown language.

1. A computer automated method for identifying an unknown language used to create a document, including the steps of: defining a set of training documents in a variety of known languages and formed from a variety of text styles; forming black and white pixel images of text material defining said training documents and said document in said unknown language; locating a plurality of seed black pixels from a region growing algorithm; progressively locating black pixels having a selected relationship with said seed pixels to define a plurality of line stroke segments that connect to form a line stroke; identifying black pixels to define a head and a tail black pixel for each said line stroke; extracting point features from said line stroke segments, where the point features include a vertical position and slope of individual line stroke segments, and locally-averaged radius of curvature that are effective to characterize each of said languages; forming feature profiles from said point features for an unknown language and each of said known languages; and comparing said feature profile from said unknown language with each of said feature profiles from said known languages to identify one of said known languages that best represents said unknown language. 2. A method according to claim 1, wherein said step of comparing said feature profile from said unknown language with said feature profiles from said known language further includes the steps of: generating from said feature profiles of a number of samples of each said known language a mean profile and a covariance matrix as a measure of profile variability for that language; determining a Mahalanobis distance between said profile for a document in said unknown language and said mean profile for each said known language; and selecting said known language having a minimum said Mahalanobis distance to best represent said unknown language.

1. A method comprising: determining to store a spatial document index for a corpus of documents, wherein the spatial document index indexes documents in the corpus according to spatial references found within the documents; determining to store a plurality of spatial keyword document indexes for the corpus of documents, wherein the spatial keyword document indexes are derived from the spatial document index, are for a different keyword, and indexes those documents among the corpus that are responsive to that keyword; and intersecting a portion of the spatial document index and selected indexes among the plurality of spatial keyword document indexes to identify a result set of those documents from among the corpus of documents that are responsive to a query.

1. A method comprising: determining to store a spatial document index for a corpus of documents, wherein the spatial document index indexes documents in the corpus according to spatial references found within the documents; determining to store a plurality of spatial keyword document indexes for the corpus of documents, wherein the spatial keyword document indexes are derived from the spatial document index, are for a different keyword, and indexes those documents among the corpus that are responsive to that keyword; and intersecting a portion of the spatial document index and selected indexes among the plurality of spatial keyword document indexes to identify a result set of those documents from among the corpus of documents that are responsive to a query. 14. The method of claim 1 , wherein at least one of the plurality of spatial keyword document indexes is for only a single corresponding keyword.

25. A method of managing attributes, comprising: maintaining, at a data store, an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with one or more multi-valued attributes, said request is associated with a preferred language; determining, at the access management system, whether the preferred language of the request matches an installed language at the access management system; in response to the preferred language not matching the installed language, performing an approximate language match based at least in part on a language code associated with the preferred language; providing a plurality of multi-valued attributes in a single entry at the data store, wherein said single entry contains all available values for said multi-valued attributes, said plurality of multi-valued attributes comprising a first multi-valued attribute that includes a plurality of values, said plurality of values are indexed using a language component provided as part of each of said plurality of values, each of said plurality of values includes a value for said attribute corresponding to an associated language component; retrieving from the single entry at the data store said plurality of multi-valued attributes; and generating a response to a request associated with said first one multi-valued attribute, said request is associated with the preferred language, said response includes at least one first value for said first multi-valued attribute that corresponds to said preferred language.

25. A method of managing attributes, comprising: maintaining, at a data store, an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with one or more multi-valued attributes, said request is associated with a preferred language; determining, at the access management system, whether the preferred language of the request matches an installed language at the access management system; in response to the preferred language not matching the installed language, performing an approximate language match based at least in part on a language code associated with the preferred language; providing a plurality of multi-valued attributes in a single entry at the data store, wherein said single entry contains all available values for said multi-valued attributes, said plurality of multi-valued attributes comprising a first multi-valued attribute that includes a plurality of values, said plurality of values are indexed using a language component provided as part of each of said plurality of values, each of said plurality of values includes a value for said attribute corresponding to an associated language component; retrieving from the single entry at the data store said plurality of multi-valued attributes; and generating a response to a request associated with said first one multi-valued attribute, said request is associated with the preferred language, said response includes at least one first value for said first multi-valued attribute that corresponds to said preferred language. 26. The method of claim 25 , wherein: said single entry is an identity profile maintained at said data store; said request is a request to view or modify said identity profile; and said response includes said at least one first value for said first multi-valued attribute in a representation of at least a portion of said identity profile.

11. A method for monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the method comprising: setting up and maintaining a synchronous computer-mediated communication system between a plurality of chat participants; checking for potential frustration including checking the text transcript for use of a text-based signal in a list of text-based signals; and taking a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a text analytics analysis on the text transcript; wherein: at least the checking step is performed by computer software running on computer hardware; the responsive action is designed to alleviate frustration of the second chat participant; the list of text-based signals is recorded in a user-specific dictionary being customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific dictionary being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant.

11. A method for monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the method comprising: setting up and maintaining a synchronous computer-mediated communication system between a plurality of chat participants; checking for potential frustration including checking the text transcript for use of a text-based signal in a list of text-based signals; and taking a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a text analytics analysis on the text transcript; wherein: at least the checking step is performed by computer software running on computer hardware; the responsive action is designed to alleviate frustration of the second chat participant; the list of text-based signals is recorded in a user-specific dictionary being customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific dictionary being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant. 13. The method of claim 11 further comprising: on condition that a secondary keyword is found in the text transcript, determining that potential frustration is evidenced by the text transcript.

7. A computer program product for managing concurrent editing in a collaborative editing environment, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on at least one of the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to receive an input to edit an electronic document from a first editor through a first user interface; program instructions to track a cursor within the electronic document associated with the first user interface; program instructions to lock content of the electronic document within a proximity of the cursor associated with the first user interface to prevent access to the content of the electronic document within the proximity of the cursor by one or more second editors, wherein scope of the proximity and a length of a delay associated with the cursor are based, at least in part, on one or more dynamic rules, wherein the scope of the proximity of the cursor and the length of the delay are based, at least in part, on a nested relationship of content of the electronic document, wherein a length of the delay at a word-level is greater than a length of the delay at a sentence-level, and the length of the delay at a sentence-level is greater than a length of the delay at a paragraph-level; and program instructions to, responsive to the cursor moving to a new location within the electronic document, unlock the content no longer in the proximity of the cursor.

7. A computer program product for managing concurrent editing in a collaborative editing environment, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on at least one of the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to receive an input to edit an electronic document from a first editor through a first user interface; program instructions to track a cursor within the electronic document associated with the first user interface; program instructions to lock content of the electronic document within a proximity of the cursor associated with the first user interface to prevent access to the content of the electronic document within the proximity of the cursor by one or more second editors, wherein scope of the proximity and a length of a delay associated with the cursor are based, at least in part, on one or more dynamic rules, wherein the scope of the proximity of the cursor and the length of the delay are based, at least in part, on a nested relationship of content of the electronic document, wherein a length of the delay at a word-level is greater than a length of the delay at a sentence-level, and the length of the delay at a sentence-level is greater than a length of the delay at a paragraph-level; and program instructions to, responsive to the cursor moving to a new location within the electronic document, unlock the content no longer in the proximity of the cursor. 9. The program product of claim 7 , wherein the unlocking the content of the electronic document occurs after a first delay associated with the cursor if the first delay has not elapsed before the content is unlocked due to the content being no longer in the proximity of the cursor associated with the first editor.

5. The method of claim 1 , further comprising: obtaining tile entry point offsets associated with the picture of the input video bitstream, a title entry point offset indicating start of a tile in the picture of the input video bitstream.

5. The method of claim 1 , further comprising: obtaining tile entry point offsets associated with the picture of the input video bitstream, a title entry point offset indicating start of a tile in the picture of the input video bitstream. 6. The method of claim 5 , wherein obtaining tile entry point offsets associated with the picture comprises: parsing tile headers of the tiles of the picture, wherein the tile header of a tile contains the tile entry point offset of the tile.

1. A computer-implemented method for intuitively applying scratch-out gestures in a computing device that comprises a handwriting surface component that receives electronic ink from a digitizer, as well as a component that provides boundary information corresponding to boundaries of words or characters and a scratch-out gesture detector coupled to the handwriting surface component and the component that provides the boundary information, wherein the scratch-out gesture detector also evaluates electronic ink received at the handwriting surface against criteria based on the boundary information to determine whether the electronic ink corresponds to any of a plurality of different acceptable scratch-out gesture types, the method comprising: the scratch-out gesture detector associating a plurality of different acceptable types of scratch-out gestures with a scratch-out gesture process that erases previously-entered ink; the computing device receiving user input corresponding to inking data entered via a digitizer at a handwriting surface component of the computing device; the scratch-out gesture detector evaluating the inking data based on boundary threshold data of at least one corresponding word or character displayed by the computing device to determine whether the user input is a scratch-out gesture corresponding to at least one of the plurality of different acceptable types of scratch-out gesture types and that would cause the scratch-out process to erase previously-entered ink; and wherein a) if the inking data is a scratch-out gesture, erasing previously-entered ink corresponding to the scratch-out gesture, as well as the inking data corresponding to the scratch-out gesture; and b) if the inking data is not a scratch-out gesture, processing the inking data as ink stroke data of at least part of a word or character.

1. A computer-implemented method for intuitively applying scratch-out gestures in a computing device that comprises a handwriting surface component that receives electronic ink from a digitizer, as well as a component that provides boundary information corresponding to boundaries of words or characters and a scratch-out gesture detector coupled to the handwriting surface component and the component that provides the boundary information, wherein the scratch-out gesture detector also evaluates electronic ink received at the handwriting surface against criteria based on the boundary information to determine whether the electronic ink corresponds to any of a plurality of different acceptable scratch-out gesture types, the method comprising: the scratch-out gesture detector associating a plurality of different acceptable types of scratch-out gestures with a scratch-out gesture process that erases previously-entered ink; the computing device receiving user input corresponding to inking data entered via a digitizer at a handwriting surface component of the computing device; the scratch-out gesture detector evaluating the inking data based on boundary threshold data of at least one corresponding word or character displayed by the computing device to determine whether the user input is a scratch-out gesture corresponding to at least one of the plurality of different acceptable types of scratch-out gesture types and that would cause the scratch-out process to erase previously-entered ink; and wherein a) if the inking data is a scratch-out gesture, erasing previously-entered ink corresponding to the scratch-out gesture, as well as the inking data corresponding to the scratch-out gesture; and b) if the inking data is not a scratch-out gesture, processing the inking data as ink stroke data of at least part of a word or character. 8. The method of claim 1 wherein the gesture comprises at least one additional separate gesture stroke, and wherein evaluating the inking data comprises evaluating a first stroke of the gesture to determine whether the inking data is a scratch-out gesture, and if so, processing each additional stroke of the gesture as part of the first stroke of the gesture, including erasing each additional stroke.

13. A method for receiving and processing search queries and presenting search results to users, the method comprising: a) receiving a query comprising terms representing a patent claim search; b) using a search engine to retrieve from a database a first set of patent information, each item of the first set of patent information comprising one or more claims responsive to the query, wherein the query comprises a plurality of query permutations derived from the original query language and comprising either or both of a claim text-based query permutation and a key concept-based query permutation, and wherein the search engine is adapted to execute a plurality of query search permutations in arriving at the first set of patent information; c) re-ranking the entire first set of patent information based on a set of patent features to generate a re-ranked set of patent information without reducing the number of candidate patent documents in the set, the re-ranking module being adapted to weight the set of patent features based on a set of features including at least one classification feature related to a subject matter of the claim, and wherein the set of patent features comprises one or more from a group consisting of: fields of a patent; patent title; patent abstract; patent IPC code; patent references; patent claims; rank-c, representing a lowest rank of any claim of a patent in the first set of candidate patent documents; sim(c,c), representing a highest similarity score between the query and claims in a patent in the first set of candidate patent documents; sim(c,cs), representing a similarity score between the query and all the claims of a patent in the first set of candidate patent documents; sim(c,title), representing a similarity score between the query and the title of a patent in the first set of candidate patent documents; sim(c,abstract), representing a similarity score between the query and the abstract of a patent in the first set of candidate patent documents; sim(key,key), representing a similarity score between key concepts of the query and a patent in the first set of candidate patent documents; sim(key,title), representing a similarity score between the key concept of the query and the title of a patent in the first set of candidate patent documents; sim(key,abstract), representing a similarity score between the key concept of the query and the abstract of a patent in the first set of candidate patent documents; IPC-overlap, representing a number of overlapping IPC codes between IPC codes of a patent in the first set of candidate patent documents and the IPC codes of an initial high-ranking set of patents in the first set of candidate patent documents; and direct-Cite, representing the number of patents in the initial high-ranking set of patent documents that cite or are cited by a patent in the first set of candidate patent documents; and d) generating for display an ordered set of information derived from the re-ranked set of patent information responsive to the query.

13. A method for receiving and processing search queries and presenting search results to users, the method comprising: a) receiving a query comprising terms representing a patent claim search; b) using a search engine to retrieve from a database a first set of patent information, each item of the first set of patent information comprising one or more claims responsive to the query, wherein the query comprises a plurality of query permutations derived from the original query language and comprising either or both of a claim text-based query permutation and a key concept-based query permutation, and wherein the search engine is adapted to execute a plurality of query search permutations in arriving at the first set of patent information; c) re-ranking the entire first set of patent information based on a set of patent features to generate a re-ranked set of patent information without reducing the number of candidate patent documents in the set, the re-ranking module being adapted to weight the set of patent features based on a set of features including at least one classification feature related to a subject matter of the claim, and wherein the set of patent features comprises one or more from a group consisting of: fields of a patent; patent title; patent abstract; patent IPC code; patent references; patent claims; rank-c, representing a lowest rank of any claim of a patent in the first set of candidate patent documents; sim(c,c), representing a highest similarity score between the query and claims in a patent in the first set of candidate patent documents; sim(c,cs), representing a similarity score between the query and all the claims of a patent in the first set of candidate patent documents; sim(c,title), representing a similarity score between the query and the title of a patent in the first set of candidate patent documents; sim(c,abstract), representing a similarity score between the query and the abstract of a patent in the first set of candidate patent documents; sim(key,key), representing a similarity score between key concepts of the query and a patent in the first set of candidate patent documents; sim(key,title), representing a similarity score between the key concept of the query and the title of a patent in the first set of candidate patent documents; sim(key,abstract), representing a similarity score between the key concept of the query and the abstract of a patent in the first set of candidate patent documents; IPC-overlap, representing a number of overlapping IPC codes between IPC codes of a patent in the first set of candidate patent documents and the IPC codes of an initial high-ranking set of patents in the first set of candidate patent documents; and direct-Cite, representing the number of patents in the initial high-ranking set of patent documents that cite or are cited by a patent in the first set of candidate patent documents; and d) generating for display an ordered set of information derived from the re-ranked set of patent information responsive to the query. 15. The method of claim 13 wherein the ordered set of information generated for display comprises patent claims responsive to the query.

1. A method for providing an interactive knowledge based community solution, the community comprising multiple users, each of the multiple users belonging to a user type, the user types comprising participant, mentor, and subject matter expert, the method comprising the steps of: (a) associating a user profile with at least one of the multiple users; (b) matching a participant user with a mentor user based on user profiles of the participant user and the mentor user; (c) matching a participant user with at least one subject matter expert user based on the user profile of the participant user including at least one of an industry identifier and an occupation identifier, and based on the user profile of the at least one subject matter expert user including at least one of an industry identifier and an occupation identifier; and (d) providing a computerized terminal interface for allowing at least one user to interact with at least one other user; wherein the computerized terminal interface displays personalized content to each participant user, and the displayed personalized content is selected on the basis of at least one of (i) a match between the participant user and a mentor user, and (ii) a match between the participant user and at least one subject matter expert user; and wherein each mentor user and subject matter expert user differs from one another.

1. A method for providing an interactive knowledge based community solution, the community comprising multiple users, each of the multiple users belonging to a user type, the user types comprising participant, mentor, and subject matter expert, the method comprising the steps of: (a) associating a user profile with at least one of the multiple users; (b) matching a participant user with a mentor user based on user profiles of the participant user and the mentor user; (c) matching a participant user with at least one subject matter expert user based on the user profile of the participant user including at least one of an industry identifier and an occupation identifier, and based on the user profile of the at least one subject matter expert user including at least one of an industry identifier and an occupation identifier; and (d) providing a computerized terminal interface for allowing at least one user to interact with at least one other user; wherein the computerized terminal interface displays personalized content to each participant user, and the displayed personalized content is selected on the basis of at least one of (i) a match between the participant user and a mentor user, and (ii) a match between the participant user and at least one subject matter expert user; and wherein each mentor user and subject matter expert user differs from one another. 15. The method of claim 1 , wherein the interface allows virtual collaboration between multiple users.

