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27. A computer-implemented method comprising: enabling, using a computing device, secure information transfer between a web browser's scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, said enabling the at least one object to be returned cross-domain enabling return of a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine.

27. A computer-implemented method comprising: enabling, using a computing device, secure information transfer between a web browser's scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, said enabling the at least one object to be returned cross-domain enabling return of a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 28. The computer-implemented method of claim 27 , further comprising: enabling the scripting engine to access to at least one property descriptor.

1. In combination in an automated editing system, text supplying means for serially supplying alpha-numeric characters and encoded control characters, first data storage means, a central processor for receiving and assembling said characters serially supplied by said text supplying means, storage means for storing said assembled characters in said first storage means, the improvement comprising means for supplying to said central processor in batched form editing commands for editing the text represented by the characters stored in said storage means, second storage means for storing signals representative of said editing commands, third storage means, and means connected to said storage means and said second and third storage means for operating upon said stored characters and said stored editing commands for generating a revised ensemble of alpha-numeric and control characters and for storing said revised character ensemble in said third storage means.

1. In combination in an automated editing system, text supplying means for serially supplying alpha-numeric characters and encoded control characters, first data storage means, a central processor for receiving and assembling said characters serially supplied by said text supplying means, storage means for storing said assembled characters in said first storage means, the improvement comprising means for supplying to said central processor in batched form editing commands for editing the text represented by the characters stored in said storage means, second storage means for storing signals representative of said editing commands, third storage means, and means connected to said storage means and said second and third storage means for operating upon said stored characters and said stored editing commands for generating a revised ensemble of alpha-numeric and control characters and for storing said revised character ensemble in said third storage means. 4. A combination as in claim 1 wherein said first and second storage means comprise parallel tracks of a magnetic tape.

18. The non-transitory memory device of claim 15 , where the one or more instructions, to determine the plurality of word hypotheses for the voice query, further include: one or more instructions that, when executed by one or more processors, cause the one or more processors to: identify a language, of a plurality of languages, associated with the voice query; and determine the plurality of word hypotheses based on the identified language.

18. The non-transitory memory device of claim 15 , where the one or more instructions, to determine the plurality of word hypotheses for the voice query, further include: one or more instructions that, when executed by one or more processors, cause the one or more processors to: identify a language, of a plurality of languages, associated with the voice query; and determine the plurality of word hypotheses based on the identified language. 19. The non-transitory memory device of claim 18 , where the one or more instructions, to determine the respective weights, further include: one or more instructions that, when executed by one or more processors, cause the one or more processors to: determine the respective weights based on a language model associated with the language.

1. A method comprising: identifying, by one or more devices, documents relating to a query; generating, by the one or more devices, a plurality of substrings from the query; calculating, by the one or more devices and for a particular substring of the plurality of substrings, a value that corresponds to a comparison between the identified documents and the particular substring; determining, by the one or more devices, that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; selecting, by the one or more devices and from two or more of the plurality of substrings, the particular substring as a semantic unit based on the calculated value for the particular substring satisfying the particular threshold; and obtaining, by the one or more devices, a refined list of documents by refining the identified documents based on the semantic unit.

1. A method comprising: identifying, by one or more devices, documents relating to a query; generating, by the one or more devices, a plurality of substrings from the query; calculating, by the one or more devices and for a particular substring of the plurality of substrings, a value that corresponds to a comparison between the identified documents and the particular substring; determining, by the one or more devices, that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; selecting, by the one or more devices and from two or more of the plurality of substrings, the particular substring as a semantic unit based on the calculated value for the particular substring satisfying the particular threshold; and obtaining, by the one or more devices, a refined list of documents by refining the identified documents based on the semantic unit. 5. The method of claim 1 , where identifying the documents includes: identifying the documents relating to the query by comparing search terms in the query to an index of a corpus.

2. The method of claim 1, wherein the selection of templates further includes the selection of drug information relating to side effects and contraindications.

2. The method of claim 1, wherein the selection of templates further includes the selection of drug information relating to side effects and contraindications. 3. The method of claim 2, wherein the selection of drug information causes the display of the selected drug information.

1. A baggage system comprising: a plurality of radio-frequency identification (RFID) chips, wherein at least a first RFID chip of the plurality of RFID chips is a passive-type RFID chip and associated with a baggage item; a data collection engine (DCE) device communicating with the plurality of RFID chips, wherein the DCE comprises: a power transmission subsystem including a power source and an antenna arranged to wirelessly transmit power from the power source to the first RFID chip; a transceiver configured to receive first data from at least one of the first RFID chip and a second RFID chip of the plurality of RFID chips while the first RFID chip is activated by the power received, the first data including identification information of the at least one of the first and second RFID chips; a controller operatively coupled to the transceiver; and one or more memory sources operatively coupled to the controller, the one or more memory sources including instructions for configuring the controller to generate one or more messages indicative of the identification information to be sent by the transceiver to a server device via the network connection, wherein the first RFID chip includes an antenna for wirelessly receiving the power from the transceiver of the DCE and control logic for generating the identification information; wherein the server device comprises: a transceiver configured to receive the one or more messages from the DCE; a controller operatively coupled to the transceiver; and one or more memory sources operatively coupled to the controller, the one or more memory sources configuring the controller to generate a message indicative of location information associated with the baggage item.

1. A baggage system comprising: a plurality of radio-frequency identification (RFID) chips, wherein at least a first RFID chip of the plurality of RFID chips is a passive-type RFID chip and associated with a baggage item; a data collection engine (DCE) device communicating with the plurality of RFID chips, wherein the DCE comprises: a power transmission subsystem including a power source and an antenna arranged to wirelessly transmit power from the power source to the first RFID chip; a transceiver configured to receive first data from at least one of the first RFID chip and a second RFID chip of the plurality of RFID chips while the first RFID chip is activated by the power received, the first data including identification information of the at least one of the first and second RFID chips; a controller operatively coupled to the transceiver; and one or more memory sources operatively coupled to the controller, the one or more memory sources including instructions for configuring the controller to generate one or more messages indicative of the identification information to be sent by the transceiver to a server device via the network connection, wherein the first RFID chip includes an antenna for wirelessly receiving the power from the transceiver of the DCE and control logic for generating the identification information; wherein the server device comprises: a transceiver configured to receive the one or more messages from the DCE; a controller operatively coupled to the transceiver; and one or more memory sources operatively coupled to the controller, the one or more memory sources configuring the controller to generate a message indicative of location information associated with the baggage item. 2. The baggage system of claim 1 , wherein in the server device: the one or more memory sources further store a trained model for generating an output value corresponding to a present event based upon at least the identification information; the one or more memory sources further store a plurality of past events, each of the plurality of past events including a plurality of input attributes and a quantifiable outcome; and the controller further configured to: train a neural network model (NNM) to generate the trained model, wherein the training of the NNM includes: performing pre-processing on the plurality of input attributes for each of the plurality of past events to generate a plurality of input data sets; dividing the plurality of past events into a first set of training data and a second set of validation data; iteratively performing a machine learning algorithm (MLA) to update synaptic weights of the NNM based upon the training data; and validating the NNM based upon the second set of validation data.

4. The method of claim 3 further comprises extracting, by the service event generator, a service measure from the transaction trace data; determining, by the service event generator, whether there is an anomaly with the service measure; and generating, by the service event generator, an incoming event record for the service measure in response to a determination of an anomaly in the service measure.

4. The method of claim 3 further comprises extracting, by the service event generator, a service measure from the transaction trace data; determining, by the service event generator, whether there is an anomaly with the service measure; and generating, by the service event generator, an incoming event record for the service measure in response to a determination of an anomaly in the service measure. 5. The method of claim 4 further comprises receiving, by an infrastructure topology data processor, infrastructure topology data, where the infrastructure topology data identifies a new entity in the topology model or a new relationship between entities in the topology model and is generated by an infrastructure agent instrumented in an entity in the distributed computing environment; and updating, by the infrastructure topology data processor, the topology model using the infrastructure topology data.