18. The medium of claim 17 , further encoded with instructions that, when executed by a processor, perform at least: determine a transportation mode, wherein determining the location candidate is based, at least in part, on the transportation mode.

18. The medium of claim 17 , further encoded with instructions that, when executed by a processor, perform at least: determine a transportation mode, wherein determining the location candidate is based, at least in part, on the transportation mode. 19. The medium of claim 18 , wherein determining the location candidate comprises: determining a navigational attribute type based, at least in part, on correlating the navigational attribute type and the transportation mode; identifying a navigational attribute of the navigational attribute type; and determining the location candidate comprising textual information indicative of the navigational attribute.

8. A computer program product for locating a genome pattern, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, wherein the computer readable program code, when executed by a processor of a computer, is configured to perform: creating one or more lexical annotators that each identify a sequence of nucleotides of nucleotide bases selected from A, C, G, and T; providing (1) the one or more lexical annotators, (2) one or more dictionary entries, (3) one or more previously-defined parsing rule annotators, and (4) one or more characters that each represent a nucleotide; creating a parsing rule annotator that identifies an order of and a combination of at least two elements selected from (1) the one or more lexical annotators and (2) the one or more dictionary entries, (3) the one or more previously-defined parsing rule annotators, and (4) the one or more characters that each represent a nucleotide; and creating an Unstructured Information Management Architecture (UIMA) pipeline to locate the genome pattern using the parsing rule annotator by: in a first stage of the UIMA pipeline, parsing a genetic sequence that is found in a Common Analysis Structure (CAS) to determine a language used and to generate tokens that are added to the CAS with a start position and an end position for each of the tokens; in a second stage of the UIMA pipeline, executing the one or more lexical annotators against the genetic sequence to identify one or more lexical annotations that are added to the CAS with a start position and an end position for each of the one or more lexical annotations; and in a third stage of the UIMA pipeline, using the start position and the end position for each of the tokens and the start position and the end position for each of the one or more lexical annotations to identify a match to the parsing rule annotation and to form a new annotation that is added to the CAS.

8. A computer program product for locating a genome pattern, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, wherein the computer readable program code, when executed by a processor of a computer, is configured to perform: creating one or more lexical annotators that each identify a sequence of nucleotides of nucleotide bases selected from A, C, G, and T; providing (1) the one or more lexical annotators, (2) one or more dictionary entries, (3) one or more previously-defined parsing rule annotators, and (4) one or more characters that each represent a nucleotide; creating a parsing rule annotator that identifies an order of and a combination of at least two elements selected from (1) the one or more lexical annotators and (2) the one or more dictionary entries, (3) the one or more previously-defined parsing rule annotators, and (4) the one or more characters that each represent a nucleotide; and creating an Unstructured Information Management Architecture (UIMA) pipeline to locate the genome pattern using the parsing rule annotator by: in a first stage of the UIMA pipeline, parsing a genetic sequence that is found in a Common Analysis Structure (CAS) to determine a language used and to generate tokens that are added to the CAS with a start position and an end position for each of the tokens; in a second stage of the UIMA pipeline, executing the one or more lexical annotators against the genetic sequence to identify one or more lexical annotations that are added to the CAS with a start position and an end position for each of the one or more lexical annotations; and in a third stage of the UIMA pipeline, using the start position and the end position for each of the tokens and the start position and the end position for each of the one or more lexical annotations to identify a match to the parsing rule annotation and to form a new annotation that is added to the CAS. 9. The computer program product of claim 8 , wherein the parsing rule annotator includes lexical annotators and no previously-defined parsing rule annotators.

1. A system for testing of control devices, the system comprising: a computer memory that stores a testing grammar that describes a set of test cases for a device under test, wherein the testing grammar comprises one or more tags including at least one of a terminal symbol and a non-terminal symbol; and a processor that: identifies one or more tags within the testing grammar; determines at least one of a number of a set of test cases that would be generated based on the one or more tags within the testing grammar and a description of the set of test cases that would be generated based on the one or more tags within the testing grammar without generating the set of test cases from the testing grammar; responsive to the determination of the at least one of the number and the description of the set of test cases, modifies at least one tag in the testing grammar based on the identified at least one of the number and the description of the set of test cases; and generates a set of test cases for the device under test using the modified at least one tag in the testing grammar.

1. A system for testing of control devices, the system comprising: a computer memory that stores a testing grammar that describes a set of test cases for a device under test, wherein the testing grammar comprises one or more tags including at least one of a terminal symbol and a non-terminal symbol; and a processor that: identifies one or more tags within the testing grammar; determines at least one of a number of a set of test cases that would be generated based on the one or more tags within the testing grammar and a description of the set of test cases that would be generated based on the one or more tags within the testing grammar without generating the set of test cases from the testing grammar; responsive to the determination of the at least one of the number and the description of the set of test cases, modifies at least one tag in the testing grammar based on the identified at least one of the number and the description of the set of test cases; and generates a set of test cases for the device under test using the modified at least one tag in the testing grammar. 4. The system as recited in claim 1 , wherein the processor determines at least one of the number and the description of the set of test cases by searching the grammar and identifying each instance of a terminal symbol.

15. An article comprising: a non-transitory machine-readable medium comprising instructions stored thereon which, in response to being executed by a special purpose computing apparatus, direct the special purpose computing apparatus to: for data from a first domain, the first domain data having a plurality of original labels, generate a first plurality of signals using a hypothesis function for a second domain, the hypothesis function determined by using a plurality of labels that are associated with data from a second domain, the first plurality of signals representative of a plurality of first predicted labels for the first domain data; apply a label relation function to the first plurality of signals representative of the first predicted labels for the first domain data and the original labels for the first domain data to generate a second plurality of signals, the second plurality of signals representative of a plurality of weighting factors for the first domain data; generate a new hypothesis function for the second domain using the second domain data, the first domain data, and the weighting factors for the first domain data; evaluate a performance of the new hypothesis function for the second domain to determine if there is a convergence; for data from the second domain, the second domain data having a plurality of original labels, generate a third plurality of signals using a hypothesis function for the first domain, the hypothesis function determined by using a plurality of labels that are associated with data from the first domain, the third plurality of signals representative of a plurality of first predicted labels for the second domain data; apply another label relation function to the first predicted labels for the second domain data and the original labels for the second domain data to determine a plurality of weighting factors for the second domain data; generate a new hypothesis function for the first domain using the first domain data, the second domain data, and the weighting factors for the second domain data; and evaluate a performance of the new hypothesis function for the first domain to determine if there is a convergence.

15. An article comprising: a non-transitory machine-readable medium comprising instructions stored thereon which, in response to being executed by a special purpose computing apparatus, direct the special purpose computing apparatus to: for data from a first domain, the first domain data having a plurality of original labels, generate a first plurality of signals using a hypothesis function for a second domain, the hypothesis function determined by using a plurality of labels that are associated with data from a second domain, the first plurality of signals representative of a plurality of first predicted labels for the first domain data; apply a label relation function to the first plurality of signals representative of the first predicted labels for the first domain data and the original labels for the first domain data to generate a second plurality of signals, the second plurality of signals representative of a plurality of weighting factors for the first domain data; generate a new hypothesis function for the second domain using the second domain data, the first domain data, and the weighting factors for the first domain data; evaluate a performance of the new hypothesis function for the second domain to determine if there is a convergence; for data from the second domain, the second domain data having a plurality of original labels, generate a third plurality of signals using a hypothesis function for the first domain, the hypothesis function determined by using a plurality of labels that are associated with data from the first domain, the third plurality of signals representative of a plurality of first predicted labels for the second domain data; apply another label relation function to the first predicted labels for the second domain data and the original labels for the second domain data to determine a plurality of weighting factors for the second domain data; generate a new hypothesis function for the first domain using the first domain data, the second domain data, and the weighting factors for the second domain data; and evaluate a performance of the new hypothesis function for the first domain to determine if there is a convergence. 19. The article of claim 15 , the instructions stored thereon which, in response to being executed by the special purpose computing apparatus, further direct the special purpose computing apparatus to generate a fourth plurality of signals using the new hypothesis function for the first domain, the fourth plurality of signals representative of a plurality of second predicted labels for the second domain data.

23. A searchable knowledge base for a plurality of items in a choice set, each of said items having an associated set of attributes including at least one subjective attribute, comprising: at least a processor; at least a computer readable medium, coupled to the Internet; a bus that interconnects said at east a processor and said at least a computer readable storage; and a computer program embodied on said at least a computer readable medium, said computer program comprising: instructions for harvesting information relevant to each of said items and a source of said harvested information from the Internet; instructions for extracting a set of normalized representations from a corresponding set of statements in one or more texts of said harvested information; instructions for analyzing the normalized representations to derive a set of scores for each attribute in said associated set of attributes for each of said items; instructions for aggregating said derived scores, for said each attribute in said associated set of attributes, by assigning a weight to each of the scores based on at least the source of the one or more texts; and instructions for incorporating attributes in said associated set of attributes and their corresponding aggregated scores, for each of said items, into said searchable knowledge base for said choice set, wherein a computer processor is utilized to automatically perform each of said instructions, the incorporating including: annotating a first statement harvested for a first item of the plurality of items with a first set of attributes and a corresponding first set of scores to generate a first annotation, the first set of attributes associated with the first item and determined based on an analysis of text in the first statement, the first statement being one of multiple statements harvested for the first item, the first annotation being one of multiple annotations in the searchable knowledge base, the first annotation including a link to the first statement, and indexing the annotations in the searchable knowledge base to facilitate retrieval of a statement of the statements that corresponds to an input attribute.

23. A searchable knowledge base for a plurality of items in a choice set, each of said items having an associated set of attributes including at least one subjective attribute, comprising: at least a processor; at least a computer readable medium, coupled to the Internet; a bus that interconnects said at east a processor and said at least a computer readable storage; and a computer program embodied on said at least a computer readable medium, said computer program comprising: instructions for harvesting information relevant to each of said items and a source of said harvested information from the Internet; instructions for extracting a set of normalized representations from a corresponding set of statements in one or more texts of said harvested information; instructions for analyzing the normalized representations to derive a set of scores for each attribute in said associated set of attributes for each of said items; instructions for aggregating said derived scores, for said each attribute in said associated set of attributes, by assigning a weight to each of the scores based on at least the source of the one or more texts; and instructions for incorporating attributes in said associated set of attributes and their corresponding aggregated scores, for each of said items, into said searchable knowledge base for said choice set, wherein a computer processor is utilized to automatically perform each of said instructions, the incorporating including: annotating a first statement harvested for a first item of the plurality of items with a first set of attributes and a corresponding first set of scores to generate a first annotation, the first set of attributes associated with the first item and determined based on an analysis of text in the first statement, the first statement being one of multiple statements harvested for the first item, the first annotation being one of multiple annotations in the searchable knowledge base, the first annotation including a link to the first statement, and indexing the annotations in the searchable knowledge base to facilitate retrieval of a statement of the statements that corresponds to an input attribute. 28. A searchable knowledge base as recited in claim 23 , wherein said instructions for extracting comprises instructions for applying a predefined set of rules.

2. The apparatus of claim 1 wherein the dialog comprises part of a telephone conversation between the caller and the automated dialog system.

2. The apparatus of claim 1 wherein the dialog comprises part of a telephone conversation between the caller and the automated dialog system. 4. The apparatus of claim 2 wherein the agent is compelled to intervene upon the occurrence of a defined event detected by the call monitoring module, the defined event comprising the potential problem.

1. A method comprising: receiving, with one or more computing devices, information from heterogeneous data sources, the information including a value automatically generated by a measuring device associated with a first user; parsing by the one or more computing devices the information to identify a keyword corresponding to a category of subject matter of the first user and the value; categorizing by the one or more computing devices the information based at least in part on the keyword; automatically identifying by the one or more computing devices a rule being set by the first user for scheduling a new appointment, the rule specifying a third party service provider and specifying whether to schedule the new appointment with the third party service provider based on the parsed value; responsive to receiving, parsing and categorizing the information, determining, with the one or more computing devices, whether the information satisfies the rule for scheduling the new appointment; determining by the one or more computing devices whether the information is matching with an already scheduled appointment in one of a plurality of calendars of the first user; responsive to the information satisfying the rule for scheduling the new appointment and the information is not matching with the already scheduled appointment, automatically transmitting a message to schedule the new appointment with the third party service provider; and generating by the one or more computing devices a calendar item for the new appointment in the one of the plurality of calendars of the first user, the one of the plurality of calendars corresponding to the category of subject matter of the first user.

1. A method comprising: receiving, with one or more computing devices, information from heterogeneous data sources, the information including a value automatically generated by a measuring device associated with a first user; parsing by the one or more computing devices the information to identify a keyword corresponding to a category of subject matter of the first user and the value; categorizing by the one or more computing devices the information based at least in part on the keyword; automatically identifying by the one or more computing devices a rule being set by the first user for scheduling a new appointment, the rule specifying a third party service provider and specifying whether to schedule the new appointment with the third party service provider based on the parsed value; responsive to receiving, parsing and categorizing the information, determining, with the one or more computing devices, whether the information satisfies the rule for scheduling the new appointment; determining by the one or more computing devices whether the information is matching with an already scheduled appointment in one of a plurality of calendars of the first user; responsive to the information satisfying the rule for scheduling the new appointment and the information is not matching with the already scheduled appointment, automatically transmitting a message to schedule the new appointment with the third party service provider; and generating by the one or more computing devices a calendar item for the new appointment in the one of the plurality of calendars of the first user, the one of the plurality of calendars corresponding to the category of subject matter of the first user. 4. The method of claim 1 , wherein the information includes the social graph and the new appointment is made if the first user is closely related to other people included in the information.

1. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: generating a plurality of syntactic annotation tokens based upon a plurality of syntactic relationships between a plurality of terms included in a source document; creating a knowledge structure that includes the plurality of terms in a plurality of original text fields and includes the plurality of syntactic annotation tokens in a plurality of parallel fields, wherein each of the plurality of syntactic annotation tokens align to at least one of the plurality of original text fields; and generating one or more question-based syntactic annotation tokens corresponding to a question; and utilizing the knowledge structure in a question answer system to generate one or more answers to the question, wherein the question answer system matches at least one of the one or more question-based syntactic annotation tokens to at least one of the plurality of syntactic annotation tokens during the generation of at least one of the one or more answers.

1. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: generating a plurality of syntactic annotation tokens based upon a plurality of syntactic relationships between a plurality of terms included in a source document; creating a knowledge structure that includes the plurality of terms in a plurality of original text fields and includes the plurality of syntactic annotation tokens in a plurality of parallel fields, wherein each of the plurality of syntactic annotation tokens align to at least one of the plurality of original text fields; and generating one or more question-based syntactic annotation tokens corresponding to a question; and utilizing the knowledge structure in a question answer system to generate one or more answers to the question, wherein the question answer system matches at least one of the one or more question-based syntactic annotation tokens to at least one of the plurality of syntactic annotation tokens during the generation of at least one of the one or more answers. 4. The information handling system of claim 1 wherein, during the generation of the knowledge structure, at least one of the one or more processors perform additional actions comprising: matching a selected one of the plurality of terms to an abstract concept entry, wherein the abstract concept entry includes the selected term and a different term; for each of the plurality of syntactic annotation tokens that include the selected term, creating an abstract syntactic annotation token that replaces the selected term with the different term, resulting in one or more abstract syntactic annotation tokens; and including one or more abstract syntactic annotation tokens in the knowledge structure.

38. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least two non-signature information fields; analyzing, using the computer system, a correlation of information between two or more of the non-signature information fields, wherein the analysis of a first non-signature information field of the document is dependent on what information is in a second non-signature information field of the document; and comparing, using the computer system, writing in the first non-signature information field of the document to information from a corresponding non-signature information field of at least one other document, wherein the comparison is based on the correlation analysis between the first non-signature information field and the second non-signature information field.

38. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least two non-signature information fields; analyzing, using the computer system, a correlation of information between two or more of the non-signature information fields, wherein the analysis of a first non-signature information field of the document is dependent on what information is in a second non-signature information field of the document; and comparing, using the computer system, writing in the first non-signature information field of the document to information from a corresponding non-signature information field of at least one other document, wherein the comparison is based on the correlation analysis between the first non-signature information field and the second non-signature information field. 43. The method of claim 38 , wherein analyzing the correlation of information between two or more non-signature information fields comprises reading information from at least one cross-correlation table.

1. A computer-implemented method of customizing language modeling components, comprising: displaying a list of language modeling components; receiving a selection of one or more language modeling components from the list; receiving selection of a fixed weight value for the selected one or more of the language modeling components; generating information based on the selection, wherein the information indicates the selected one or more of the language modeling components based on one or more domains and the selected value for the selected one or more of the language modeling components; sending the information to a service provider; and receiving from the service provider a customized combination of the selected language modeling components based on the information.

1. A computer-implemented method of customizing language modeling components, comprising: displaying a list of language modeling components; receiving a selection of one or more language modeling components from the list; receiving selection of a fixed weight value for the selected one or more of the language modeling components; generating information based on the selection, wherein the information indicates the selected one or more of the language modeling components based on one or more domains and the selected value for the selected one or more of the language modeling components; sending the information to a service provider; and receiving from the service provider a customized combination of the selected language modeling components based on the information. 3. The method of claim 1 , wherein the information further includes a selection of a pre-compiled language model based on the one or more domains.

9. A system comprising: an inference component configured to determine a transportation mode for one or more segments of positioning data based at least in part on one or more features of the one or more segments.

9. A system comprising: an inference component configured to determine a transportation mode for one or more segments of positioning data based at least in part on one or more features of the one or more segments. 10. The system of claim 9 , comprising: a segmentation component configured to separate GPS data into the one or more segments of positioning data; and a feature extraction component configured to extract the one or more features for the one or more segments of positioning data.

6. A non-transitory computer-readable storage medium bearing instructions that, when executed by a computer, cause the computer to perform the following steps: obtaining a command phrase specifying an operation, a protocol, and an object, wherein the command phrase is in a natural language based syntax; obtaining one or more parameters associated with the command phrase; determining that one or more additional parameters are associated with the command phrase; obtaining the one or more additional parameters from a database translating the command phrase, the one or more parameters, and the one or more additional parameters into an XML command; transmitting the XML command to the registry; obtaining a response from the registry; and determining that the response corresponds to an anticipated response; wherein the one or mere parameters comprise a variable.

6. A non-transitory computer-readable storage medium bearing instructions that, when executed by a computer, cause the computer to perform the following steps: obtaining a command phrase specifying an operation, a protocol, and an object, wherein the command phrase is in a natural language based syntax; obtaining one or more parameters associated with the command phrase; determining that one or more additional parameters are associated with the command phrase; obtaining the one or more additional parameters from a database translating the command phrase, the one or more parameters, and the one or more additional parameters into an XML command; transmitting the XML command to the registry; obtaining a response from the registry; and determining that the response corresponds to an anticipated response; wherein the one or mere parameters comprise a variable. 7. The non-transitory storage medium of claim 6 , wherein the protocol comprises at least one of registry registrar protocol and extensible provisioning protocol.

8. A computer system comprising: a processing unit coupled to a memory, the memory storing computer-executable instructions for causing the processing unit to: provide a browser-based integrated development environment that is implemented at least in part using a dynamic language; receive input from a user in a form of at least a portion of a code command, the code command implemented at least in part using a dynamic language; use introspection of the browser-based integrated development environment that is implemented at least in part using a dynamic language to dynamically generate a list of one or more possible code command completion suggestions that are suitable completions for the input received from the user, wherein at least a portion of the code command completion suggestions are generated from searching a plurality of available commands for one or more suitable completions to the code command input by the user, wherein introspection is performed against one or more available classes and global variables implemented using the dynamic language in the integrated development environment; and provide at least a portion of the list of possible code command completion suggestions.

8. A computer system comprising: a processing unit coupled to a memory, the memory storing computer-executable instructions for causing the processing unit to: provide a browser-based integrated development environment that is implemented at least in part using a dynamic language; receive input from a user in a form of at least a portion of a code command, the code command implemented at least in part using a dynamic language; use introspection of the browser-based integrated development environment that is implemented at least in part using a dynamic language to dynamically generate a list of one or more possible code command completion suggestions that are suitable completions for the input received from the user, wherein at least a portion of the code command completion suggestions are generated from searching a plurality of available commands for one or more suitable completions to the code command input by the user, wherein introspection is performed against one or more available classes and global variables implemented using the dynamic language in the integrated development environment; and provide at least a portion of the list of possible code command completion suggestions. 10. The computer system of claim 8 , wherein at least a portion of the available commands are system-defined.

1. A method for multimedia model retrieval, comprising: acquiring parameters of a first multimedia model to be retrieved; performing a projection on the first multimedia model according to the parameters of the first multimedia model so as to obtain a projection image; performing a feature extraction on the projection image to generate a first feature extraction result; comparing the first feature extraction result with a plurality of feature extraction results corresponding to a plurality of multimedia models stored in a database so as to obtain a retrieval result, wherein the retrieval result comprises a number of multimedia models; labeling by a user each of the multimedia models in the retrieval result with a probability value; training a support vector machine with the labeled multimedia models; performing a probability-based classification on the plurality of multimedia models stored in the database by using the support vector machine to obtain a classification result; and updating the retrieval result with the classification result.

1. A method for multimedia model retrieval, comprising: acquiring parameters of a first multimedia model to be retrieved; performing a projection on the first multimedia model according to the parameters of the first multimedia model so as to obtain a projection image; performing a feature extraction on the projection image to generate a first feature extraction result; comparing the first feature extraction result with a plurality of feature extraction results corresponding to a plurality of multimedia models stored in a database so as to obtain a retrieval result, wherein the retrieval result comprises a number of multimedia models; labeling by a user each of the multimedia models in the retrieval result with a probability value; training a support vector machine with the labeled multimedia models; performing a probability-based classification on the plurality of multimedia models stored in the database by using the support vector machine to obtain a classification result; and updating the retrieval result with the classification result. 3. The method according to claim 1 , further comprising: performing a pre-processing on the parameters of the first multimedia model to be retrieved.

1. A computer program product for storing a representation of a digital document, including first means for storing the digital document, the digital document having descriptive markup defining a plurality of hierarchical elements, wherein each element except a root element has an ancestor element and wherein each element has a type name and wherein an element may have a child element, a left sibling element, a right sibling element, and wherein at least one element contains text content, the computer program product comprising: a computer readable media having computer program logic stored thereon, wherein the computer program logic defines: second means for storing a value indicative of a parent element for each element having a parent element; third means for storing a value indicative of a first child element for each element having a child element; and fourth means for storing a value indicative of a left sibling element, for each element having a left sibling element.

1. A computer program product for storing a representation of a digital document, including first means for storing the digital document, the digital document having descriptive markup defining a plurality of hierarchical elements, wherein each element except a root element has an ancestor element and wherein each element has a type name and wherein an element may have a child element, a left sibling element, a right sibling element, and wherein at least one element contains text content, the computer program product comprising: a computer readable media having computer program logic stored thereon, wherein the computer program logic defines: second means for storing a value indicative of a parent element for each element having a parent element; third means for storing a value indicative of a first child element for each element having a child element; and fourth means for storing a value indicative of a left sibling element, for each element having a left sibling element. 2. The computer program product as set forth in claim 1, wherein the computer program logic farther defines: fifth means for storing the text content of the digital document; for each element containing text content, sixth means for storing a value indicative of the location of the text content in the fifth means for storing the text content; and seventh means for storing, for each element, the type name of the mark up element.

1. A computer implemented method of operating a wagering game system in real time, comprising the steps of: establishing a communication link using network infrastructure between a plurality of gaming devices and a central recommender processor, wherein each gaming device is operated by a player having a wagering game system registration, and wherein each gaming device is programmed to carry out game functions of receiving wagering and game instructions, determining a game outcome and determining an award; generating a gaming and play behavior model by partitioning stored play data into a plurality of game session patterns, each game session pattern corresponds to a time period and indicates occurrence of game factors over the time period; detecting, at the recommender processor, in real time or near real time that a current player begins to play a game or indicates a desire to play the game using a first gaming device of the plurality of gaming devices; collecting, by the recommender processor from the first gaming device using the communication link, at the moment of the detection that the current player begins to play the game or indicates the desire to play the game, a first set of real time game data defining occurrence of game factors for game play in an ongoing live game; determining, by the recommender processor, that the first set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour using the plurality of game session patterns; matching, by the recommender processor, the first set of real time game data to a first set of game session patterns of the plurality of game session patterns; determining, by the recommender processor, at least one game player type from among a set of predefined game player types for the current game player based on the first set of game session patterns; and transmitting from the recommender processor to the first gaming device using the communication link, a selection of games identified for the determined at least one game player type.

1. A computer implemented method of operating a wagering game system in real time, comprising the steps of: establishing a communication link using network infrastructure between a plurality of gaming devices and a central recommender processor, wherein each gaming device is operated by a player having a wagering game system registration, and wherein each gaming device is programmed to carry out game functions of receiving wagering and game instructions, determining a game outcome and determining an award; generating a gaming and play behavior model by partitioning stored play data into a plurality of game session patterns, each game session pattern corresponds to a time period and indicates occurrence of game factors over the time period; detecting, at the recommender processor, in real time or near real time that a current player begins to play a game or indicates a desire to play the game using a first gaming device of the plurality of gaming devices; collecting, by the recommender processor from the first gaming device using the communication link, at the moment of the detection that the current player begins to play the game or indicates the desire to play the game, a first set of real time game data defining occurrence of game factors for game play in an ongoing live game; determining, by the recommender processor, that the first set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour using the plurality of game session patterns; matching, by the recommender processor, the first set of real time game data to a first set of game session patterns of the plurality of game session patterns; determining, by the recommender processor, at least one game player type from among a set of predefined game player types for the current game player based on the first set of game session patterns; and transmitting from the recommender processor to the first gaming device using the communication link, a selection of games identified for the determined at least one game player type. 4. The method of claim 1 , wherein the step of generating the gaming and play behavior model comprises: detecting trends within the plurality of game session patterns.

1. A method comprising: receiving, at a first computing device, a search request from a second computing device of a user, the search request for images associated with a textual query; determining, by the first computing device and based at least in part on the received textual query, multiple images that are associated with the received textual query; determining, by the first computing device, a first keyword that is associated with a first set of the multiple images and determining, by the first computing device, a second keyword that is associated with a second set of the multiple images; clustering, by the first computing device, the first set of the multiple images into two or more clusters and clustering, by the first computing device, the second set of the multiple images into two or more clusters; determining, by the first computing device: (i) an image from the first cluster of the first set of the multiple images that is representative of the first cluster of the first set of the multiple images; (ii) an image from the second cluster of the first set of the multiple images that is representative of the second cluster of the first set of the multiple images; (iii) an image from the first cluster of the second set of the multiple images that is representative of the first cluster of the second set of the multiple images, and (iv) an image from the second cluster of the second set of the multiple images that is representative of the second cluster of the second set of the multiple images; providing the first keyword and the second keyword and the respective representative images of the first and the second clusters of the first set and the respective representative images of the first and the second clusters of the second set, to the second computing device of the user, in a suggestion to refine the search request based at least on the first keyword or the second keyword and based at least on one of the respective representative images; and responsive to receiving a selection of one of the first keyword or the second keyword and a selection of one of the respective representative images, refining the search request based at least on the selected keyword and based at least on the selected representative image.

1. A method comprising: receiving, at a first computing device, a search request from a second computing device of a user, the search request for images associated with a textual query; determining, by the first computing device and based at least in part on the received textual query, multiple images that are associated with the received textual query; determining, by the first computing device, a first keyword that is associated with a first set of the multiple images and determining, by the first computing device, a second keyword that is associated with a second set of the multiple images; clustering, by the first computing device, the first set of the multiple images into two or more clusters and clustering, by the first computing device, the second set of the multiple images into two or more clusters; determining, by the first computing device: (i) an image from the first cluster of the first set of the multiple images that is representative of the first cluster of the first set of the multiple images; (ii) an image from the second cluster of the first set of the multiple images that is representative of the second cluster of the first set of the multiple images; (iii) an image from the first cluster of the second set of the multiple images that is representative of the first cluster of the second set of the multiple images, and (iv) an image from the second cluster of the second set of the multiple images that is representative of the second cluster of the second set of the multiple images; providing the first keyword and the second keyword and the respective representative images of the first and the second clusters of the first set and the respective representative images of the first and the second clusters of the second set, to the second computing device of the user, in a suggestion to refine the search request based at least on the first keyword or the second keyword and based at least on one of the respective representative images; and responsive to receiving a selection of one of the first keyword or the second keyword and a selection of one of the respective representative images, refining the search request based at least on the selected keyword and based at least on the selected representative image. 3. The method as recited in claim 1 , wherein determining the first keyword and the second keyword further comprises analyzing a query log that stores previous queries.

8. At least one tangible non-transitory computer-readable storage medium having encoded thereon computer instructions that, when executed, perform a method for providing a statistical initial topic classification model for use in a natural language call routing application to map a natural language user statement to at least one of a plurality of topics in the natural language call routing application, the method comprising acts of: accessing a voice user interface (VUI) specification that specifies a VUI for allowing users to interact with the natural language call routing application, the VUI specification comprising a plurality of expressions of possible user intentions composed by at least one VUI designer, the VUI specification further comprising, for each one of the plurality of expressions of possible user intentions, at least one system response or action defined by the at least one VUI designer as corresponding to the one of the plurality of expressions of possible user intentions; analyzing the VUI specification to determine a plurality of topic descriptions, each one of the plurality of topic descriptions describing a meaning of a corresponding one of the plurality of topics; and using, as training data, the plurality of topic descriptions determined by analyzing the VUI specification to build the statistical initial topic classification model, comprising; identifying keywords in the plurality of topic descriptions used as training data to build the statistical initial topic classification model; providing an optimal feature set comprising at least one combination of at least some of the keywords; and using at least one computer to build the statistical initial topic classification model based at least partially on the optimal feature set.

8. At least one tangible non-transitory computer-readable storage medium having encoded thereon computer instructions that, when executed, perform a method for providing a statistical initial topic classification model for use in a natural language call routing application to map a natural language user statement to at least one of a plurality of topics in the natural language call routing application, the method comprising acts of: accessing a voice user interface (VUI) specification that specifies a VUI for allowing users to interact with the natural language call routing application, the VUI specification comprising a plurality of expressions of possible user intentions composed by at least one VUI designer, the VUI specification further comprising, for each one of the plurality of expressions of possible user intentions, at least one system response or action defined by the at least one VUI designer as corresponding to the one of the plurality of expressions of possible user intentions; analyzing the VUI specification to determine a plurality of topic descriptions, each one of the plurality of topic descriptions describing a meaning of a corresponding one of the plurality of topics; and using, as training data, the plurality of topic descriptions determined by analyzing the VUI specification to build the statistical initial topic classification model, comprising; identifying keywords in the plurality of topic descriptions used as training data to build the statistical initial topic classification model; providing an optimal feature set comprising at least one combination of at least some of the keywords; and using at least one computer to build the statistical initial topic classification model based at least partially on the optimal feature set. 22. The at least one tangible non-transitory computer-readable storage medium of claim 8 , wherein accessing the VUI specification comprises obtaining the VUI specification from the at least one VUI designer.

1. A method for implementing a geographic search mode in connection with a search engine, the method comprising: indexing geographic locations for resources available to the search engine in a search engine index; determining a target location from one or more keywords in a query string submitted by a user to a search engine; identifying the target location as a geographic city; determining two or more alternative location cities within a pre-defined geographic radius around the geographic city with at least a minimum population of people; suggesting that a user limit a search for at least one of the one or more keywords to the two or more alternative cities; presenting a drop-down menu with the two or more alternative location cities arranged in alphabetic order; receiving an indication, by the user, to limit the search for the at least one of the one or more keywords one of the two or more alternative cities; searching web content for information relevant to the at least one of the one or more keywords and limited to the one of the two or more alternative cities; and transmitting the information.