1. A solid state memory device, comprising: multiple data blocks, each block comprising an array of memory cells arranged in a plurality of pages; encoder circuitry configured to encode data into inner code words and symbol-based outer code words; and modulator circuitry configured to store the inner code words and the symbol-based outer code words in the memory cells of the multiple blocks, the modulator circuitry configured to store one or more inner code words in each page of each block and to store one or more symbols of each outer code word in at least one page of each block.

1. A solid state memory device, comprising: multiple data blocks, each block comprising an array of memory cells arranged in a plurality of pages; encoder circuitry configured to encode data into inner code words and symbol-based outer code words; and modulator circuitry configured to store the inner code words and the symbol-based outer code words in the memory cells of the multiple blocks, the modulator circuitry configured to store one or more inner code words in each page of each block and to store one or more symbols of each outer code word in at least one page of each block. 8. The device of claim 1 , wherein the memory cells comprise multiple level memory cells capable of storing x bits, where x>1.

8. A computer system for establishing personalized limits on a search responsive to a key word query to an enterprise search system, the computer system including one or more processors configured to perform operations including: receiving an object types access history for at least one=particular user; wherein the object types access history includes records of object types selected by the particular user from search results returning multiple object types and records of object types selected by the particular user via interfaces other than search results; and determining and storing in computer readable memory a personalized scope of object types by analyzing frequencies of individual object type selections in the object types access history; wherein the personalized scope limits individual object types initially returned by an enterprise search system to object types that have frequencies above a pre-determined threshold in response to key word queries by the particular user that do not specify object types to search.

8. A computer system for establishing personalized limits on a search responsive to a key word query to an enterprise search system, the computer system including one or more processors configured to perform operations including: receiving an object types access history for at least one=particular user; wherein the object types access history includes records of object types selected by the particular user from search results returning multiple object types and records of object types selected by the particular user via interfaces other than search results; and determining and storing in computer readable memory a personalized scope of object types by analyzing frequencies of individual object type selections in the object types access history; wherein the personalized scope limits individual object types initially returned by an enterprise search system to object types that have frequencies above a pre-determined threshold in response to key word queries by the particular user that do not specify object types to search. 14. The computer system of claim 8 , wherein the processors configured to further perform operations including: determining and storing in computer readable memory a personalized ordering of object types for the at least one particular user using the object types access history; wherein the personalized ordering of object types sets an order in which to present search results from the search performed by the enterprise search system.

15. A content management system, comprising: one or more processors; and a computer-readable medium including one or more sequences of instructions that, when executed by the one or more processors, causes: receiving a first message from a collaboration system remote from a content management system, the first message including document metadata corresponding to a document generated by the content management system and stored therein; synchronizing the first reference to the document with a first client device, such that the first reference is stored via a local file system managed by the first client as a first local reference to the document; mapping the first reference in the content management system to the first local reference in the first client device; in response to receiving the first message, creating, in the content management system, a first reference to the document of the collaboration system and saving the document metadata received in the first message as metadata for the first reference; synchronizing the first reference metadata with the first client device detecting a second reference to the document in the collaboration system as a result of the first client device sharing the first local reference with a second client device; updating the mapping between the first reference and the first local reference, such that the second reference is stored via a second local file system managed by the second client as a second local reference to the document; and upon detecting a change by the first client device to the first reference to the document, synchronizing the change with the second local reference to the document.

15. A content management system, comprising: one or more processors; and a computer-readable medium including one or more sequences of instructions that, when executed by the one or more processors, causes: receiving a first message from a collaboration system remote from a content management system, the first message including document metadata corresponding to a document generated by the content management system and stored therein; synchronizing the first reference to the document with a first client device, such that the first reference is stored via a local file system managed by the first client as a first local reference to the document; mapping the first reference in the content management system to the first local reference in the first client device; in response to receiving the first message, creating, in the content management system, a first reference to the document of the collaboration system and saving the document metadata received in the first message as metadata for the first reference; synchronizing the first reference metadata with the first client device detecting a second reference to the document in the collaboration system as a result of the first client device sharing the first local reference with a second client device; updating the mapping between the first reference and the first local reference, such that the second reference is stored via a second local file system managed by the second client as a second local reference to the document; and upon detecting a change by the first client device to the first reference to the document, synchronizing the change with the second local reference to the document. 21. The content management system of claim 15 , wherein the content management system synchronizes first metadata for a content item of a first type in the content management system with second metadata of a content item of a second type in the collaboration system.

35. A digital image processing device comprising a circuit for: executing a pre-scan of a document, on which document the user has marked a plurality of document blocks, and creating pre-scan image data from which pre-scan image data the plurality of document blocks that is marked by the user are detected; extracting the plurality of document blocks that are digital image data representing a portion of the scanned document, the scanned document having document images and a background, the plurality of document blocks includes document image data and background image data, the document image data represents some of the document images on the scanned document, wherein all the document image data in the plurality of document blocks represents fewer document images than are present in the scanned document, the plurality of document blocks being identified by the perimeter and containing a specific image to be processed, the perimeter being established by the user beforehand; generating character code data for character images within the plurality of document blocks; reconstructing the plurality of document blocks into a single document block in a specific shape based on the plurality of extracted document blocks; and laying out the character code data within the reconstructed document block to create a layout image.

35. A digital image processing device comprising a circuit for: executing a pre-scan of a document, on which document the user has marked a plurality of document blocks, and creating pre-scan image data from which pre-scan image data the plurality of document blocks that is marked by the user are detected; extracting the plurality of document blocks that are digital image data representing a portion of the scanned document, the scanned document having document images and a background, the plurality of document blocks includes document image data and background image data, the document image data represents some of the document images on the scanned document, wherein all the document image data in the plurality of document blocks represents fewer document images than are present in the scanned document, the plurality of document blocks being identified by the perimeter and containing a specific image to be processed, the perimeter being established by the user beforehand; generating character code data for character images within the plurality of document blocks; reconstructing the plurality of document blocks into a single document block in a specific shape based on the plurality of extracted document blocks; and laying out the character code data within the reconstructed document block to create a layout image. 37. A digital image processing device as claimed in claim 35 , wherein the character code includes at least font size.

8. A polyaxial bone screw assembly comprising: a) a closure including an outer fastener ring and an inner fastener ring, the closure rings positioned entirely within a bore of a receiver member having a mating helically wound guide and advancement structure thereon; wherein: b) the outer fastener ring includes a base with a first outer surface having a first outer helically wound guide and advancement structure thereon, an inner bore having an internal helically wound guide and advancement structure thereon, and a bottom surface joining the first outer surface and the inner bore; the bottom surface being positioned to directly engage upright arms of a lower pressure insert so as to be able to apply a downward pressure directly to the lower pressure insert as the outer fastener ring is advanced in the receiver; c) the inner fastener ring is located within the inner bore and includes a second outer surface having a second outer guide and advancement structure thereon, the second outer guide and advancement structure being sized and shaped so as to rotatingly mate with the internal guide and advancement structure of the inner bore, and a lower surface portion with a centrally located lower through-bore located therein; and d) the inner fastener ring lower through bore being sized and shaped to slidingly and rotatably receive an upward projecting structure located on a pressure insert positioned beneath the closure to allow the closure to rotate while holding the insert in position to translate the insert downwardly without the insert rotating.