1. A method for implementing a geographic search mode in connection with a search engine, the method comprising: indexing geographic locations for resources available to the search engine in a search engine index; determining a target location from one or more keywords in a query string submitted by a user to a search engine; identifying the target location as a geographic city; determining two or more alternative location cities within a pre-defined geographic radius around the geographic city with at least a minimum population of people; suggesting that a user limit a search for at least one of the one or more keywords to the two or more alternative cities; presenting a drop-down menu with the two or more alternative location cities arranged in alphabetic order; receiving an indication, by the user, to limit the search for the at least one of the one or more keywords one of the two or more alternative cities; searching web content for information relevant to the at least one of the one or more keywords and limited to the one of the two or more alternative cities; and transmitting the information. 3. The method of claim 1 , further comprising determining the target location by examining stored information pertaining to user settings.

5. A system comprising: a first microphone to detect a first sound; a second microphone to detect a second sound; memory; one or more processors; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising: determining that the first sound is representative of at least a portion of a target voice; determining that the second sound is representative of at least a portion of noise; implementing a delay with respect to a first audio signal that represents the noise and refraining from delaying a second audio signal that represents the target voice; terminating the delay based at least in part on detecting the noise; processing, by a first adaptive filter, the target voice to generate a target voice estimate, the target voice estimate representing a first estimate of the target voice of a user associated with the first sound; processing, by the first adaptive filter, the noise to generate a noise estimate, the noise estimate representing a second estimate of the noise within an environment associated with the user; and generating, by a second adaptive filter different from the first adaptive filter, an enhanced target voice based at least in part on the target voice estimate and the noise estimate.

5. A system comprising: a first microphone to detect a first sound; a second microphone to detect a second sound; memory; one or more processors; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising: determining that the first sound is representative of at least a portion of a target voice; determining that the second sound is representative of at least a portion of noise; implementing a delay with respect to a first audio signal that represents the noise and refraining from delaying a second audio signal that represents the target voice; terminating the delay based at least in part on detecting the noise; processing, by a first adaptive filter, the target voice to generate a target voice estimate, the target voice estimate representing a first estimate of the target voice of a user associated with the first sound; processing, by the first adaptive filter, the noise to generate a noise estimate, the noise estimate representing a second estimate of the noise within an environment associated with the user; and generating, by a second adaptive filter different from the first adaptive filter, an enhanced target voice based at least in part on the target voice estimate and the noise estimate. 11. The system as recited in claim 5 , wherein the operations further comprise determining the enhanced target voice based at least in part on a suppression of the noise.

1. A method of multi-device video communication, the method comprising: receiving recorded content from a multi-device video communication session; processing the recorded content to detect vocal expressions from a plurality of participants in the multi-device video communication session; generating a plurality of text elements each corresponding to one or more of the vocal expressions; receiving at least one rating for at least one participant of the plurality of participants; and generating a word cloud based on the plurality of text elements and at least in part on the at least one rating for the at least one participant.

1. A method of multi-device video communication, the method comprising: receiving recorded content from a multi-device video communication session; processing the recorded content to detect vocal expressions from a plurality of participants in the multi-device video communication session; generating a plurality of text elements each corresponding to one or more of the vocal expressions; receiving at least one rating for at least one participant of the plurality of participants; and generating a word cloud based on the plurality of text elements and at least in part on the at least one rating for the at least one participant. 9. The method in claim 1 wherein a first rating is received from a first participant of the plurality of participants and the first rating represents an assessment of the importance of a second participant of the plurality of participants.

1. A method comprising: receiving, with an authentication device, authentication information from an endpoint device; authenticating, with the authentication device, the endpoint device based on the authentication information; based on the authentication, storing, with the authentication device, authorization information in accordance with a first proprietary authorization data model; applying, with the authentication device, an export translation policy to translate the authorization information stored in accordance the first proprietary authorization data model into translated authorization information that complies with a second Interface for Metadata Access Point (IF-MAP) authorization data model conforming to an IF-MAP standard, wherein the second IF-MAP authorization data model is different from the first proprietary authorization data model; and publishing, with the authentication device, the translated authorization information in accordance with an IF-MAP protocol to an intermediate storage device that implements the second IF-MAP authorization data model.

1. A method comprising: receiving, with an authentication device, authentication information from an endpoint device; authenticating, with the authentication device, the endpoint device based on the authentication information; based on the authentication, storing, with the authentication device, authorization information in accordance with a first proprietary authorization data model; applying, with the authentication device, an export translation policy to translate the authorization information stored in accordance the first proprietary authorization data model into translated authorization information that complies with a second Interface for Metadata Access Point (IF-MAP) authorization data model conforming to an IF-MAP standard, wherein the second IF-MAP authorization data model is different from the first proprietary authorization data model; and publishing, with the authentication device, the translated authorization information in accordance with an IF-MAP protocol to an intermediate storage device that implements the second IF-MAP authorization data model. 6. The method of claim 1 , wherein the authentication device comprises a Remote Access Dial In User Service (RADIUS) server.

15. The process of claim 3 further comprising the steps: C) controlling a computer to display diagrams and textual interactive dialogs and process and store requirements data entered using said diagrams and textual interactive dialogs so as to perform the functions recited herein, said diagrams and textual interactive dialogs being tools which a designer of said computer program uses to enter requirements data that define the meta-model building blocks or elements which comprise an Object Model, a Dynamic Model, a Functional Model and a Presentation Model which together comprise the Conceptual Model which fully specifies the desired structure, behavior and user interface of said computer program, said Conceptual Model being the entity from which said validated Formal Specification is generated; D) storing in said memory of said computer said requirements data entered using said diagrams and textual interactive dialogs and using said computer to automatically convert said requirements data, as it is entered, into elements of a formal specification language and storing all said elements automatically created from items of requirements data as said Formal Specification, said Formal Specification being written in a formal specification language having rules of syntax and semantics that define a grammar; E) controlling a computer to use said rules of syntax and semantics to validate said Formal Specification to ensure it is correct and complete so as to generate said validated Formal Specification.

15. The process of claim 3 further comprising the steps: C) controlling a computer to display diagrams and textual interactive dialogs and process and store requirements data entered using said diagrams and textual interactive dialogs so as to perform the functions recited herein, said diagrams and textual interactive dialogs being tools which a designer of said computer program uses to enter requirements data that define the meta-model building blocks or elements which comprise an Object Model, a Dynamic Model, a Functional Model and a Presentation Model which together comprise the Conceptual Model which fully specifies the desired structure, behavior and user interface of said computer program, said Conceptual Model being the entity from which said validated Formal Specification is generated; D) storing in said memory of said computer said requirements data entered using said diagrams and textual interactive dialogs and using said computer to automatically convert said requirements data, as it is entered, into elements of a formal specification language and storing all said elements automatically created from items of requirements data as said Formal Specification, said Formal Specification being written in a formal specification language having rules of syntax and semantics that define a grammar; E) controlling a computer to use said rules of syntax and semantics to validate said Formal Specification to ensure it is correct and complete so as to generate said validated Formal Specification. 16. The process of claim 15 wherein said diagrams and textual interactive dialogs receive and process requirements data entered by said designer defining an Object Model, a Dynamic Model, a Functional Model and a Presentation Model which can include definitions of classes, relationships between classes, global interactions, global functions and views, and wherein said diagrams and textual interactive dialogs receive and process requirements data as part of said Object Model, Dynamic Model, Functional Model and Presentation Model, said diagrams and textual interactive dialogs enabling entry of requirements data defining: attributes; services; derivations; constraints; transaction formulas; triggers; display sets; filters; population selection patterns; a state transition diagram; formal interfaces; a name.

2. The drive support apparatus for a movable body according to claim 1 , wherein the movable body is an automobile.

2. The drive support apparatus for a movable body according to claim 1 , wherein the movable body is an automobile. 7. The drive support apparatus for a movable body according to claim 2 , wherein the awareness denotes a level of awareness of the driver respectively with respect to at least two evaluation items selected from the group consisting of four evaluation items of a speed limit, an inter-vehicle distance, a timing for operating a direction indicator, and a deceleration at a time of passing a curve or an intersection; corresponding to the evaluation items, the driving state detecting portion acquires driving state information of at least two from the speed limit of the movable body, the inter-vehicle distance from a movable body ahead, the timing for operating a direction indicator, and the deceleration at the time of passing a curve or an intersection, from the sensor of the movable body; and once plural evaluation items satisfy simultaneously the interaction-start conditions, the interaction controlling portion generates a question for checking the awareness with respect to an evaluation item for which the driver's awareness has been determined as the lowest.

11. A system for inferring problem data from bug repositories, the system comprising: a memory comprising a knowledge base configured to store phrases that are mapped to classes of an ontology; and a computing device coupled to the memory, the computing device comprising one or more processors, a query engine coupled to the knowledge base, and a program interface, wherein, upon execution of the one or more processors, the program interface is configured to: obtain a bug report; identify a plurality of phrases that are repeated in the bug report; select a first phrase from the plurality of phrases to keep and a second phrase from the plurality of phrases to drop based on a meaning of the first phrase being greater in significance in the bug report than a meaning of the second phrase; map the first phrase to a class of an ontology model having a plurality of classes associated with the bug report, the ontology model defining valid interactions between the plurality of classes; determine whether the first phrase corresponds to a valid interaction defined by the ontology model; and based on determining the first phrase corresponds to a valid interaction defined by the ontology model, generate an output corresponding to the mapping for use in analyzing the bug report.

11. A system for inferring problem data from bug repositories, the system comprising: a memory comprising a knowledge base configured to store phrases that are mapped to classes of an ontology; and a computing device coupled to the memory, the computing device comprising one or more processors, a query engine coupled to the knowledge base, and a program interface, wherein, upon execution of the one or more processors, the program interface is configured to: obtain a bug report; identify a plurality of phrases that are repeated in the bug report; select a first phrase from the plurality of phrases to keep and a second phrase from the plurality of phrases to drop based on a meaning of the first phrase being greater in significance in the bug report than a meaning of the second phrase; map the first phrase to a class of an ontology model having a plurality of classes associated with the bug report, the ontology model defining valid interactions between the plurality of classes; determine whether the first phrase corresponds to a valid interaction defined by the ontology model; and based on determining the first phrase corresponds to a valid interaction defined by the ontology model, generate an output corresponding to the mapping for use in analyzing the bug report. 14. The system of claim 11 , wherein the retrieved information comprises at least one of a problem concept, an activity concept, an action concept, a series of steps taken to arrive at a solution, or a conversation contained within the bug report.

8. A system comprising: a data store for storing data; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: receiving a series of queries provided from a user device, the series of queries comprising two or more queries; determining a query pattern of the series of queries based on one or more entities and one or more aspects associated with the two or more queries, the determining comprising: for each query in the series of queries: determining a set of entities comprising one or more entities and described in the query, and determining a set of aspects comprising one or more aspects and described in the query; comparing sets of entities across queries in the series of queries; comparing sets of aspects across queries in the series of queries; determining that at least one of a set of aspects are consistent in each of the queries or a set of entities are consistent in each of the queries; and determining that the at least one of a set of aspects that are consistent in each of the queries or a set of entities that are consistent in each of the queries is a context of the queries, and that the context defines the query pattern; determining, at least partially based on the context defining the query pattern, that a teachable moment interface is to be displayed with search results on the user device; and transmitting content to be displayed in the teachable moment interface on a user device, the content including instructions to a user that instructs the user that the user need not include the content that defines the query pattern in queries that are subsequent to the series of queries.

8. A system comprising: a data store for storing data; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: receiving a series of queries provided from a user device, the series of queries comprising two or more queries; determining a query pattern of the series of queries based on one or more entities and one or more aspects associated with the two or more queries, the determining comprising: for each query in the series of queries: determining a set of entities comprising one or more entities and described in the query, and determining a set of aspects comprising one or more aspects and described in the query; comparing sets of entities across queries in the series of queries; comparing sets of aspects across queries in the series of queries; determining that at least one of a set of aspects are consistent in each of the queries or a set of entities are consistent in each of the queries; and determining that the at least one of a set of aspects that are consistent in each of the queries or a set of entities that are consistent in each of the queries is a context of the queries, and that the context defines the query pattern; determining, at least partially based on the context defining the query pattern, that a teachable moment interface is to be displayed with search results on the user device; and transmitting content to be displayed in the teachable moment interface on a user device, the content including instructions to a user that instructs the user that the user need not include the content that defines the query pattern in queries that are subsequent to the series of queries. 13. The system of claim 8 , wherein the content suggests one or more queries for improved interaction between the user and a search system, to which the two or more queries are submitted.

1. A method of generating an application accessible by a user through one or more computer-based devices, the method comprising the steps of: representing interactions that the user is permitted to have with the one or more computer-based devices used to access the application by interaction-based programming components, wherein the interaction-based programming components are independent of content/application logic and presentation requirements associated with the application, and further wherein the interaction-based programming components may be transcoded on a component by component basis to generate one or more modality-specific renderings of the application renderable in accordance with one or more modality-specific browsers associated with the one or more computer-based devices, such that the interaction-based programming components are independent of any modality and any modality-specific browser; and authoring the application using at least a portion of the interaction-based programming components; wherein representation by the interaction-based programming components permits synchronization of the one or more modality-specific renderings of the application on the one or more computer-based devices.

1. A method of generating an application accessible by a user through one or more computer-based devices, the method comprising the steps of: representing interactions that the user is permitted to have with the one or more computer-based devices used to access the application by interaction-based programming components, wherein the interaction-based programming components are independent of content/application logic and presentation requirements associated with the application, and further wherein the interaction-based programming components may be transcoded on a component by component basis to generate one or more modality-specific renderings of the application renderable in accordance with one or more modality-specific browsers associated with the one or more computer-based devices, such that the interaction-based programming components are independent of any modality and any modality-specific browser; and authoring the application using at least a portion of the interaction-based programming components; wherein representation by the interaction-based programming components permits synchronization of the one or more modality-specific renderings of the application on the one or more computer-based devices. 4. The method of claim 1 , wherein the one or more modality-specific renderings comprise a speech-based representation of portions of the application.

51. A non-transitory computer-readable medium whose stored contents configure a computing device to perform a method, the method comprising: receiving information at an electronic marketplace from multiple executing programs of multiple task requesters that indicates multiple tasks available to be performed by multiple human task performers who have registered with the electronic marketplace as being able to perform tasks, the information being received via a programmatic interface of the electronic marketplace and indicating multiple available tasks that each has one or more associated required qualifications for a human performer of the task and has associated compensation for performance of the task, the electronic marketplace being provided by one or more configured computing systems to facilitate task performance transactions involving the task requesters and the human task performers; for each of at least some of the available tasks, identifying one or more human task performers who have indicated to the electronic marketplace to be available to perform tasks and are otherwise unaffiliated with the electronic marketplace and who each have one or more qualifications that satisfy the required qualifications for the task, and providing information about the task to the identified one or more human task performers to enable each of the identified one or more human task performers to select whether to participate in a transaction that involves the identified human task performer performing the task for a task requester in exchange for the associated compensation for the task, the identifying of the one or more human task performers for each of the at least some available tasks being performed by the one or more configured computing systems; and for each of one or more of the at least some available tasks, after receiving results for the available task based on performance of the task by one or more of the identified human task performers for the task, and without further human intervention, supplying the received results via the programmatic interface to an executing program of the task requester from whose program the information about the task was received, and facilitating providing of the associated compensation for the task to those one or more human task performers on behalf of that task requester.

51. A non-transitory computer-readable medium whose stored contents configure a computing device to perform a method, the method comprising: receiving information at an electronic marketplace from multiple executing programs of multiple task requesters that indicates multiple tasks available to be performed by multiple human task performers who have registered with the electronic marketplace as being able to perform tasks, the information being received via a programmatic interface of the electronic marketplace and indicating multiple available tasks that each has one or more associated required qualifications for a human performer of the task and has associated compensation for performance of the task, the electronic marketplace being provided by one or more configured computing systems to facilitate task performance transactions involving the task requesters and the human task performers; for each of at least some of the available tasks, identifying one or more human task performers who have indicated to the electronic marketplace to be available to perform tasks and are otherwise unaffiliated with the electronic marketplace and who each have one or more qualifications that satisfy the required qualifications for the task, and providing information about the task to the identified one or more human task performers to enable each of the identified one or more human task performers to select whether to participate in a transaction that involves the identified human task performer performing the task for a task requester in exchange for the associated compensation for the task, the identifying of the one or more human task performers for each of the at least some available tasks being performed by the one or more configured computing systems; and for each of one or more of the at least some available tasks, after receiving results for the available task based on performance of the task by one or more of the identified human task performers for the task, and without further human intervention, supplying the received results via the programmatic interface to an executing program of the task requester from whose program the information about the task was received, and facilitating providing of the associated compensation for the task to those one or more human task performers on behalf of that task requester. 55. The non-transitory computer-readable medium of claim 51 wherein the providing of information about the at least some available tasks includes repeatedly providing information to one of the identified human task performers about multiple available tasks matching specified criteria.

42. A computer readable storage medium on which is encoded executable program code for category based search, the program code comprising: program code for identifying an event comprising a user interaction with a web page responsive to monitoring user interactions with a client device; program code for identifying an event schema describing a format of the identified event responsive at least in part to an article type of the web page, the schema comprising fields describing the web page and fields that describe interactions with the web page; program code for identifying a plurality of attributes associated with the identified event based at least in part on one or more fields of the event schema, the plurality of attributes identified responsive to the web page and the monitored user interactions, wherein at least a first attribute is associated with a keyword; program code for searching a category-keyword data store for a category associated with the keyword; program code for receiving a category identifier from the category-keyword data store; program code for storing an association data record in a category-article data store, the association data record comprising a category-article pair identifier, the category-article pair identifier associating the category identifier and an identifier identifying the web page; program code for receiving an implicit search query; program code for causing the implicit search query to be executed on the category-article data store; program code for receiving the association data record from the category-article data store; and program code for causing the identifier identifying the web page and the category to be output.

42. A computer readable storage medium on which is encoded executable program code for category based search, the program code comprising: program code for identifying an event comprising a user interaction with a web page responsive to monitoring user interactions with a client device; program code for identifying an event schema describing a format of the identified event responsive at least in part to an article type of the web page, the schema comprising fields describing the web page and fields that describe interactions with the web page; program code for identifying a plurality of attributes associated with the identified event based at least in part on one or more fields of the event schema, the plurality of attributes identified responsive to the web page and the monitored user interactions, wherein at least a first attribute is associated with a keyword; program code for searching a category-keyword data store for a category associated with the keyword; program code for receiving a category identifier from the category-keyword data store; program code for storing an association data record in a category-article data store, the association data record comprising a category-article pair identifier, the category-article pair identifier associating the category identifier and an identifier identifying the web page; program code for receiving an implicit search query; program code for causing the implicit search query to be executed on the category-article data store; program code for receiving the association data record from the category-article data store; and program code for causing the identifier identifying the web page and the category to be output. 43. The computer-readable storage medium of claim 42 , wherein program code for identifying the event schema for the identified event responsive at least in part to an article type of the article comprises program code for: selecting the event schema for the event from among a plurality of schemas associated with a plurality of article types.

16. The system of claim 14 , wherein each of the plurality of different database types is associated with a single plugin.

16. The system of claim 14 , wherein each of the plurality of different database types is associated with a single plugin. 18. The system of claim 16 , the processor to execute instructions to: add a second plugin associated with a second database type different from those in the plurality of different database types; and allow a second database specific schema to be generated for the second database type by the second plugin.

16. The non-transitory computer-readable medium according to claim 15 , wherein the code for setting up a context in a debugger comprises: code for displaying a waveform of misbehaved signals associated with the anomaly in a waveform window; and code for centering the waveform window around a simulation time at which the anomaly is detected.

16. The non-transitory computer-readable medium according to claim 15 , wherein the code for setting up a context in a debugger comprises: code for displaying a waveform of misbehaved signals associated with the anomaly in a waveform window; and code for centering the waveform window around a simulation time at which the anomaly is detected. 17. The non-transitory computer-readable medium according to claim 16 , wherein the code for setting up a context in a debugger comprises: code for displaying in a text window a portion of the circuit design associated with the anomaly, a portion of the power specification associated with the anomaly, or a combination thereof.

7. A method comprising: receiving a string by a computing device, wherein the received string is associated with a conversation between a user of the computing device and one or more parties; determining a context for the received string by the computing device based on a contact associated with one of the one or more parties of the conversation, wherein the context includes only a plurality of strings that were entered by the user when the user previously interacted with the contact; determining if a criterion is met by the received string by the computing device; and if the criterion is met by the received string, adding the received string to the plurality of strings of the context by the computing device.

7. A method comprising: receiving a string by a computing device, wherein the received string is associated with a conversation between a user of the computing device and one or more parties; determining a context for the received string by the computing device based on a contact associated with one of the one or more parties of the conversation, wherein the context includes only a plurality of strings that were entered by the user when the user previously interacted with the contact; determining if a criterion is met by the received string by the computing device; and if the criterion is met by the received string, adding the received string to the plurality of strings of the context by the computing device. 11. The method of claim 7 , further comprising determining a style of the conversation, and wherein determining the context for the received string based on the contact associated with one of the one or more parties of the conversation further comprises determining the context for the received string based on the determined style.

3. Computer apparatus as claimed in claim 1 wherein the execution engine employs a plurality of queues that allow execution threads to execute any kernel action at any time.

3. Computer apparatus as claimed in claim 1 wherein the execution engine employs a plurality of queues that allow execution threads to execute any kernel action at any time. 4. Computer apparatus as claimed in claim 3 wherein the queues are coupled in parallel.

17. A computer-implemented system providing optimized processing of messages, the system comprising: a computer having at least one processor and a memory; metadata, created at design time based on user input received in a graphical user interface, comprising markup language information for characterizing logical structure and physical structure of a particular message type in serialized form; a designer module for generating source code in response to said metadata, said source code for de novo creation of custom runtime components comprising newly created custom source code that is highly optimized for runtime processing of said particular message type; and a compiler for compiling the source code into said custom runtime components, so that in a runtime environment deploying said runtime components the messages are processed by said runtime components in a manner that is highly optimized for the particular message type.

17. A computer-implemented system providing optimized processing of messages, the system comprising: a computer having at least one processor and a memory; metadata, created at design time based on user input received in a graphical user interface, comprising markup language information for characterizing logical structure and physical structure of a particular message type in serialized form; a designer module for generating source code in response to said metadata, said source code for de novo creation of custom runtime components comprising newly created custom source code that is highly optimized for runtime processing of said particular message type; and a compiler for compiling the source code into said custom runtime components, so that in a runtime environment deploying said runtime components the messages are processed by said runtime components in a manner that is highly optimized for the particular message type. 22. The system of claim 17 , wherein the metadata itself is represented as an XML markup file.

13. A non-transitory computer readable medium storing instructions that, when executed, cause a computer to perform a method for determining a reputation score representing a reputation of an Internet user, the method comprising: collecting, at a computer, at least one search result from a data source via a search engine based on a search term identifying the Internet user; identifying a contextual token describing the Internet user within a string of words surrounding a relevancy-indicating token in the at least one search result; determining an effect of the at least one search result on the reputation of the Internet user based at least in part on whether the identified contextual token affects the reputation of the user; associating the identified contextual token with a token weight based on the determined effect; and calculating the reputation score representing the reputation of the Internet user based at least in part on the associated token weight.

13. A non-transitory computer readable medium storing instructions that, when executed, cause a computer to perform a method for determining a reputation score representing a reputation of an Internet user, the method comprising: collecting, at a computer, at least one search result from a data source via a search engine based on a search term identifying the Internet user; identifying a contextual token describing the Internet user within a string of words surrounding a relevancy-indicating token in the at least one search result; determining an effect of the at least one search result on the reputation of the Internet user based at least in part on whether the identified contextual token affects the reputation of the user; associating the identified contextual token with a token weight based on the determined effect; and calculating the reputation score representing the reputation of the Internet user based at least in part on the associated token weight. 20. The computer readable medium of claim 13 , wherein the instructions that, when executed, cause the computer to perform the method further comprising: associating the at least one search result along a positive to negative scale; and determining the effect of the at least one search result on the reputation of the Internet user based at least in part on the positive to negative association of the at least one search result.

1. A method for managing and utilizing connections between an application server comprising the Java Platform, Enterprise Edition architecture and an enterprise information system comprising a database management system based on a Daytona architecture, comprising: operating a resource adapter, said resource adapter conforming to a Java Platform, Enterprise Edition Connector architecture and being interfaced with and managed by the application server, wherein operating the resource adapter comprises: providing a connection to the enterprise information system; submitting a query request to the enterprise information system; and receiving query results from the enterprise information system; wherein submitting a query request to the enterprise information system comprises: receiving the query request from a client; instructing the enterprise information system to open a query; instructing the enterprise information system to compile the query; instructing the enterprise information system to execute the query; and wherein receiving query results from the enterprise information system comprises: instructing the enterprise information system to return the results of the execution of the query; receiving the results of the execution of the query from the enterprise information system; instructing the enterprise information system to terminate the connection; and returning the results of the execution of the query to the client; wherein instructing the enterprise information system to open a query comprises issuing a DS OPEN command, including login credentials and a specification of the type of the query, to a PolyClient Daytona Query server of the enterprise information system; and wherein instructing the enterprise information system to compile the query comprises issuing a DS COMPILE command, including a name for the query and the query itself, to the PolyClient Daytona Query server; and wherein instructing the enterprise information system to execute the query comprises issuing a DS EXECUTE command, including the name for the query, to the PolyClient Daytona Query server; and wherein instructing the enterprise information system to return the results of the query comprises issuing a DS CAT command, including the name for the query, to the PolyClient Daytona Query server; and wherein instructing the enterprise information system to terminate the connection comprises issuing a DS CLOSE command to the PolgClient Daytona Query server.

1. A method for managing and utilizing connections between an application server comprising the Java Platform, Enterprise Edition architecture and an enterprise information system comprising a database management system based on a Daytona architecture, comprising: operating a resource adapter, said resource adapter conforming to a Java Platform, Enterprise Edition Connector architecture and being interfaced with and managed by the application server, wherein operating the resource adapter comprises: providing a connection to the enterprise information system; submitting a query request to the enterprise information system; and receiving query results from the enterprise information system; wherein submitting a query request to the enterprise information system comprises: receiving the query request from a client; instructing the enterprise information system to open a query; instructing the enterprise information system to compile the query; instructing the enterprise information system to execute the query; and wherein receiving query results from the enterprise information system comprises: instructing the enterprise information system to return the results of the execution of the query; receiving the results of the execution of the query from the enterprise information system; instructing the enterprise information system to terminate the connection; and returning the results of the execution of the query to the client; wherein instructing the enterprise information system to open a query comprises issuing a DS OPEN command, including login credentials and a specification of the type of the query, to a PolyClient Daytona Query server of the enterprise information system; and wherein instructing the enterprise information system to compile the query comprises issuing a DS COMPILE command, including a name for the query and the query itself, to the PolyClient Daytona Query server; and wherein instructing the enterprise information system to execute the query comprises issuing a DS EXECUTE command, including the name for the query, to the PolyClient Daytona Query server; and wherein instructing the enterprise information system to return the results of the query comprises issuing a DS CAT command, including the name for the query, to the PolyClient Daytona Query server; and wherein instructing the enterprise information system to terminate the connection comprises issuing a DS CLOSE command to the PolgClient Daytona Query server. 9. The method of claim 1 , wherein the connection to the enterprise information system comprises a secure connection; and wherein data communicated over the secure connection is encrypted using a cryptographic algorithm.

3. A communication aid for an impaired individual comprising: a) a collection assembly including a plurality of support structures segregated into a plurality of categories, each category representative of a different subject matter, b) a plurality of demonstration pieces each having an exposed surface including informative indicia formed thereon, c) each of said support structures comprising a display surface formed thereon which is structured and disposed to removably mount a number of subject-related ones of said plurality of demonstration pieces thereon, each of said subject-related demonstration pieces oriented to display said exposed surface thereof for viewing of said informative indicia thereon, d) said collection assembly including at least one primary display portion structured to removably support at least one of said plurality of demonstration pieces thereon in a cooperative array, e) said informative indicia of said at least one demonstration piece which comprises said cooperative array defining a communication created at least in part by the impaired individual, f) said informative indicia on at least some of said plurality of demonstration pieces comprising alphanumeric displays and said alphanumeric displays on said subject related ones of said plurality of demonstration pieces all being representative of one of said plurality of categories, and g) each of said plurality of support structures including code means for identifying a number of said plurality of subject-related demonstration pieces as being representative of one grouping of subject-related demonstration pieces.

3. A communication aid for an impaired individual comprising: a) a collection assembly including a plurality of support structures segregated into a plurality of categories, each category representative of a different subject matter, b) a plurality of demonstration pieces each having an exposed surface including informative indicia formed thereon, c) each of said support structures comprising a display surface formed thereon which is structured and disposed to removably mount a number of subject-related ones of said plurality of demonstration pieces thereon, each of said subject-related demonstration pieces oriented to display said exposed surface thereof for viewing of said informative indicia thereon, d) said collection assembly including at least one primary display portion structured to removably support at least one of said plurality of demonstration pieces thereon in a cooperative array, e) said informative indicia of said at least one demonstration piece which comprises said cooperative array defining a communication created at least in part by the impaired individual, f) said informative indicia on at least some of said plurality of demonstration pieces comprising alphanumeric displays and said alphanumeric displays on said subject related ones of said plurality of demonstration pieces all being representative of one of said plurality of categories, and g) each of said plurality of support structures including code means for identifying a number of said plurality of subject-related demonstration pieces as being representative of one grouping of subject-related demonstration pieces. 10. A communication aid as recited in claim 3 further comprising a second collection assembly having a plurality of support structures for additional demonstration pieces.

8. An information handling system comprising: one or more processors; one or more data stores accessible by at least one of the processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: selecting a question from a post in a threaded discussion; automatically identifying an answer to the selected question from one or more crowd-based sources, wherein the identified answer has a confidence level greater than a threshold; revising the selected question based on a lexical answer type (LAT) of the selected question; building an answer key with the revised selected question and the identified answer; and automatically training a question answering (QA) system using the answer key.

8. An information handling system comprising: one or more processors; one or more data stores accessible by at least one of the processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: selecting a question from a post in a threaded discussion; automatically identifying an answer to the selected question from one or more crowd-based sources, wherein the identified answer has a confidence level greater than a threshold; revising the selected question based on a lexical answer type (LAT) of the selected question; building an answer key with the revised selected question and the identified answer; and automatically training a question answering (QA) system using the answer key. 9. The information handling system of claim 8 wherein the actions further comprise: revising the selected question based on a focus and the lexical answer type (LAT) of the selected question given a noun, a subject, a verb and a context identified in the selected question.

8. A system to translate a software package including a non-localizable file and a localizable file, the localizable file including string data from at least one source in a first human language for translation into a second human language, the non-localizable file lacking data requiring translation from the first to the second human language, the system comprising: an extractor to receive the localizable file, the localizable file and the non-localizable file having been compiled by a computer system remote from the extractor to produce a set of install files, a reader module remote from the computer system and coupled to the extractor, the reader module to extract the string data from the localizable file and export the extracted string data to a formatted file; a translator coupled to the reader, the translator receiving a translated formatted file that includes translated string data corresponding to the extracted string data that has been at least partially translated from the first human language to the second human language; and a writer module coupled to the translator, the writer to receive the translated formatted file that includes the translated string data, extracted string data that has been translated from the first human language into the second the writer module to import the translated string data into the localizable files to produce a translated localizable file that includes the imported translated string data, the writing module providing the translated localizable file to a packager for packaging the translated localizable file together with the non-localizable file into a set of target install files in a storage medium without requiring recompilation from source code to computer-executable code of the non-localizable file, the non-localizable file including a computer-executable binary file.

8. A system to translate a software package including a non-localizable file and a localizable file, the localizable file including string data from at least one source in a first human language for translation into a second human language, the non-localizable file lacking data requiring translation from the first to the second human language, the system comprising: an extractor to receive the localizable file, the localizable file and the non-localizable file having been compiled by a computer system remote from the extractor to produce a set of install files, a reader module remote from the computer system and coupled to the extractor, the reader module to extract the string data from the localizable file and export the extracted string data to a formatted file; a translator coupled to the reader, the translator receiving a translated formatted file that includes translated string data corresponding to the extracted string data that has been at least partially translated from the first human language to the second human language; and a writer module coupled to the translator, the writer to receive the translated formatted file that includes the translated string data, extracted string data that has been translated from the first human language into the second the writer module to import the translated string data into the localizable files to produce a translated localizable file that includes the imported translated string data, the writing module providing the translated localizable file to a packager for packaging the translated localizable file together with the non-localizable file into a set of target install files in a storage medium without requiring recompilation from source code to computer-executable code of the non-localizable file, the non-localizable file including a computer-executable binary file. 9. The system of claim 8 wherein the software package is a power monitoring software product.