8. A polyaxial bone screw assembly comprising: a) a closure including an outer fastener ring and an inner fastener ring, the closure rings positioned entirely within a bore of a receiver member having a mating helically wound guide and advancement structure thereon; wherein: b) the outer fastener ring includes a base with a first outer surface having a first outer helically wound guide and advancement structure thereon, an inner bore having an internal helically wound guide and advancement structure thereon, and a bottom surface joining the first outer surface and the inner bore; the bottom surface being positioned to directly engage upright arms of a lower pressure insert so as to be able to apply a downward pressure directly to the lower pressure insert as the outer fastener ring is advanced in the receiver; c) the inner fastener ring is located within the inner bore and includes a second outer surface having a second outer guide and advancement structure thereon, the second outer guide and advancement structure being sized and shaped so as to rotatingly mate with the internal guide and advancement structure of the inner bore, and a lower surface portion with a centrally located lower through-bore located therein; and d) the inner fastener ring lower through bore being sized and shaped to slidingly and rotatably receive an upward projecting structure located on a pressure insert positioned beneath the closure to allow the closure to rotate while holding the insert in position to translate the insert downwardly without the insert rotating. 11. The assembly of claim 8 , further comprising the upper compression structure including: a) the upwardly projecting structure is a pin that extends upwardly and is sized and shaped to engage the inner fastener lower through-bore; and b) a pair of downwardly extending leg portions joined by a lower U-shaped surface so as to be adapted to engage and partially encircle the connecting member.

15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list.

15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list. 23. The apparatus of claim 15 , further comprising: a module for resolving frequency collisions when two words in said list have equal frequency counts by ordering said most recently selected word first.

10. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the stored program logic comprising: document identifying logic executed by the processor for identifying documents relating to a search category; document analyzing logic executed by the processor for analyzing the documents to determine internal statistical content; interestingness tracking logic executed by the processor for tracking users' interestingness data for the documents, where the tracking of the users' interestingness data comprises tracking user interaction with each document clicked through from a search result page, the tracking of the user interaction with each document comprising determining a user interaction data group including one or more of measuring how fast a user reads the each document based on page scroll speed and average reading time based on length of the each document, whether the user chose to cut and paste a portion of the document for further reading, whether the user bookmarked the each document, or combinations thereof; first query term identifying logic executed by the processor for identifying first query terms from the documents; second query term tracking logic executed by the processor for tracking second query terms specified by the users; interest tracking logic executed by the processor for tracking users' indication of interest in pairs of query terms; query suggestion tracking logic executed by the processor for tracking a query suggestion selected from a plurality of query suggestions and obtained from the first query terms, the second query terms, and the users' indication of interest in pairs of query terms; search results web page generating logic executed by the processor for generating the search results page from the interaction with the each document and documents comprising a search result in the identified documents, ordered in a determined order, wherein the search results page comprises the plurality of query suggestions.

10. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the stored program logic comprising: document identifying logic executed by the processor for identifying documents relating to a search category; document analyzing logic executed by the processor for analyzing the documents to determine internal statistical content; interestingness tracking logic executed by the processor for tracking users' interestingness data for the documents, where the tracking of the users' interestingness data comprises tracking user interaction with each document clicked through from a search result page, the tracking of the user interaction with each document comprising determining a user interaction data group including one or more of measuring how fast a user reads the each document based on page scroll speed and average reading time based on length of the each document, whether the user chose to cut and paste a portion of the document for further reading, whether the user bookmarked the each document, or combinations thereof; first query term identifying logic executed by the processor for identifying first query terms from the documents; second query term tracking logic executed by the processor for tracking second query terms specified by the users; interest tracking logic executed by the processor for tracking users' indication of interest in pairs of query terms; query suggestion tracking logic executed by the processor for tracking a query suggestion selected from a plurality of query suggestions and obtained from the first query terms, the second query terms, and the users' indication of interest in pairs of query terms; search results web page generating logic executed by the processor for generating the search results page from the interaction with the each document and documents comprising a search result in the identified documents, ordered in a determined order, wherein the search results page comprises the plurality of query suggestions. 19. The system of claim 10 , wherein the second query terms comprise search terms used to initiate search sessions.

1. A computer implemented method of constructing formal definitions in intelligent glossaries for interpreting text, said method comprising the steps of: providing at least one distinction, wherein each distinction has a boundary, an indication, a counter-indication and a frame; modeling each said distinction as a diagram to provide a distinction model; verifying each distinction model as being an instantiation of a generic distinction pattern to provide a verified distinction model; providing at least one arrangement, wherein each arrangement is made of nonintersecting marks of distinction containing indications from said verified distinction model; writing at least one formulation for each indication appearing in said verified distinction model and arrangement, providing well-founded indications; calculating precise formulations in natural language from well-founded indications by performing at least one of the steps of substituting variables symbols and replacing constants symbols to transform imprecise formulations into precise formulations; selecting a definition type, wherein said definition type is selected from the group consisting of terminologies, assertions, and theorems; embedding at least one said precise formulation and definition type as a formal definition in an intelligent glossary to provide computerized semantic systems of intelligent glossaries.

1. A computer implemented method of constructing formal definitions in intelligent glossaries for interpreting text, said method comprising the steps of: providing at least one distinction, wherein each distinction has a boundary, an indication, a counter-indication and a frame; modeling each said distinction as a diagram to provide a distinction model; verifying each distinction model as being an instantiation of a generic distinction pattern to provide a verified distinction model; providing at least one arrangement, wherein each arrangement is made of nonintersecting marks of distinction containing indications from said verified distinction model; writing at least one formulation for each indication appearing in said verified distinction model and arrangement, providing well-founded indications; calculating precise formulations in natural language from well-founded indications by performing at least one of the steps of substituting variables symbols and replacing constants symbols to transform imprecise formulations into precise formulations; selecting a definition type, wherein said definition type is selected from the group consisting of terminologies, assertions, and theorems; embedding at least one said precise formulation and definition type as a formal definition in an intelligent glossary to provide computerized semantic systems of intelligent glossaries. 11. A computer implemented method as in claim 1 , further comprising the steps of writing formulations in natural language by inserting syntactically a at least one identifier or symbol in or around other natural language writings.

6. The apparatus of claim 1 further comprising a computer program subroutine for displaying of said modified and/or unmodified auxiliary information component at the time an undesirable word or phrase is replaced.

6. The apparatus of claim 1 further comprising a computer program subroutine for displaying of said modified and/or unmodified auxiliary information component at the time an undesirable word or phrase is replaced. 7. The apparatus of claim 6 wherein: said microcomputer is programmed to selectively provide different levels of operation with respect to the displaying of said modified auxiliary information component which include: (1) a full captioning level in which all modified or unmodified auxiliary information data is displayed; (2) a normal captioning level in which only modified words or phrases which represent the replacement words or phrases are displayed; and, (3) a no captioning level in which no word or phrase is displayed.

17. A method performed by data processing apparatus, the method comprising: selecting a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item and a resource identifier for each initial label, wherein each initial label includes one or more words; selecting one or more sets of matching web pages from the plurality of web pages, wherein each set of matching web pages includes two or more matching web pages; grouping, for each set of matching web pages, initial labels that are associated with the set of matching web pages into a separate initial label group that corresponds to the set of matching web pages; selecting one or more sets of matching labels, wherein each set of matching labels includes two or more initial labels; grouping each set of matching labels into a separate initial label group that corresponds to the set of matching labels; and selecting, as a final label for the non-text content item, an n-gram of one or more words that are included in at least a threshold number of separate initial label groups.