10. The system of claim 1 , the acts further comprising: determining that a user is utilizing a mouse pointer to hover over at least one message; and determining that the user is utilizing the mouse pointer to hover over the at least one message, displaying biographical information for the at least one author.

10. The system of claim 1 , the acts further comprising: determining that a user is utilizing a mouse pointer to hover over at least one message; and determining that the user is utilizing the mouse pointer to hover over the at least one message, displaying biographical information for the at least one author. 11. The system of claim 10 , wherein the biographical information comprises: location of the at least one author; a number of messages generated by the at least one author through utilization of a social networking application; a number of followers of the at least one author; and graphical indicia of sentiment of messages generated by the at least one author.

12. A speech communication system comprising: non-transitory memory; a transcription unit, the transcription unit configured to transcribe a recorded portion of a speech communication between the at least first and second user stored in the memory to form a transcribed portion, a selecting unit, the selecting unit configured to select and mark at least one of the words of the transcribed portion which is considered to be a keyword of the speech communication, a search unit, the search unit configured to perform at least one search for each keyword and produce at least one definition for each keyword that identifies a meaning of that keyword, a trustworthiness unit, the trustworthiness unit configured to calculate a trustworthiness factor for each keyword, each trustworthiness factor indicating a calculated validity of a respective definition for a respective keyword; and a display unit, the display unit configured to display the transcribed portion such that, in response to a pointer being positioned over at least one keyword of the displayed transcribed portion or selection of at least one displayed keyword, displaying of the at least one definition of the keyword together with the calculated trustworthiness factor for each displayed definition is actuated.

12. A speech communication system comprising: non-transitory memory; a transcription unit, the transcription unit configured to transcribe a recorded portion of a speech communication between the at least first and second user stored in the memory to form a transcribed portion, a selecting unit, the selecting unit configured to select and mark at least one of the words of the transcribed portion which is considered to be a keyword of the speech communication, a search unit, the search unit configured to perform at least one search for each keyword and produce at least one definition for each keyword that identifies a meaning of that keyword, a trustworthiness unit, the trustworthiness unit configured to calculate a trustworthiness factor for each keyword, each trustworthiness factor indicating a calculated validity of a respective definition for a respective keyword; and a display unit, the display unit configured to display the transcribed portion such that, in response to a pointer being positioned over at least one keyword of the displayed transcribed portion or selection of at least one displayed keyword, displaying of the at least one definition of the keyword together with the calculated trustworthiness factor for each displayed definition is actuated. 17. The speech communication system of claim 12 , further comprising: a semantic search unit, the semantic search unit configured to perform a semantic search using ontologies.

1. A method comprising, by one or more computing devices: receiving from a first user of an online social network a search query input comprising one or more n-grams; generating a plurality of query commands by parsing the search query input, wherein each query command comprises one or more query constraints, each query constraint being a request for a particular object-type to be retrieved from a particular vertical, and wherein each query command is customized for one or more respective verticals; searching, for each query command of the plurality of query commands, the one or more respective verticals to identify a plurality of objects stored by the vertical that match the respective query command, each vertical storing one or more objects of a particular object-type associated with the online social network; generating a plurality of search-result modules corresponding to the plurality of query commands, respectively, each search-result module of the plurality of search-result modules comprising references to a plurality of the identified objects matching the query command corresponding to the search-result module; classifying the search query input, wherein the classification of the search query input is based at least in part on a semantic parsing of the search query input and social-networking information of the first user; scoring each search-result module of the plurality of search-result modules, wherein scoring the search-result modules comprises, for each search-result module of the plurality of search-result modules: calculating a score for the search-result module based at least in part on: a relevance of the search-result module with respect to the classification of the search query input; and a relevance of each identified object referenced in the search-result module with respect to the search query input; and sending each search-result module having a score greater than a threshold score to the first user for display, wherein the search-result modules are displayed in order based on their respective scores.

1. A method comprising, by one or more computing devices: receiving from a first user of an online social network a search query input comprising one or more n-grams; generating a plurality of query commands by parsing the search query input, wherein each query command comprises one or more query constraints, each query constraint being a request for a particular object-type to be retrieved from a particular vertical, and wherein each query command is customized for one or more respective verticals; searching, for each query command of the plurality of query commands, the one or more respective verticals to identify a plurality of objects stored by the vertical that match the respective query command, each vertical storing one or more objects of a particular object-type associated with the online social network; generating a plurality of search-result modules corresponding to the plurality of query commands, respectively, each search-result module of the plurality of search-result modules comprising references to a plurality of the identified objects matching the query command corresponding to the search-result module; classifying the search query input, wherein the classification of the search query input is based at least in part on a semantic parsing of the search query input and social-networking information of the first user; scoring each search-result module of the plurality of search-result modules, wherein scoring the search-result modules comprises, for each search-result module of the plurality of search-result modules: calculating a score for the search-result module based at least in part on: a relevance of the search-result module with respect to the classification of the search query input; and a relevance of each identified object referenced in the search-result module with respect to the search query input; and sending each search-result module having a score greater than a threshold score to the first user for display, wherein the search-result modules are displayed in order based on their respective scores. 16. The method of claim 1 , wherein the score for each search-result module is further based on: calculating a sub-score for each identified object referenced in the search-result module, wherein the sub-score is based on the relevance of the identified object with respect to the search query input; and summing the sub-scores of the top N identified objects in the search-result module.

6. A handheld electronic device comprising: an input apparatus comprising a plurality of input members, at least some of the input members each having a plurality of characters assigned thereto; a processor apparatus comprising a processor and a memory having stored therein a plurality of objects comprising a plurality of language objects and a plurality of frequency objects, at least some of the language objects each being associated with an associated frequency object, the plurality of language objects comprising a plurality of word objects and a plurality of N-gram objects that each comprises at least a first character, the processor apparatus being structured to detect an ambiguous input that comprises a number of input member actuations, and being further structured to generate a plurality of character permutations of the ambiguous input, one of the character permutations being a potential artificial variant that is neither a prefix of a word object nor is identical to a word object; an output apparatus; the processor apparatus being structured to make a determination that at least a portion of the potential artificial variant corresponds with an N-gram object associated with a frequency object having a frequency value below a predetermined threshold, the portion including fewer characters than the number of input member actuations; the processor apparatus being structured to generate an output that comprises a representation of each of a number of the character permutations; and the processor apparatus being structured to output as an artificial variant a representation of the potential artificial variant at a position of relatively lower priority than a representation of another character permutation, if the artificial variant has been displayed during a current session.

6. A handheld electronic device comprising: an input apparatus comprising a plurality of input members, at least some of the input members each having a plurality of characters assigned thereto; a processor apparatus comprising a processor and a memory having stored therein a plurality of objects comprising a plurality of language objects and a plurality of frequency objects, at least some of the language objects each being associated with an associated frequency object, the plurality of language objects comprising a plurality of word objects and a plurality of N-gram objects that each comprises at least a first character, the processor apparatus being structured to detect an ambiguous input that comprises a number of input member actuations, and being further structured to generate a plurality of character permutations of the ambiguous input, one of the character permutations being a potential artificial variant that is neither a prefix of a word object nor is identical to a word object; an output apparatus; the processor apparatus being structured to make a determination that at least a portion of the potential artificial variant corresponds with an N-gram object associated with a frequency object having a frequency value below a predetermined threshold, the portion including fewer characters than the number of input member actuations; the processor apparatus being structured to generate an output that comprises a representation of each of a number of the character permutations; and the processor apparatus being structured to output as an artificial variant a representation of the potential artificial variant at a position of relatively lower priority than a representation of another character permutation, if the artificial variant has been displayed during a current session. 7. The handheld electronic device of claim 6 wherein the N-gram object that is associated with the frequency object having the frequency value below the predetermined threshold comprises three characters, and wherein the processor apparatus is structured to make, as at least a part of said determination, a determination that a final three characters of the potential artificial variant correspond with said N-gram object.

1. A computer-implemented method for exchanging meta-documents between meta-document servers, comprising: importing, at an importing meta-document server, a meta-document from an exporting meta-document server; the imported meta-document including one or more document service requests fulfilled using one or more document services available at the exporting meta-document server; developing at the importing meta-document server an ontology of namespaces that describe entities in the imported meta-document; binding at least a selected one of the one or more document service requests in the imported meta-document to one of a plurality of document services available at the importing meta-document server when: (a) properties of the selected document service request in the imported meta-document map to properties of one of the plurality of document services available at the importing meta-document server; or (b) the selected document service request in the imported meta-document and one of the plurality of document services available at the importing meta-document server (i) map to the same category in the developed ontology, and (ii) have at least one dictionary and one key in common.

1. A computer-implemented method for exchanging meta-documents between meta-document servers, comprising: importing, at an importing meta-document server, a meta-document from an exporting meta-document server; the imported meta-document including one or more document service requests fulfilled using one or more document services available at the exporting meta-document server; developing at the importing meta-document server an ontology of namespaces that describe entities in the imported meta-document; binding at least a selected one of the one or more document service requests in the imported meta-document to one of a plurality of document services available at the importing meta-document server when: (a) properties of the selected document service request in the imported meta-document map to properties of one of the plurality of document services available at the importing meta-document server; or (b) the selected document service request in the imported meta-document and one of the plurality of document services available at the importing meta-document server (i) map to the same category in the developed ontology, and (ii) have at least one dictionary and one key in common. 3. The method according to claim 1 , wherein two keys are in common with each other when one of the two keys associated with a first service and the other of the two keys associated with a second service reduce to a common generic key.

10. One or more computer-readable storage media encoded with instructions that, when executed by a processor, perform acts comprising: receiving video data including a plurality of video frames; extracting a plurality of features from individual video frames of the plurality of video frames to determine a first set of feature values associated with the individual video frames; applying a classifier to the first set of feature values to determine a second set of feature values associated with the individual video frames; using the second set of feature values to determine individual probabilities that the individual video frames belong to at least one semantic category of a predefined set of semantic categories; applying a scoring model to the first set of feature values and the second set of feature values to determine desirability scores associated with the individual video frames; identifying a subset of the plurality of video frames in the video data that have a desirability score above a predetermined threshold desirability score; analyzing the video data to determine, in association with the subset of video frames, changes in camera motion and changes in object motion; and locating, based at least in part on the changes in camera motion and the changes in object motion, boundaries in the video data to produce one or more video segments, wherein: an individual video segment includes at least one video frame that has the desirability score above the predetermined threshold desirability score, and the locating the boundaries in the video data comprises determining that object motion intensity of a first video frame and object motion intensity of a second video frame differ by a predetermined threshold.

10. One or more computer-readable storage media encoded with instructions that, when executed by a processor, perform acts comprising: receiving video data including a plurality of video frames; extracting a plurality of features from individual video frames of the plurality of video frames to determine a first set of feature values associated with the individual video frames; applying a classifier to the first set of feature values to determine a second set of feature values associated with the individual video frames; using the second set of feature values to determine individual probabilities that the individual video frames belong to at least one semantic category of a predefined set of semantic categories; applying a scoring model to the first set of feature values and the second set of feature values to determine desirability scores associated with the individual video frames; identifying a subset of the plurality of video frames in the video data that have a desirability score above a predetermined threshold desirability score; analyzing the video data to determine, in association with the subset of video frames, changes in camera motion and changes in object motion; and locating, based at least in part on the changes in camera motion and the changes in object motion, boundaries in the video data to produce one or more video segments, wherein: an individual video segment includes at least one video frame that has the desirability score above the predetermined threshold desirability score, and the locating the boundaries in the video data comprises determining that object motion intensity of a first video frame and object motion intensity of a second video frame differ by a predetermined threshold. 17. The computer-readable storage media of claim 10 , wherein: the plural of features includes low level features and high level features; the first set of feature values includes at least a low level feature value and a first high level feature value; and the second set of feature values includes at least one second high level feature value that is not included in the first set of feature values.

1. A computer-implemented method for validating an entity, the method comprising: classifying an entity type of an entity to be validated based on a predefined entity classifier; selecting at least one of a plurality of validation rules in accordance with the entity type; producing, by a computer of a requesting entity and based on the selected at least one validation rule, a validation request including information identifying the entity; providing, by the computer, the validation request to a validation entity for performance of at least a portion of a validation in accordance with the selected at least one validation rule; receiving, by the computer, a validation outcome of the at least the portion of the validation from the validation entity; generating a validation request management display including an inbox icon, an outbox icon, an overview section, and a details section; wherein: responsive to selection of the inbox icon, the overview section displays a list of validation outcomes that have been received and the details section displays detailed information regarding a selected one of the listed validation outcomes; and responsive to selection of the outbox icon, the overview section displays a list of validation requests that have been provided to validation entities and the details section displays detailed information regarding a selected one of the listed validation requests.

1. A computer-implemented method for validating an entity, the method comprising: classifying an entity type of an entity to be validated based on a predefined entity classifier; selecting at least one of a plurality of validation rules in accordance with the entity type; producing, by a computer of a requesting entity and based on the selected at least one validation rule, a validation request including information identifying the entity; providing, by the computer, the validation request to a validation entity for performance of at least a portion of a validation in accordance with the selected at least one validation rule; receiving, by the computer, a validation outcome of the at least the portion of the validation from the validation entity; generating a validation request management display including an inbox icon, an outbox icon, an overview section, and a details section; wherein: responsive to selection of the inbox icon, the overview section displays a list of validation outcomes that have been received and the details section displays detailed information regarding a selected one of the listed validation outcomes; and responsive to selection of the outbox icon, the overview section displays a list of validation requests that have been provided to validation entities and the details section displays detailed information regarding a selected one of the listed validation requests. 7. The method of claim 1 , wherein the validation rules are applied using a predetermined selection of validation criteria.

20. A method of automatically generating an index page in an image forming apparatus, the method comprising: receiving data associated with a document having one or more pages and determining a text area in the one or more pages with a text/image separation apparatus; determining one or more content indicating texts from among the text area in the one or more pages by selecting characters of the content indicating texts based on comparing a size of characters in the text area with a predetermined size threshold that is set as an average value of preset character properties calculated on a variation of the preset character properties, and grouping selected characters together based on relative proximity to one another with an index determination apparatus; and automatically generating the index page for the document including the one or more content indicating texts with an index page creation apparatus, wherein the determining of the one or more content indicating texts from among the text area in the one or more pages comprises: receiving separated symbols of the text area; and comparing the separated symbols to one or more predetermined size parameters to determine whether the separated symbols are content indicating symbols, and grouping adjacent ones of the content indicating symbols together; and determining the grouped content indicating symbols as the content indicating texts for the index page.

20. A method of automatically generating an index page in an image forming apparatus, the method comprising: receiving data associated with a document having one or more pages and determining a text area in the one or more pages with a text/image separation apparatus; determining one or more content indicating texts from among the text area in the one or more pages by selecting characters of the content indicating texts based on comparing a size of characters in the text area with a predetermined size threshold that is set as an average value of preset character properties calculated on a variation of the preset character properties, and grouping selected characters together based on relative proximity to one another with an index determination apparatus; and automatically generating the index page for the document including the one or more content indicating texts with an index page creation apparatus, wherein the determining of the one or more content indicating texts from among the text area in the one or more pages comprises: receiving separated symbols of the text area; and comparing the separated symbols to one or more predetermined size parameters to determine whether the separated symbols are content indicating symbols, and grouping adjacent ones of the content indicating symbols together; and determining the grouped content indicating symbols as the content indicating texts for the index page. 27. The method of claim 20 , wherein the generating of the index page for the document including the one or more content indicating texts comprises generating the index page to include the content indicating texts associated with page indicators of pages of the document that include the content indicating texts.

3. The method according to claim 2 , wherein the rhythm feature is represented as a phrase boundary location of the input speech data.

3. The method according to claim 2 , wherein the rhythm feature is represented as a phrase boundary location of the input speech data. 4. The method according to claim 3 , wherein comparing the rhythm feature to the standard rhythm feature comprises determining whether the phrase boundary location matches with a standard phrase boundary location.