17. A method performed by data processing apparatus, the method comprising: selecting a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item and a resource identifier for each initial label, wherein each initial label includes one or more words; selecting one or more sets of matching web pages from the plurality of web pages, wherein each set of matching web pages includes two or more matching web pages; grouping, for each set of matching web pages, initial labels that are associated with the set of matching web pages into a separate initial label group that corresponds to the set of matching web pages; selecting one or more sets of matching labels, wherein each set of matching labels includes two or more initial labels; grouping each set of matching labels into a separate initial label group that corresponds to the set of matching labels; and selecting, as a final label for the non-text content item, an n-gram of one or more words that are included in at least a threshold number of separate initial label groups. 26. The method of claim 17 , wherein receiving label data that includes a set of initial labels comprises receiving metadata for the web page with which the non-text content item is associated.

5. The method of claim 1 wherein the actions are traversals.

5. The method of claim 1 wherein the actions are traversals. 6. The method of claim 5 wherein the web content is a web destination associated with a traversal.

1. A method for arranging content in an electronic page, the method comprising: identifying a plurality of objects on the electronic page; forming a membrane for each identified object by setting a geometric shape around each identified object, wherein forming the membrane comprises generating guidelines for each identified object, wherein generating the guidelines further comprises associating a gravity distance with each of the generated guidelines; receiving an entry of an insertion point in the electronic page; and aligning the insertion point based on at least one of the guidelines, wherein aligning the insertion point based on at least one of the guidelines comprises: determining a plurality of guidelines from the generated guidelines having the gravity distance extending to the point of insertion, and selecting a dominant guideline from the plurality of guidelines, wherein selecting the dominant guideline comprises: determining a guideline hierarchy associated with each of the plurality of guidelines based on the gravity distance associated with each of the plurality of guidelines and a position of the insertion point relative to each of the plurality of guidelines, and selecting the dominant guideline from the plurality of guidelines based on the determined guideline hierarchy; and aligning the insertion point relative to the selected dominant guideline.

1. A method for arranging content in an electronic page, the method comprising: identifying a plurality of objects on the electronic page; forming a membrane for each identified object by setting a geometric shape around each identified object, wherein forming the membrane comprises generating guidelines for each identified object, wherein generating the guidelines further comprises associating a gravity distance with each of the generated guidelines; receiving an entry of an insertion point in the electronic page; and aligning the insertion point based on at least one of the guidelines, wherein aligning the insertion point based on at least one of the guidelines comprises: determining a plurality of guidelines from the generated guidelines having the gravity distance extending to the point of insertion, and selecting a dominant guideline from the plurality of guidelines, wherein selecting the dominant guideline comprises: determining a guideline hierarchy associated with each of the plurality of guidelines based on the gravity distance associated with each of the plurality of guidelines and a position of the insertion point relative to each of the plurality of guidelines, and selecting the dominant guideline from the plurality of guidelines based on the determined guideline hierarchy; and aligning the insertion point relative to the selected dominant guideline. 12. The method of claim 1 , wherein associating the gravity distance with each of the generated guidelines comprises associating the gravity distance according to one of the following: a preset system parameter, a user preference, and the electronic page needs.

1. A computer implemented method of converting one or more electronic music files into an electronic musical representation, the computer implemented method comprising the steps of: (a) providing a song framework including a plurality of song framework rules and associated processing steps for converting a one or more track electronic music file into a song framework output, the song framework output defining: (i) one or more framework elements; (ii) one or more performance elements, being bar-level representations of one track of the one or more track electronic music file comprising a structure incorporating at least one of the following: (A) metric information; (B) non-metric information being one or more compositional elements and one or more mechanical elements; and (C) expressive information being one or more mechanical performance elements; and (iii) a performance element collective, that functions to perform the further steps of: (A) maintaining a collection of performance elements within a song framework out put, such performance elements being non-matching to other performance elements in the collection; (B) identifying performance elements according to at least metric information and pitch sequence equivalence; and (C) grouping mechanical performance elements within a grouping structure consisting of performance elements that have common compositional performance elements; and (b) applying the plurality of song framework rules to each track of the one or more track electronic music file, thereby: (i) detecting the one or more performance elements of each track of the one or more track electronic music file; (ii) classifying each of the detected one or more performance elements as matching or non-matching, involving a comparison of the metric information, mechanical performance elements, and compositional performance elements of the performance elements to other performance elements stored in the performance element collective; and (iii) mapping each of the one or more performance elements to the corresponding framework elements.

1. A computer implemented method of converting one or more electronic music files into an electronic musical representation, the computer implemented method comprising the steps of: (a) providing a song framework including a plurality of song framework rules and associated processing steps for converting a one or more track electronic music file into a song framework output, the song framework output defining: (i) one or more framework elements; (ii) one or more performance elements, being bar-level representations of one track of the one or more track electronic music file comprising a structure incorporating at least one of the following: (A) metric information; (B) non-metric information being one or more compositional elements and one or more mechanical elements; and (C) expressive information being one or more mechanical performance elements; and (iii) a performance element collective, that functions to perform the further steps of: (A) maintaining a collection of performance elements within a song framework out put, such performance elements being non-matching to other performance elements in the collection; (B) identifying performance elements according to at least metric information and pitch sequence equivalence; and (C) grouping mechanical performance elements within a grouping structure consisting of performance elements that have common compositional performance elements; and (b) applying the plurality of song framework rules to each track of the one or more track electronic music file, thereby: (i) detecting the one or more performance elements of each track of the one or more track electronic music file; (ii) classifying each of the detected one or more performance elements as matching or non-matching, involving a comparison of the metric information, mechanical performance elements, and compositional performance elements of the performance elements to other performance elements stored in the performance element collective; and (iii) mapping each of the one or more performance elements to the corresponding framework elements. 5. The computer implemented method claimed in claim 1 , whereby the framework elements are derived from one or more environmental parameters defined by the one or more electronic music files, including one or more of: time signature; tempo; key; or song structure.

88. A system as defined in claim 87, wherein the means for determining a dictionary size selects a size from a set of predetermined dictionary fixed sizes.

88. A system as defined in claim 87, wherein the means for determining a dictionary size selects a size from a set of predetermined dictionary fixed sizes. 89. A system as defined in claim 88, wherein the set of predetermined fixed sizes comprises 512, 1K, 2K, 4K, and 8K dictionary entries.

1. A training program comprising a combination of games configured to systematically drive neurological changes to overcome social cognitive deficits, the training program comprising: one or more computerized social cue perception games, wherein one of the social cue perception games challenges the participant to observe gaze directions in facial images; one or more computerized emotion perception games; and one or more computerized theory of mind games; wherein each computerized game is configured to: present a plurality of target and/or distractor stimuli; prompt a game participant to respond to the target and/or distractor stimuli; receive the game participant's input through a game piece; provide an indication to the game participant of whether the game participant's input was accurate or apt; provide a signal indicative of the game participant's performance or game difficulty; and repeat the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range.

1. A training program comprising a combination of games configured to systematically drive neurological changes to overcome social cognitive deficits, the training program comprising: one or more computerized social cue perception games, wherein one of the social cue perception games challenges the participant to observe gaze directions in facial images; one or more computerized emotion perception games; and one or more computerized theory of mind games; wherein each computerized game is configured to: present a plurality of target and/or distractor stimuli; prompt a game participant to respond to the target and/or distractor stimuli; receive the game participant's input through a game piece; provide an indication to the game participant of whether the game participant's input was accurate or apt; provide a signal indicative of the game participant's performance or game difficulty; and repeat the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range. 6. The training program of claim 1 , wherein another one of the social cue perception games challenges the participant to memorize social details about sequentially presented faces.

16. A computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to perform a method comprising: generating, from an input lattice representing a first modality of an input, a first markup-language expression; generating, via a finite-state transducer, a concatenated mapping, wherein the finite state transducer: uses the input lattice and a first finite-state machine having associated markup-language semantics to relate the first markup-language expression to a second markup-language expression representing a second modality based on a level of coincidence between the first modality and the second modality, to yield a mapping; and concatenates input symbols of the mapping associated with the markup-language semantics, to yield the concatenated mapping; generating, using a second finite-state machine representing the concatenated mapping and the input, a third markup-language expression; and outputting the third markup-language expression.

16. A computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to perform a method comprising: generating, from an input lattice representing a first modality of an input, a first markup-language expression; generating, via a finite-state transducer, a concatenated mapping, wherein the finite state transducer: uses the input lattice and a first finite-state machine having associated markup-language semantics to relate the first markup-language expression to a second markup-language expression representing a second modality based on a level of coincidence between the first modality and the second modality, to yield a mapping; and concatenates input symbols of the mapping associated with the markup-language semantics, to yield the concatenated mapping; generating, using a second finite-state machine representing the concatenated mapping and the input, a third markup-language expression; and outputting the third markup-language expression. 21. The computer-readable storage medium of claim 16 , wherein using the first finite-state device and the second finite-state device to perform a function using the input lattice comprises using extensible-markup-language-based symbols in the finite state device having symbols based on markup-language semantics.

24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer.

24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer. 35. The method of claim 24 , wherein a single nonblocking control thread drives the decoding layer and the application layer according to message events in an event queue.

1. A method for using a computing device to control access to a resource, wherein the access includes one or more of perceiving, modifying, creating, adding to, or deleting the resource, comprising the steps of: (a) enabling a user desiring to provide access to the resource by a specific group of one or more persons who can interact with the computing device, to specify a shared knowledge question and to indicate one or more acceptable answers to the shared knowledge question, wherein the user creates the shared knowledge question so that only the specific group of one or more persons are likely to know an acceptable answer to the shared knowledge question; (b) enabling a person desiring to access the resource, the person being different than the user, to be presented with the shared knowledge question and to respond by entering a proposed answer to the shared knowledge question; (c) using the computing device to automatically employ an inexact matching procedure to determine if the proposed answer at least inexactly matches any of the one or more acceptable answers sufficiently to enable the person to access the resource; and (i) if so, enabling the person to access the resource; else, (ii) if not, denying the person access to the resource.

1. A method for using a computing device to control access to a resource, wherein the access includes one or more of perceiving, modifying, creating, adding to, or deleting the resource, comprising the steps of: (a) enabling a user desiring to provide access to the resource by a specific group of one or more persons who can interact with the computing device, to specify a shared knowledge question and to indicate one or more acceptable answers to the shared knowledge question, wherein the user creates the shared knowledge question so that only the specific group of one or more persons are likely to know an acceptable answer to the shared knowledge question; (b) enabling a person desiring to access the resource, the person being different than the user, to be presented with the shared knowledge question and to respond by entering a proposed answer to the shared knowledge question; (c) using the computing device to automatically employ an inexact matching procedure to determine if the proposed answer at least inexactly matches any of the one or more acceptable answers sufficiently to enable the person to access the resource; and (i) if so, enabling the person to access the resource; else, (ii) if not, denying the person access to the resource. 16. The method of claim 1 , wherein a site includes a plurality of resources for which the user has chosen a plurality of shared knowledge questions for use by the computing device in determining the persons who are granted access to the resources, further comprising the step of enabling the user to associate one or more of the shared knowledge questions respectively with one or more specific resources, but without indicating to a person the resource to which the person will be granted access if the proposed answer input to any of the shared knowledge questions is acceptable, thereby effectively hiding the resource to which the person will be granted access until the proposed answer input by the person is determined by the computing device to be correct.

10. A non-transitory computer readable storage medium having stored thereon instructions for causing one or more processors to reason data, the instructions including instructions that: cause the one or more processors to cause storage of data in a data store; cause the one or more processors to reason the data using a reasoner to determine a conclusion, the reasoner comprising at least one semantic reasoning module and at least one pattern-based reasoning module in series with the semantic reasoning module; cause the one or more processors to receive a selection of said one or more semantic reasoning module and of said one or more pattern-based reasoning module from a user, said selection from a plurality of potential semantic reasoning modules and potential pattern-based reasoning modules; and cause information related to the conclusion to be displayed.

10. A non-transitory computer readable storage medium having stored thereon instructions for causing one or more processors to reason data, the instructions including instructions that: cause the one or more processors to cause storage of data in a data store; cause the one or more processors to reason the data using a reasoner to determine a conclusion, the reasoner comprising at least one semantic reasoning module and at least one pattern-based reasoning module in series with the semantic reasoning module; cause the one or more processors to receive a selection of said one or more semantic reasoning module and of said one or more pattern-based reasoning module from a user, said selection from a plurality of potential semantic reasoning modules and potential pattern-based reasoning modules; and cause information related to the conclusion to be displayed. 13. The computer readable storage medium of claim 10 , wherein the instructions cause the one or more processors to use output of one of the one or more pattern-based reasoning modules for input to the one or more semantic reasoning modules.

1. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: An interface; A process manager system executable on at least one processor and operable to execute activities comprising: receiving user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; Providing at least one of an interactive workspace or a suggestion to a user, or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; Providing an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project, in display or output or both.

1. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: An interface; A process manager system executable on at least one processor and operable to execute activities comprising: receiving user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; Providing at least one of an interactive workspace or a suggestion to a user, or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; Providing an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project, in display or output or both. 24. The system of claim 1 further comprising that a specification or model or both, is comprised of more than one specification or model, or is comprised of related, linked, or associated specifications or models, or subsets of specification or models, or a combination thereof.

1. A method of compressing visual descriptors from at least one image by exploiting redundancy of natural image descriptors, comprising: extracting the visual descriptors from at least one image, said visual descriptors describing key points in images; creating model parameters of a generative probabilistic model from the extracted visual descriptors in a maximum likelihood sense; quantizing and encoding said model parameters; quantizing said extracted visual descriptors; and, applying a model-based arithmetic encoding to said quantized extracted visual descriptors using said encoded model parameters exploiting redundancy of the visual descriptors within the at least one image for compression of the visual descriptors.

1. A method of compressing visual descriptors from at least one image by exploiting redundancy of natural image descriptors, comprising: extracting the visual descriptors from at least one image, said visual descriptors describing key points in images; creating model parameters of a generative probabilistic model from the extracted visual descriptors in a maximum likelihood sense; quantizing and encoding said model parameters; quantizing said extracted visual descriptors; and, applying a model-based arithmetic encoding to said quantized extracted visual descriptors using said encoded model parameters exploiting redundancy of the visual descriptors within the at least one image for compression of the visual descriptors. 4. The method of claim 1 , said encoding of said quantized extracted visual descriptors comprising: associating each said visual descriptor with a corresponding Gaussian mixture model component for which the likelihood of said visual descriptor is maximum; rearranging said visual descriptors by order of Gaussian mixture model component indices so that the visual descriptors are non-decreasing; encoding Gaussian mixture model component indices using a predictive entropy coding scheme; and encoding each said visual descriptor using a multivariate Gaussian-based arithmetic coding.

6. A computer program product for creating a structured hardware description language design, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code configured to, remove, based on execution of an instruction by a processor, a part of a logic from a hardware description language design to create a modified hardware language design, the part of the logic comprising at least one time sensitive path in the hardware description language design; compare the modified hardware language design to a physical representation that is logically equivalent to the hardware description language design to create a delta list of differences; create a modified physical representation that includes a part of the physical representation that includes the logical equivalent of the part of the logic comprising the at least one time sensitive path, using the delta list of differences; create a structured hardware description language design of the part of the logic comprising the at least one time sensitive path using the modified physical representation, the structured hardware description language design comprising a physical implementation requirement of at least one component; and modify the structured hardware description language design, wherein the computer readable program code to modify comprises computer readable program code configured to update the structured hardware description language design to comply with requirements of a synthesis operation of a synthesis tool, and wherein the computer readable program code to modify comprises computer readable program code configured to preclude the synthesis tool from modifying the physical implementation requirement of the at least one component.