2. The method of claim 1 , wherein the mapping information includes a first mapping rule that defines a value of an attribute of a destination entity in terms of a value of an attribute of a first source entity and a value of an attribute of a second source entity.

2. The method of claim 1 , wherein the mapping information includes a first mapping rule that defines a value of an attribute of a destination entity in terms of a value of an attribute of a first source entity and a value of an attribute of a second source entity. 8. The method of claim 2 , wherein the first source entity and the second source entity are related according to a relationship defined in a schema.

1. A method for transforming narrative content into structured output that defines where individual information resides within the output, the method comprising the steps of: receiving narrative content; scanning the narrative content using a natural language processing engine to identify at least one section and at least one clinical assertion within that section; extracting information from the narrative content, wherein the extracted information includes clinical assertions and contextual information; and identifying one or more clinical assertion elements which define a clinical assertion and assigning a clinical assertion element label to at least one clinical assertion element of the one or more clinical assertion elements based on a clinical model, wherein the label assigned to the at least one clinical assertion element is selected from a predetermined list, wherein the list is predetermined based on a clinical assertion type.

1. A method for transforming narrative content into structured output that defines where individual information resides within the output, the method comprising the steps of: receiving narrative content; scanning the narrative content using a natural language processing engine to identify at least one section and at least one clinical assertion within that section; extracting information from the narrative content, wherein the extracted information includes clinical assertions and contextual information; and identifying one or more clinical assertion elements which define a clinical assertion and assigning a clinical assertion element label to at least one clinical assertion element of the one or more clinical assertion elements based on a clinical model, wherein the label assigned to the at least one clinical assertion element is selected from a predetermined list, wherein the list is predetermined based on a clinical assertion type. 10. The method of claim 1 , wherein the clinical assertion element label qualifies or modifies a clinical assertion element of the clinical assertion elements.

9. A system for managing data, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: providing a principal data set and another data set, wherein the principal data set includes a plurality of principal objects and the other data set includes a plurality of other objects; instantiating a first engine to perform actions including: associating each of the plurality of principal objects with one or more other objects that are selected from the plurality of other objects, wherein the one or more other objects are selected as potential matches to one or more of the principal objects; selecting one or more principal objects of the plurality of principal objects based on one or more heuristics and the one or more selected principal objects association with selected other objects; and labeling one or more of the selected other objects as either a match or a non-match of their associated principal object; and instantiating a second engine to perform actions, including: training a ranker to identify a selected other object that is top-ranked in similarity to its association with the one or more principal objects based on the labeling of the one or more selected other objects; and employing the trained ranker to indicate a match among the plurality of principal objects and the plurality of other objects; and instantiating a third engine to selectively filter the plurality of other objects to rank each matched other object higher than other objects associated with a same principal object, wherein geolocation information from a GPS device is employed to localize the displaying of the ranked other objects including one or more of time zone or language, and wherein a hardware security module is used to provide tamper resistant safeguarding of cryptographic information; and a client computer, comprising: a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: displaying one or more of the one or more principal objects and the one or more selected other objects on a display of the client computer, wherein the displayed selected other objects are associated with a same principal object.

9. A system for managing data, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: providing a principal data set and another data set, wherein the principal data set includes a plurality of principal objects and the other data set includes a plurality of other objects; instantiating a first engine to perform actions including: associating each of the plurality of principal objects with one or more other objects that are selected from the plurality of other objects, wherein the one or more other objects are selected as potential matches to one or more of the principal objects; selecting one or more principal objects of the plurality of principal objects based on one or more heuristics and the one or more selected principal objects association with selected other objects; and labeling one or more of the selected other objects as either a match or a non-match of their associated principal object; and instantiating a second engine to perform actions, including: training a ranker to identify a selected other object that is top-ranked in similarity to its association with the one or more principal objects based on the labeling of the one or more selected other objects; and employing the trained ranker to indicate a match among the plurality of principal objects and the plurality of other objects; and instantiating a third engine to selectively filter the plurality of other objects to rank each matched other object higher than other objects associated with a same principal object, wherein geolocation information from a GPS device is employed to localize the displaying of the ranked other objects including one or more of time zone or language, and wherein a hardware security module is used to provide tamper resistant safeguarding of cryptographic information; and a client computer, comprising: a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: displaying one or more of the one or more principal objects and the one or more selected other objects on a display of the client computer, wherein the displayed selected other objects are associated with a same principal object. 16. The system of claim 9 , further comprising, distributing one or more instances of one or more of the first engine, or the second engine across two or more separate network computers, wherein the one or more instances may execute in parallel or concurrently.

18. The system of claim 13 , the set of actions further comprising: receiving feedback indicating whether the first word was correctly predicted during the first ASR processing; determining a total number of first predictions for the first word by adding a first number of predictions during ASR testing and a second number of times the first word was predicted during the first ASR processing; determining a first number of correct results for the first word, the first number of correct results corresponding to a number of times the first word was correctly predicted during the ASR testing and the first ASR processing; and determining an individual prior probability for the first word by dividing the first number of correct results and the total number of first predictions.

18. The system of claim 13 , the set of actions further comprising: receiving feedback indicating whether the first word was correctly predicted during the first ASR processing; determining a total number of first predictions for the first word by adding a first number of predictions during ASR testing and a second number of times the first word was predicted during the first ASR processing; determining a first number of correct results for the first word, the first number of correct results corresponding to a number of times the first word was correctly predicted during the ASR testing and the first ASR processing; and determining an individual prior probability for the first word by dividing the first number of correct results and the total number of first predictions. 19. The system of claim 18 , wherein the memory further comprises instructions that, when executed by the at least one processor, further cause the system to: determine that the total number of first predictions exceeds a threshold; and determine the first prior probability for the first word using the individual prior probability.

4. The system of claim 3 , wherein the set of repertoire functions comprise one of resolver, context-gate, collector, qualifier or operators, and wherein each type of repertoire function fulfills a specific role in the inference process.

4. The system of claim 3 , wherein the set of repertoire functions comprise one of resolver, context-gate, collector, qualifier or operators, and wherein each type of repertoire function fulfills a specific role in the inference process. 9. The system of claim 4 , wherein the context-gate function defined within a concept decides whether notes within all the upstream nodes required to create a downstream node have met the conditions needed to create new downstream nodes and wherein the context-gate function is invoked after the operator functions of the concept have been invoked.

1. A method comprising: receiving, from a client, text associated with a request for text-to-speech synthesis; performing, via a processor of a computing device, an analysis of the text to identify a plurality of intonational phrases in the text, wherein a size of the text being analyzed is based on a network latency; generating, via the processor, a first file containing text-to-speech data for a first intonational phrase of the plurality of intonational phrases using a first text-to-speech voice, wherein the first text-to-speech voice is selected based on user preferences, and wherein the first intonational phrase is indexed by a first unique identifier; generating, via the processor, a second file containing the text-to-speech data for a second intonational phrase of the plurality of intonational phrases using a second text-to-speech voice, wherein the second text-to-speech voice is selected based on the user preferences, and wherein the second intonational phrase is indexed by a second unique identifier; storing the first file and the second file in a cache on a web-server; transmitting the first file to the client in response to the request; and while the client plays the first file, generating additional files containing additional text-to-speech data for remaining intonational phrases of the plurality of intonational phrases, wherein the remaining intonational phrases comprise the second intonational phrase, and wherein each of the additional files is indexed by the first unique identifier plus a respective offset.

1. A method comprising: receiving, from a client, text associated with a request for text-to-speech synthesis; performing, via a processor of a computing device, an analysis of the text to identify a plurality of intonational phrases in the text, wherein a size of the text being analyzed is based on a network latency; generating, via the processor, a first file containing text-to-speech data for a first intonational phrase of the plurality of intonational phrases using a first text-to-speech voice, wherein the first text-to-speech voice is selected based on user preferences, and wherein the first intonational phrase is indexed by a first unique identifier; generating, via the processor, a second file containing the text-to-speech data for a second intonational phrase of the plurality of intonational phrases using a second text-to-speech voice, wherein the second text-to-speech voice is selected based on the user preferences, and wherein the second intonational phrase is indexed by a second unique identifier; storing the first file and the second file in a cache on a web-server; transmitting the first file to the client in response to the request; and while the client plays the first file, generating additional files containing additional text-to-speech data for remaining intonational phrases of the plurality of intonational phrases, wherein the remaining intonational phrases comprise the second intonational phrase, and wherein each of the additional files is indexed by the first unique identifier plus a respective offset. 5. The method of claim 1 , wherein the unique identifier comprises a text identifier and an offset index.

21. A system for processing search results, comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving documents responsive to a query, each document having a respective associated score indicative of the document's relevance to the query, wherein: each respective associated score is based on a plurality of different score factors; each score factor for a given associated score corresponds to a different criterion than each other score factor for the given associated score; and each score factor has a respective trustworthiness score that indicates a respective reliability of values determined based on the score factor; determining, based on the trustworthiness scores for the score factors of a plurality of the associated scores of a plurality of different documents, a value-based distribution of the trustworthiness scores for each of the different score factors of the plurality of associated scores along a dimension based on relative values of the trustworthiness scores, the distribution including trustworthiness scores for multiple score factors for each of the different documents; adjusting the value of at least one score factor of a given associated score by an amount that is determined based on: a relative position of the at least one score factor's respective trustworthiness score in the distribution with respect to other trustworthiness scores in the distribution; and a measure of how widely the trustworthiness scores for each of the different score factors of the plurality of associated scores are distributed in the distribution; adjusting the given associated score based on the adjusted value of the at least one score factor; and ranking the documents to account for the adjusted score.

21. A system for processing search results, comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving documents responsive to a query, each document having a respective associated score indicative of the document's relevance to the query, wherein: each respective associated score is based on a plurality of different score factors; each score factor for a given associated score corresponds to a different criterion than each other score factor for the given associated score; and each score factor has a respective trustworthiness score that indicates a respective reliability of values determined based on the score factor; determining, based on the trustworthiness scores for the score factors of a plurality of the associated scores of a plurality of different documents, a value-based distribution of the trustworthiness scores for each of the different score factors of the plurality of associated scores along a dimension based on relative values of the trustworthiness scores, the distribution including trustworthiness scores for multiple score factors for each of the different documents; adjusting the value of at least one score factor of a given associated score by an amount that is determined based on: a relative position of the at least one score factor's respective trustworthiness score in the distribution with respect to other trustworthiness scores in the distribution; and a measure of how widely the trustworthiness scores for each of the different score factors of the plurality of associated scores are distributed in the distribution; adjusting the given associated score based on the adjusted value of the at least one score factor; and ranking the documents to account for the adjusted score. 27. The system of claim 21 , wherein each score factor's trustworthiness score is determined by a metric that calculates a degree of trustworthiness for the score factor.

1. An emotion script generating method, comprising: receiving, at a user terminal, a user's emotion data; generating, with a processor, emotion script using the emotion data based on a predefined template; the generated emotion script being computer readable program code; providing the generated emotion script to the user so that the user experiences an emotion corresponding to the emotion script in which providing the emotion script to the user comprises: determining configurations of the predefined template including a category of an emotion; adding values describing the emotion data to a number of categories within the predefined template according to the configurations of the predefined template; providing the generated emotion script to an emotion data adjustment interface and presenting the emotion data adjustment interface to the user; and providing the generated emotion script to a number of devices that affect the user's environment; and receiving adjustments to the emotion script comprising: after the user experiences the emotion, receiving adjustments to the generated emotion script at the emotion data adjustment interface adjusted by the user; replacing the stored emotion script with the adjusted emotion script; and associating the adjusted emotion script with a specific emotion felt by the user.

1. An emotion script generating method, comprising: receiving, at a user terminal, a user's emotion data; generating, with a processor, emotion script using the emotion data based on a predefined template; the generated emotion script being computer readable program code; providing the generated emotion script to the user so that the user experiences an emotion corresponding to the emotion script in which providing the emotion script to the user comprises: determining configurations of the predefined template including a category of an emotion; adding values describing the emotion data to a number of categories within the predefined template according to the configurations of the predefined template; providing the generated emotion script to an emotion data adjustment interface and presenting the emotion data adjustment interface to the user; and providing the generated emotion script to a number of devices that affect the user's environment; and receiving adjustments to the emotion script comprising: after the user experiences the emotion, receiving adjustments to the generated emotion script at the emotion data adjustment interface adjusted by the user; replacing the stored emotion script with the adjusted emotion script; and associating the adjusted emotion script with a specific emotion felt by the user. 15. The method of claim 1 , wherein the categories of emotion comprise sub-categories.

7. A computer implemented method of recognizing speech, the method comprising: identifying a valid verb; identifying a set of valid objects that corresponds to the valid verb; identifying a valid speech recognition command that includes a pairing of the valid verb with one of the valid objects; receiving an utterance from a user; determining that the utterance includes the valid verb in combination with an invalid object, the invalid object being determined to be invalid based at least in part upon a comparison of the invalid object to the set of valid objects; and providing, using a computer processor in response to the determination, inductive feedback that induces the user to select from at least two options for proceeding, comprising: prompting the user to submit an additional utterance that includes the valid verb in combination with the invalid object but is preceded by a valid command word other than the valid verb, to convert the valid verb and the invalid object into a textual representation to be inserted as dictation; and prompting the user to select one of the valid objects that corresponds to the valid verb, to use with the valid verb, by rendering a list of at least some of the valid objects; if the user submits the additional utterance, inserting the textual representation of the valid verb and the invalid object into a displayed collection of text generated based on other utterances received from the user; and if the user selects one of the valid objects from the list, executing the action defined by the valid verb and selected valid object.

7. A computer implemented method of recognizing speech, the method comprising: identifying a valid verb; identifying a set of valid objects that corresponds to the valid verb; identifying a valid speech recognition command that includes a pairing of the valid verb with one of the valid objects; receiving an utterance from a user; determining that the utterance includes the valid verb in combination with an invalid object, the invalid object being determined to be invalid based at least in part upon a comparison of the invalid object to the set of valid objects; and providing, using a computer processor in response to the determination, inductive feedback that induces the user to select from at least two options for proceeding, comprising: prompting the user to submit an additional utterance that includes the valid verb in combination with the invalid object but is preceded by a valid command word other than the valid verb, to convert the valid verb and the invalid object into a textual representation to be inserted as dictation; and prompting the user to select one of the valid objects that corresponds to the valid verb, to use with the valid verb, by rendering a list of at least some of the valid objects; if the user submits the additional utterance, inserting the textual representation of the valid verb and the invalid object into a displayed collection of text generated based on other utterances received from the user; and if the user selects one of the valid objects from the list, executing the action defined by the valid verb and selected valid object. 12. The method of claim 7 , wherein providing the inductive feedback comprises providing the inductive feedback in immediate response to the utterance without instructing the user to provide an additional utterance.

2. The computer implemented method of claim 1 , wherein the computer implemented method further comprises: responsive to receiving the hypertext request from the client, the server determining that a web server module is enabled, wherein looking up the hypertext document is in response to a determination that the web server module is enabled.

2. The computer implemented method of claim 1 , wherein the computer implemented method further comprises: responsive to receiving the hypertext request from the client, the server determining that a web server module is enabled, wherein looking up the hypertext document is in response to a determination that the web server module is enabled. 3. The computer implemented method of claim 2 , wherein determining that the web server module is enabled further comprises: the server parsing a configuration file for an indicator that the web server module is enabled.

6. The computer of claim 5 wherein said memory stores said performance metric data in a unique data structure in said non relational database file system, said one or more computer programs controlling said computer to record said metadata in said data structure by creating said data structure so as to have a separate to level directory for each day that stores all said performance attribute data gathered or measured on said day, said top level directory having a name and said name containing said date of said day in said name, and by creating a separate subdirectory in said top level directory for each resource instance, each said subdirectory storing one or more files each of said one or more files storing one or more time series of Unicode characters, each said time series of Unicode characters representing a time series of performance metric data numerical values, each said time series of performance metric data numerical values being measurements of one attribute in a group of attributes of said resource instance to which said subdirectory is devoted, each said files having a number of sections equal to said number of attributes in said group, each said section storing in a plurality of positions or storage locations said Unicode characters from one time series of Unicode characters representing a time series of performance metric numerical values measured in a plurality of time slots spanning said day to which said top level directory is devoted from said attribute to which said section is devoted, each said position or storage location storing one of said Unicode characters in said time series mapping to said time slot and said time of day during which said performance metric numerical value represented by said Unicode character was collected or measured, and wherein said one or more computer programs are structured to control said computer to implement said query definition language such that reverse mapping syntax building blocks exist which a user can use in said syntax specifying any search to specify a number or numerical range as part of said matching or filter condition in said regular expression of said search which performance metric data numerical values must match or fall within to qualify and be returned by said search as a search result, and wherein said one or more computer programs are structured to control said computer such that each said search which includes a number or numerical range specified with said reverse mapping syntax building block in said regular expression as part of said filtering condition, is carried out by mapping said number or numerical range to an equivalent Unicode character or an equivalent set or range of Unicode characters, and applying said filtering condition specified in said regular expression of said search to said relevant data by comparing said equivalent Unicode character or said equivalent set or range of Unicode characters to said relevant data retrieved from said memory.