6. A computer program product for creating a structured hardware description language design, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code configured to, remove, based on execution of an instruction by a processor, a part of a logic from a hardware description language design to create a modified hardware language design, the part of the logic comprising at least one time sensitive path in the hardware description language design; compare the modified hardware language design to a physical representation that is logically equivalent to the hardware description language design to create a delta list of differences; create a modified physical representation that includes a part of the physical representation that includes the logical equivalent of the part of the logic comprising the at least one time sensitive path, using the delta list of differences; create a structured hardware description language design of the part of the logic comprising the at least one time sensitive path using the modified physical representation, the structured hardware description language design comprising a physical implementation requirement of at least one component; and modify the structured hardware description language design, wherein the computer readable program code to modify comprises computer readable program code configured to update the structured hardware description language design to comply with requirements of a synthesis operation of a synthesis tool, and wherein the computer readable program code to modify comprises computer readable program code configured to preclude the synthesis tool from modifying the physical implementation requirement of the at least one component. 9. The computer program product of claim 6 , wherein the physical implementation requirement comprises at least one of a placement of a component and a requirement of a wire coupling components together.

33. A computer system for collecting information from users and aggregating it into a useful format, comprising: a server computer; a client device coupled to the server by a communication network, the server computer and client device being operatively configured to: a. present a question to a subject user; b. electronically record the subject user's free text response to the question; c. calculate a list of one or more prior free text responses from other subject users which may be equivalent to response of the subject user; d. present the calculated list of potentially-equivalent free text responses from other subject users to the subject user; e. the subject user selecting if one or more prior responses on the list is equivalent to the subject user's response or if none on the list is equivalent; f. electronically record the subject user's selection of an equivalent response; g. calculate a selected list of responses to the question; h. re-present the question and the selected list of responses to the subject user; i. electronically record which response on the selected list the subject user selects as the best response to the question; such that responses from the subject user are collected and aggregated into the responses from other subject users in a manner resulting in information enhancing knowledge retention and learning.

33. A computer system for collecting information from users and aggregating it into a useful format, comprising: a server computer; a client device coupled to the server by a communication network, the server computer and client device being operatively configured to: a. present a question to a subject user; b. electronically record the subject user's free text response to the question; c. calculate a list of one or more prior free text responses from other subject users which may be equivalent to response of the subject user; d. present the calculated list of potentially-equivalent free text responses from other subject users to the subject user; e. the subject user selecting if one or more prior responses on the list is equivalent to the subject user's response or if none on the list is equivalent; f. electronically record the subject user's selection of an equivalent response; g. calculate a selected list of responses to the question; h. re-present the question and the selected list of responses to the subject user; i. electronically record which response on the selected list the subject user selects as the best response to the question; such that responses from the subject user are collected and aggregated into the responses from other subject users in a manner resulting in information enhancing knowledge retention and learning. 60. The system of claim 33 , further comprising the step of providing the subject user with the correct answer(s) to the question and/or educational material to foster learning about the topic covered by the question.

2. The computer-readable storage medium of claim 1 having computer-executable instructions to perform: receiving a first indication that is indicative of a selected salient keyphrase, the selected salient keyphrase being one of a plurality of salient keyphrases; and displaying related keyphrases in the thumbnail, the related keyphrases being associated with the selected salient keyphrase.

2. The computer-readable storage medium of claim 1 having computer-executable instructions to perform: receiving a first indication that is indicative of a selected salient keyphrase, the selected salient keyphrase being one of a plurality of salient keyphrases; and displaying related keyphrases in the thumbnail, the related keyphrases being associated with the selected salient keyphrase. 7. The computer-readable storage medium of claim 2 having computer-executable instructions to perform: in response to receiving a first indication that is indicative of a selected salient keyphrase, repositioning the first tag and the second tag within the thumbnail.

13. An apparatus comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions for: receiving a first document, a second document and a third document from at least one machine-readable media, the second document being associated with a specific subsection of the first document and is at least one of a replacement of a contiguous part of the first document or an addition to the first document at the specific subsection in the first document, the third document being associated with a specific subsection of the second document and is at least one of a replacement of a contiguous part of the second document or an addition to the second document the specific subsection in the second document; and simultaneously and distinctly displaying, on a display, the first document, the second document and the third document in a nested enhancement hierarchy by displaying the entirety of the second document in the first document at a location based on the specific subsection of the first document with which it is associated and an entirety of the third document is included in the second document at a location based on the specific subsection of the second document with which it is associated; and indicating at least one of the a location in the first document at which the second document is included, and the location in the second document at which the third document is included.

13. An apparatus comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions for: receiving a first document, a second document and a third document from at least one machine-readable media, the second document being associated with a specific subsection of the first document and is at least one of a replacement of a contiguous part of the first document or an addition to the first document at the specific subsection in the first document, the third document being associated with a specific subsection of the second document and is at least one of a replacement of a contiguous part of the second document or an addition to the second document the specific subsection in the second document; and simultaneously and distinctly displaying, on a display, the first document, the second document and the third document in a nested enhancement hierarchy by displaying the entirety of the second document in the first document at a location based on the specific subsection of the first document with which it is associated and an entirety of the third document is included in the second document at a location based on the specific subsection of the second document with which it is associated; and indicating at least one of the a location in the first document at which the second document is included, and the location in the second document at which the third document is included. 18. The apparatus of claim 13 , further comprising displaying the first document, the second document and the third document with numbered lines, wherein numbering of the first document, numbering of the second document and numbering of the third document are independent of each other.

1. A method comprising, by one or more computing systems: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes corresponding to a plurality of content objects associated with an online social network; receiving an input from a user, wherein the input comprises free-form text; determining, through application of natural-language processing of the free-form text, one or more objects associated with the input, each object corresponding to one of the plurality of nodes in the social graph, wherein each of the one or more objects comprises a noun detected in the free-form text; determining, through application of natural-language processing of the free-form text, one or more affinity declarations associated with the one or more objects; determining, from the one or more objects, a first concept and a second concept, the first concept corresponding to a first node in the social graph, the second concept corresponding to a second node in the social graph, wherein the first concept is a specific instance of the second concept; determining a first affinity coefficient between the user and the first concept based on the one or more affinity declarations; inferring a second affinity coefficient between the user and the second concept, wherein the inference is based on: the first affinity coefficient; and social networking information of the user; storing the first affinity coefficient in a data store in association with the user and the first concept; dynamically adjusting the inferred second affinity coefficient based on social-networking information of the user, wherein the social-networking information reinforces or reduces the inferred second affinity coefficient; and upon determining that the inferred second affinity coefficient for a threshold number of users exceeds a predetermined number, creating a hub page associated with the first concept for display on an online social network.

1. A method comprising, by one or more computing systems: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes corresponding to a plurality of content objects associated with an online social network; receiving an input from a user, wherein the input comprises free-form text; determining, through application of natural-language processing of the free-form text, one or more objects associated with the input, each object corresponding to one of the plurality of nodes in the social graph, wherein each of the one or more objects comprises a noun detected in the free-form text; determining, through application of natural-language processing of the free-form text, one or more affinity declarations associated with the one or more objects; determining, from the one or more objects, a first concept and a second concept, the first concept corresponding to a first node in the social graph, the second concept corresponding to a second node in the social graph, wherein the first concept is a specific instance of the second concept; determining a first affinity coefficient between the user and the first concept based on the one or more affinity declarations; inferring a second affinity coefficient between the user and the second concept, wherein the inference is based on: the first affinity coefficient; and social networking information of the user; storing the first affinity coefficient in a data store in association with the user and the first concept; dynamically adjusting the inferred second affinity coefficient based on social-networking information of the user, wherein the social-networking information reinforces or reduces the inferred second affinity coefficient; and upon determining that the inferred second affinity coefficient for a threshold number of users exceeds a predetermined number, creating a hub page associated with the first concept for display on an online social network. 7. The method of claim 1 , wherein the first affinity coefficient is a positive or negative numerical value.