6. The computer of claim 5 wherein said memory stores said performance metric data in a unique data structure in said non relational database file system, said one or more computer programs controlling said computer to record said metadata in said data structure by creating said data structure so as to have a separate to level directory for each day that stores all said performance attribute data gathered or measured on said day, said top level directory having a name and said name containing said date of said day in said name, and by creating a separate subdirectory in said top level directory for each resource instance, each said subdirectory storing one or more files each of said one or more files storing one or more time series of Unicode characters, each said time series of Unicode characters representing a time series of performance metric data numerical values, each said time series of performance metric data numerical values being measurements of one attribute in a group of attributes of said resource instance to which said subdirectory is devoted, each said files having a number of sections equal to said number of attributes in said group, each said section storing in a plurality of positions or storage locations said Unicode characters from one time series of Unicode characters representing a time series of performance metric numerical values measured in a plurality of time slots spanning said day to which said top level directory is devoted from said attribute to which said section is devoted, each said position or storage location storing one of said Unicode characters in said time series mapping to said time slot and said time of day during which said performance metric numerical value represented by said Unicode character was collected or measured, and wherein said one or more computer programs are structured to control said computer to implement said query definition language such that reverse mapping syntax building blocks exist which a user can use in said syntax specifying any search to specify a number or numerical range as part of said matching or filter condition in said regular expression of said search which performance metric data numerical values must match or fall within to qualify and be returned by said search as a search result, and wherein said one or more computer programs are structured to control said computer such that each said search which includes a number or numerical range specified with said reverse mapping syntax building block in said regular expression as part of said filtering condition, is carried out by mapping said number or numerical range to an equivalent Unicode character or an equivalent set or range of Unicode characters, and applying said filtering condition specified in said regular expression of said search to said relevant data by comparing said equivalent Unicode character or said equivalent set or range of Unicode characters to said relevant data retrieved from said memory. 7. The computer of claim 6 wherein said one or more computer programs are structured to control said computer to parse a search query which defines a first configuration attribute data search followed by a second performance metric data search and carry out said search query by controlling said computer to retrieve configuration attribute data of a configuration attribute specified in said first search which existed during said relevant interval for all instances of a resource type specified in said first search and apply a filter condition specified in said regular expression of said first search to said configuration attribute data, and return all instances of said resource type specified in said first search which meet said filter condition specified in said first search, and control said computer to retrieve from said memory Unicode characters representing performance metric attribute data gathered during said relevant interval for a performance metric attribute specified in said second search for all instances of a related resource type specified in said second search which are related to instances of said resource type specified in said first search which passed said filter or matching condition specified in said first search and apply a filter condition specified in said second search to said Unicode characters retrieved from said memory representing said performance metric data numerical values of said performance metric attribute specified in said second search of said instances of said related resource type specified in said second search, and return all instance of said related resource type specified in said second search which meet said filter condition specified in said second search.

104. The system of claim 103 wherein determining comprises predicting an average precision of the search query using a combination of at least one temporal feature of the temporal profile and a content feature of documents retrieved in response to the search query.

104. The system of claim 103 wherein determining comprises predicting an average precision of the search query using a combination of at least one temporal feature of the temporal profile and a content feature of documents retrieved in response to the search query. 108. The system of claim 104 wherein predicting the average precision comprises using a learning algorithm.

12. One or more computing devices having stored thereupon a plurality of computer-executable instructions that, when executed by a processor, causes the processor to perform operations comprising: analyzing a plurality of labeled accounts from one or more sources, each of the plurality of labeled accounts indicating that a respective labeled account is malicious or benign; determining one or more features extracted from the plurality of accounts that distinguish a respective labeled account that is malicious and a respective labeled account that is benign, wherein at least one of the one or more features is based on memorability of email addresses, the memorability relating to a pattern of symmetry, anti-symmetry, or uniformly distanced characters in the email address; applying one or more machine learning methods to build a classification model based on the obtained one or more features; and using the classification model to determine a trust level of an incoming account.

12. One or more computing devices having stored thereupon a plurality of computer-executable instructions that, when executed by a processor, causes the processor to perform operations comprising: analyzing a plurality of labeled accounts from one or more sources, each of the plurality of labeled accounts indicating that a respective labeled account is malicious or benign; determining one or more features extracted from the plurality of accounts that distinguish a respective labeled account that is malicious and a respective labeled account that is benign, wherein at least one of the one or more features is based on memorability of email addresses, the memorability relating to a pattern of symmetry, anti-symmetry, or uniformly distanced characters in the email address; applying one or more machine learning methods to build a classification model based on the obtained one or more features; and using the classification model to determine a trust level of an incoming account. 14. The one or more computing devices as recited in claim 12 , wherein the one or more operations further comprise: comparing the trust level of the incoming account determined by the classification model with a ground truth of the trust level of the incoming account; and improving the classification model based on a result of the comparison.

1. A system for transforming media elements into a narrative comprising: a processor; a memory in communication with the processor; a clustering module in communication with the processor and the memory, the clustering module configured to: receive a dataset comprising a plurality of media elements each comprising metadata; and organize the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and a narrative module in communication with the processor and the memory, the narrative module configured to create a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result: T>SI+GI+TI+P min +SE guess .

1. A system for transforming media elements into a narrative comprising: a processor; a memory in communication with the processor; a clustering module in communication with the processor and the memory, the clustering module configured to: receive a dataset comprising a plurality of media elements each comprising metadata; and organize the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and a narrative module in communication with the processor and the memory, the narrative module configured to create a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result: T>SI+GI+TI+P min +SE guess . 12. The system of claim 1 , further comprising a representation module in communication with the processor and the memory, the representation module configured to identify external information relevant to the narrative sequence; wherein the narrative module is further configured to incorporate the external information into the narrative sequence.

18. A system for computing a solution to a query formulated against a knowledge base (KB), comprising: a memory; and at least one processor coupled to the memory and operative to: receive a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto; ignore each probability value of the one or more axioms and computing a solution to the query; compute each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution; and use each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution.

18. A system for computing a solution to a query formulated against a knowledge base (KB), comprising: a memory; and at least one processor coupled to the memory and operative to: receive a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto; ignore each probability value of the one or more axioms and computing a solution to the query; compute each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution; and use each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution. 20. The system of claim 18 , wherein the at least one processor coupled to the memory is further operative to output the query solution to a display.

10. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform: receive a request for map route data, the request having a type; determine the type of the request, wherein the type of request is (a) a display request, (b) a route request, (c) a name request, or (d) some combination thereof; generate a structured query based on the request; generate a virtual table in response to the structured query, the virtual table generated based on (a) one or more parameters determined based on the type of the request and (b) map route data stored in a navigation database coupled with the processor, the generated virtual table comprises at least a subset of map route data stored in the navigation database but is not part of the schema of the navigation database, the constructed virtual table and the navigation database being accessible via a same query format; query the virtual table using the request for map route data in the query format to obtain the requested map route data therefrom; and generate a map command based on the obtained map route data in the virtual table corresponding to the request for map route data.

10. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform: receive a request for map route data, the request having a type; determine the type of the request, wherein the type of request is (a) a display request, (b) a route request, (c) a name request, or (d) some combination thereof; generate a structured query based on the request; generate a virtual table in response to the structured query, the virtual table generated based on (a) one or more parameters determined based on the type of the request and (b) map route data stored in a navigation database coupled with the processor, the generated virtual table comprises at least a subset of map route data stored in the navigation database but is not part of the schema of the navigation database, the constructed virtual table and the navigation database being accessible via a same query format; query the virtual table using the request for map route data in the query format to obtain the requested map route data therefrom; and generate a map command based on the obtained map route data in the virtual table corresponding to the request for map route data. 11. The apparatus of claim 10 , wherein the display request further includes a tile render request, a region render request, a tile vector request, or some combination thereof.

5. A method for mapping document style web services 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; 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; validating the XML document by the XML schema to generate a PSVI annotation of the XML document; 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; and mapping element and attribute nodes to ontology property instances; 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; and 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, b) 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; e) wherein this mapping is performed dynamically while evaluating a query inquiring data from the XML document.

5. A method for mapping document style web services 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; 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; validating the XML document by the XML schema to generate a PSVI annotation of the XML document; 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; and mapping element and attribute nodes to ontology property instances; 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; and 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, b) 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; e) wherein this mapping is performed dynamically while evaluating a query inquiring data from the XML document. 6. The method according claim 5 characterized in that for mapping an XML web service to an ontology the following steps are performed: providing an XML SOAP (Simple Object Access Protocol) web service with a corresponding web service description (WSDL); a) mapping the WSDL definitions to ontology schema definitions in the following way: mapping an operation definition to a class definition of the ontology; mapping a part definition to an ontology property definition; b) the input and output message of the SOAP request are mapped in the following way to ontology instances: a single SOAP request is mapped to a single ontology class instance; the element nodes representing the parts of the input and output message are mapped to ontology property instances.

1. A computer-implemented method of providing metadata associated with a file stored on a cloud storage system to a first application, comprising: receiving a request, from a user, to edit metadata associated with the file; identifying the first application, wherein the first application generates the request; dividing the metadata associated with the file into a first set of metadata categories and a second set of metadata categories, wherein the first set of metadata categories is associated with the first application and the second set of metadata categories is not associated with the first application; filtering the first set of metadata categories to obtain filtered metadata containing metadata associated with the file; providing the filtered metadata to the first application; receiving edits from the user, via the first application, to metadata associated with the first file; determining the category of metadata of the received edits and: in response to determining that the received edits belong to the first set of metadata categories, applying the edits to the metadata category; and in response to determining that the category of the metadata does not exist, generating a new metadata category associated only with the application in the first set of metadata categories.

1. A computer-implemented method of providing metadata associated with a file stored on a cloud storage system to a first application, comprising: receiving a request, from a user, to edit metadata associated with the file; identifying the first application, wherein the first application generates the request; dividing the metadata associated with the file into a first set of metadata categories and a second set of metadata categories, wherein the first set of metadata categories is associated with the first application and the second set of metadata categories is not associated with the first application; filtering the first set of metadata categories to obtain filtered metadata containing metadata associated with the file; providing the filtered metadata to the first application; receiving edits from the user, via the first application, to metadata associated with the first file; determining the category of metadata of the received edits and: in response to determining that the received edits belong to the first set of metadata categories, applying the edits to the metadata category; and in response to determining that the category of the metadata does not exist, generating a new metadata category associated only with the application in the first set of metadata categories. 3. The method of claim 1 , wherein at least one metadata category in the first set of metadata categories is only associated with the first application.

13. A non-transitory computer-readable storage medium comprising computer program instructions that, when executed on at least one processor in a computer, perform a method of synchronizing visual and speech events in a multimodal application, the method comprising: calling a voice form of the multimodal application, wherein the multimodal application provides a multimodal web page to a client device over a network; receiving speech from a user; determining a semantic interpretation of the speech; calling a global application update handler of the multimodal application including exiting a voice form; identifying, by the global application update handler, an additional processing function in dependence upon the semantic interpretation; executing the additional processing function; updating a visual element after executing the additional processing function; updating a voice form after executing the additional processing function; and restarting the voice form after executing the additional processing function, wherein determining a semantic interpretation of the speech comprises determining a plurality of semantic interpretations of the speech, and wherein identifying, by the global application update handler, an additional processing function in dependence upon the semantic interpretation comprises identifying, by the global application update handler, an additional processing function for each of the plurality of semantic interpretations.

13. A non-transitory computer-readable storage medium comprising computer program instructions that, when executed on at least one processor in a computer, perform a method of synchronizing visual and speech events in a multimodal application, the method comprising: calling a voice form of the multimodal application, wherein the multimodal application provides a multimodal web page to a client device over a network; receiving speech from a user; determining a semantic interpretation of the speech; calling a global application update handler of the multimodal application including exiting a voice form; identifying, by the global application update handler, an additional processing function in dependence upon the semantic interpretation; executing the additional processing function; updating a visual element after executing the additional processing function; updating a voice form after executing the additional processing function; and restarting the voice form after executing the additional processing function, wherein determining a semantic interpretation of the speech comprises determining a plurality of semantic interpretations of the speech, and wherein identifying, by the global application update handler, an additional processing function in dependence upon the semantic interpretation comprises identifying, by the global application update handler, an additional processing function for each of the plurality of semantic interpretations. 16. The non-transitory computer-readable storage medium claim 13 , wherein calling the global application update handler comprises calling the global application update handler as a result of an event invoked upon a return of the semantic interpretation of the speech.

1. A computer based assessment tool for providing a current project status and predicting a future project status, the tool comprising: a computer memory storing a project ontology framework (POF), wherein the POF has at least one class and subclass; one or more computer processors configured to: classify a plurality of incoming messages into a class or subclass within the POF based on a source of each of the messages and assign a confidence level to each of the incoming messages based on the classification; extracting the current project status from the plurality of incoming messages based on the source and the assigned confidence level of each of the incoming messages; input first classified messages with a first assigned confidence level into a matching function that: compares the first classified messages to pre-stored data formatted according to the POF, generates a match score, and modifies an operation of the POF when the match score exceeds a certain threshold; inputs second classified messages with a second assigned confidence level to a mapping function that: formats the second classified messages according to at least one class within the POF, and inputs the formatted second classified messages into the matching function; inputs third classified messages with a third assigned confidence level into a parsing function that: parses words and phrases in the third classified messages, generates tags identifying attributes of the parsed words and phrases in the third classified messages, and inputs the third classified messages with the tags into the mapping function, and inputs results of the mapping function corresponding to the third classified messages with the tags into the matching function; predicts the future project status based on match score of each of the plurality of incoming messages based on the matching function; generates a status matrix providing a multi-relational representation of the current project status and predicted future project status; and a display configured to display the status matrix.

1. A computer based assessment tool for providing a current project status and predicting a future project status, the tool comprising: a computer memory storing a project ontology framework (POF), wherein the POF has at least one class and subclass; one or more computer processors configured to: classify a plurality of incoming messages into a class or subclass within the POF based on a source of each of the messages and assign a confidence level to each of the incoming messages based on the classification; extracting the current project status from the plurality of incoming messages based on the source and the assigned confidence level of each of the incoming messages; input first classified messages with a first assigned confidence level into a matching function that: compares the first classified messages to pre-stored data formatted according to the POF, generates a match score, and modifies an operation of the POF when the match score exceeds a certain threshold; inputs second classified messages with a second assigned confidence level to a mapping function that: formats the second classified messages according to at least one class within the POF, and inputs the formatted second classified messages into the matching function; inputs third classified messages with a third assigned confidence level into a parsing function that: parses words and phrases in the third classified messages, generates tags identifying attributes of the parsed words and phrases in the third classified messages, and inputs the third classified messages with the tags into the mapping function, and inputs results of the mapping function corresponding to the third classified messages with the tags into the matching function; predicts the future project status based on match score of each of the plurality of incoming messages based on the matching function; generates a status matrix providing a multi-relational representation of the current project status and predicted future project status; and a display configured to display the status matrix. 6. The computer based assessment tool of claim 1 , wherein the POF is broken down into multiple classes including at least lexicon, portfolios, project templates, activities and roles.

12. The system of claim 8 , wherein the at least one of the set of custom publication units that includes the additional content includes both the additional content and at least one of the copied, selected units of content.

12. The system of claim 8 , wherein the at least one of the set of custom publication units that includes the additional content includes both the additional content and at least one of the copied, selected units of content. 14. The system of claim 12 , wherein the additional content is a reference to a source of the at least one of the copied, selected units of content.