10. The method of claim 9 , wherein: the item of content is identified based at least in part on the command and a predetermined rule set.

10. The method of claim 9 , wherein: the item of content is identified based at least in part on the command and a predetermined rule set. 11. The method of claim 10 , wherein the predetermined rule set pertains to the application.

14. One or more computer devices, comprising: one or more memory devices to store log data associated with a plurality of searches of repositories based on search queries provided by a plurality of users, the plurality of search repositories including respective different types of documents, the log data including: information regarding a user that provided a certain search query, information regarding the certain search query, and information regarding a repository from which search results were provided in response to the certain search query; a search engine system to: receive a search query from a user, calculate a score, for each of a plurality of repositories with respect to the search query from the user based on the log data, the score for each of the plurality of repositories reflecting a likelihood that each of the plurality of repositories includes information that satisfies the search query from the user, the search engine system, when calculating of the score, being further to: compare information regarding the search query and information, from the log data, regarding other search queries associated with the plurality of users; compare information regarding the user and the plurality of users; and information about respective selections, related to the other search queries, from each of the plurality of searches of repositories, rank the plurality of repositories based on the respective scores, compare the respective scores, for the ranked plurality of repositories, to a threshold value, perform a search on one or more of the plurality of repositories, based on the search query and based on the comparison, to identify, for each of the one or more of the plurality of repositories, a set of search results, and provide one or more of the sets of search results based on the scores.

14. One or more computer devices, comprising: one or more memory devices to store log data associated with a plurality of searches of repositories based on search queries provided by a plurality of users, the plurality of search repositories including respective different types of documents, the log data including: information regarding a user that provided a certain search query, information regarding the certain search query, and information regarding a repository from which search results were provided in response to the certain search query; a search engine system to: receive a search query from a user, calculate a score, for each of a plurality of repositories with respect to the search query from the user based on the log data, the score for each of the plurality of repositories reflecting a likelihood that each of the plurality of repositories includes information that satisfies the search query from the user, the search engine system, when calculating of the score, being further to: compare information regarding the search query and information, from the log data, regarding other search queries associated with the plurality of users; compare information regarding the user and the plurality of users; and information about respective selections, related to the other search queries, from each of the plurality of searches of repositories, rank the plurality of repositories based on the respective scores, compare the respective scores, for the ranked plurality of repositories, to a threshold value, perform a search on one or more of the plurality of repositories, based on the search query and based on the comparison, to identify, for each of the one or more of the plurality of repositories, a set of search results, and provide one or more of the sets of search results based on the scores. 19. The one or more computer devices of claim 14 , where, when providing the one or more of the sets of search results, the search engine system is to: select one of the plurality of repositories with a highest score among the scores associated with the plurality of repositories, and present only the set of search results associated with the selected one of the plurality of repositories.

20. An apparatus according to claim 1, the further improvement whereby said main dictionary means includes any one of the following dictionary sections: (i) a first dictionary section storing at least one addressable entry representative of a linguistic expression having a character length less than nine, (ii) a second dictionary section storing at least one addressable entry representative of a linguistic expression having a character length greater than or equal to nine and not more than sixteen, (iii) a third dictionary section storing at least one addressable entry representative of a linguistic expression having a character length greater than or equal to sixteen, (iv) a fourth dictionary section storing at least one addressable entry representative of a linguistic expression having a capitalized initial letter.

20. An apparatus according to claim 1, the further improvement whereby said main dictionary means includes any one of the following dictionary sections: (i) a first dictionary section storing at least one addressable entry representative of a linguistic expression having a character length less than nine, (ii) a second dictionary section storing at least one addressable entry representative of a linguistic expression having a character length greater than or equal to nine and not more than sixteen, (iii) a third dictionary section storing at least one addressable entry representative of a linguistic expression having a character length greater than or equal to sixteen, (iv) a fourth dictionary section storing at least one addressable entry representative of a linguistic expression having a capitalized initial letter. 21. An apparatus according to claim 20 in which said at least one stored entry of at least one of said dictionary section store is bit-wise compressed.

1. A method to update a database, the method comprising: identifying, by a processor, contents of the database, wherein the contents of the database are categorized into intelligence fields, wherein the intelligence fields relate to particular types of information among the contents of the database, and wherein the database is stored in a first data structure stored in a memory; receiving, by the processor, a selection of a particular intelligence field in the database; searching, by the processor, a first data file in the database for matching data among the particular types of information, wherein the particular types of information are categorized within the particular intelligence field; identifying, by the processor, a match between a first piece of data of the particular type of information and a second piece of data of the particular type of information, wherein the first piece of data is in the first data file and related to a first entity, the first piece of data includes a first link to a first source, the first source is stored in a second data structure different from the first data structure, and wherein the second piece of data is related to a second entity in a second data file, the second piece of data includes a second link to a second source different from the first source, and the second source is stored in a third data structure different from the first data structure and the second data structure; determining, by the processor, that the first entity and the second entity are related based on the match; updating the first data file, by the processor, to produce an updated first data file, wherein the updated first data file stored in the first structure indicates a relationship between the first entity and the second entity; displaying, by the processor, at least some of the contents of the updated first data file related to the first entity and the second entity on a display; and storing the updated first data file in the memory.

1. A method to update a database, the method comprising: identifying, by a processor, contents of the database, wherein the contents of the database are categorized into intelligence fields, wherein the intelligence fields relate to particular types of information among the contents of the database, and wherein the database is stored in a first data structure stored in a memory; receiving, by the processor, a selection of a particular intelligence field in the database; searching, by the processor, a first data file in the database for matching data among the particular types of information, wherein the particular types of information are categorized within the particular intelligence field; identifying, by the processor, a match between a first piece of data of the particular type of information and a second piece of data of the particular type of information, wherein the first piece of data is in the first data file and related to a first entity, the first piece of data includes a first link to a first source, the first source is stored in a second data structure different from the first data structure, and wherein the second piece of data is related to a second entity in a second data file, the second piece of data includes a second link to a second source different from the first source, and the second source is stored in a third data structure different from the first data structure and the second data structure; determining, by the processor, that the first entity and the second entity are related based on the match; updating the first data file, by the processor, to produce an updated first data file, wherein the updated first data file stored in the first structure indicates a relationship between the first entity and the second entity; displaying, by the processor, at least some of the contents of the updated first data file related to the first entity and the second entity on a display; and storing the updated first data file in the memory. 6. The method of claim 1 , further comprising: selecting an item of information from among the contents of the first data file; and linking the first data file to at least one third data file, when the third data file includes the selected item of information.

1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results.

1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results. 9. The apparatus of claim 1 , wherein the processor is configured to enable the user to modify the particular audit rule to generate a modified audit rule.

1. A method comprising, by a computing device: receiving, from a client system of a first user, a structured query comprising references to one or more selected objects accessible by the computing device; generating one or more search results corresponding to the structured query, wherein each search result corresponds to a particular object accessible by the computing device; determining one or more search intents based at least on whether one or more of the selected objects referenced in the structured query match objects corresponding to a search intent indexed in a pattern-detection model; and scoring the search results based on one or more of the search intents.

1. A method comprising, by a computing device: receiving, from a client system of a first user, a structured query comprising references to one or more selected objects accessible by the computing device; generating one or more search results corresponding to the structured query, wherein each search result corresponds to a particular object accessible by the computing device; determining one or more search intents based at least on whether one or more of the selected objects referenced in the structured query match objects corresponding to a search intent indexed in a pattern-detection model; and scoring the search results based on one or more of the search intents. 9. The method of claim 1 , further comprising generating a query command based on the structured query, the query command comprising one or more query constraints.

8. The system of claim 1 , wherein the search result providing unit is configured to provide the document associated with the at least one of the first personal network and the second personal network as a search result of the search term by arranging the document among documents associated with the search term, based on an order of net association comprising an association with respect to the search term and an association between the user providing the search term and the at least one of the first personal network and the second personal network.

8. The system of claim 1 , wherein the search result providing unit is configured to provide the document associated with the at least one of the first personal network and the second personal network as a search result of the search term by arranging the document among documents associated with the search term, based on an order of net association comprising an association with respect to the search term and an association between the user providing the search term and the at least one of the first personal network and the second personal network. 9. The system of claim 8 , wherein the search result providing unit is configured to place, in the search result of the search term, documents associated with communities joined by the user at a higher ranking than documents associated with communities joined by at least one neighbor of the user.

1. A computer-implemented method comprising: receiving, from a given user and by a microphone of a mobile device that includes (i) the microphone, (ii) an automated speech recognition system, and (iii) an end of utterance detector that is configured to identify an endpoint of an utterance spoken by a user in response to determining that a speaker has stopped speaking for a fixed duration, a first utterance; determining, by the end of utterance detector, that the given user has stopped speaking for the fixed duration after the first utterance; generating, by the automated speech recognition system, a first transcription of the first utterance; based on the first transcription of the first utterance, maintaining the microphone in an active state without endpointing the first utterance; after the given user has stopped speaking for at least the fixed duration after the first utterance, receiving, by the microphone and from the given user, a second utterance; generating, by the automated speech recognition system, a second transcription of the second utterance; based on both the first transcription and the second transcription, deactivating the microphone and endpointing the second utterance; in response to endpointing the second utterance, submitting, by the mobile device, a single search query that includes both the first transcription and the second transcription; receiving, by the mobile device, search results in response to the single search query that includes both the first transcription and the second transcription; and providing, for output by the mobile device, the search results.

1. A computer-implemented method comprising: receiving, from a given user and by a microphone of a mobile device that includes (i) the microphone, (ii) an automated speech recognition system, and (iii) an end of utterance detector that is configured to identify an endpoint of an utterance spoken by a user in response to determining that a speaker has stopped speaking for a fixed duration, a first utterance; determining, by the end of utterance detector, that the given user has stopped speaking for the fixed duration after the first utterance; generating, by the automated speech recognition system, a first transcription of the first utterance; based on the first transcription of the first utterance, maintaining the microphone in an active state without endpointing the first utterance; after the given user has stopped speaking for at least the fixed duration after the first utterance, receiving, by the microphone and from the given user, a second utterance; generating, by the automated speech recognition system, a second transcription of the second utterance; based on both the first transcription and the second transcription, deactivating the microphone and endpointing the second utterance; in response to endpointing the second utterance, submitting, by the mobile device, a single search query that includes both the first transcription and the second transcription; receiving, by the mobile device, search results in response to the single search query that includes both the first transcription and the second transcription; and providing, for output by the mobile device, the search results. 5. The method of claim 1 , comprising: after receiving the second utterance, updating a user interface to include the first transcription and the second transcription, without updating the user interface after the given user has stopped speaking for longer than the fixed duration after the end of the first utterance to include only the first transcription.

14. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query.

14. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query. 20. The system of claim 14 , wherein associating the user submitted search query with a respective search context includes associating one or more parameters of a user profile of the user with a respective search context of the plurality of search contexts.

7. A method for identifying a possible error made by a speech recognition system comprising: with an apparatus using at least one hardware-implemented processor, identifying when a hypothesis generated by the speech recognition system does not match an expected response word-for-word, but the hypothesis mostly matches the expected response word-for-word; with the apparatus using the at least one hardware-implemented processor, identifying when the speech recognition system generates a first hypothesis and a second hypothesis of two utterances received from a user and the speech recognition system accepts the second hypothesis, wherein the first hypothesis and the second hypothesis do not match word-for-word, but the first hypothesis and the second hypothesis mostly match word-for-word; with the apparatus using the at least one hardware-implemented processor, incrementing a count of an occurrence of a possible error made by the speech recognition system; and with the apparatus using the at least one hardware-implemented processor, adjusting an adaptation of a model used by the speech recognition system for a word associated with the possible error when the count exceeds an acceptance threshold.

7. A method for identifying a possible error made by a speech recognition system comprising: with an apparatus using at least one hardware-implemented processor, identifying when a hypothesis generated by the speech recognition system does not match an expected response word-for-word, but the hypothesis mostly matches the expected response word-for-word; with the apparatus using the at least one hardware-implemented processor, identifying when the speech recognition system generates a first hypothesis and a second hypothesis of two utterances received from a user and the speech recognition system accepts the second hypothesis, wherein the first hypothesis and the second hypothesis do not match word-for-word, but the first hypothesis and the second hypothesis mostly match word-for-word; with the apparatus using the at least one hardware-implemented processor, incrementing a count of an occurrence of a possible error made by the speech recognition system; and with the apparatus using the at least one hardware-implemented processor, adjusting an adaptation of a model used by the speech recognition system for a word associated with the possible error when the count exceeds an acceptance threshold. 11. The method of claim 7 , wherein the first hypothesis and the second hypothesis differ in that a word in the second hypothesis is substituted with a word in the first hypothesis.

9. A method of teaching the pronounciation and spelling and distinguishing between the written and spoken form of any language, the method comprising utilizing three sets of tiles, the first set denoting alphabet letters, the second set denoting phonetic vowels, the third set denoting phonetic consonants, the first set comprising all geometrically uniform tiles, each tile having an alphabet letter on one surface thereof, in black or white, and a background of opposite white or black colour to the letter colours, there being separate tiles for each upper case alphabet letter and separate tiles for each lower case alphabet letter, the second set of tiles comprising geometrically uniform tiles wherein one surface of each tile is blank and individually and distinctively coloured to represent a phonetic vowel sound and vowel spelling where there are differences in spelling the same vowel sound, while the other surface of each tile contains an individual International Phonetic Alphabet Symbol to represent the vowel sound on said one surface, the second set of tiles also including tiles individually distinctively coloured to represent single letter vowel sounds and tiles individually distinctively coloured to represent double letter vowel sounds, the third set of tiles comprising single letter consonants and two letter digraphs of two-letter combinations of consonants having a single phonetic sound, selecting the first, second and third sets to be distinct, and teaching how to distinguish between pronounciation and spelling of words of the language by interposing the alphabet tiles and the phonetic tiles.

9. A method of teaching the pronounciation and spelling and distinguishing between the written and spoken form of any language, the method comprising utilizing three sets of tiles, the first set denoting alphabet letters, the second set denoting phonetic vowels, the third set denoting phonetic consonants, the first set comprising all geometrically uniform tiles, each tile having an alphabet letter on one surface thereof, in black or white, and a background of opposite white or black colour to the letter colours, there being separate tiles for each upper case alphabet letter and separate tiles for each lower case alphabet letter, the second set of tiles comprising geometrically uniform tiles wherein one surface of each tile is blank and individually and distinctively coloured to represent a phonetic vowel sound and vowel spelling where there are differences in spelling the same vowel sound, while the other surface of each tile contains an individual International Phonetic Alphabet Symbol to represent the vowel sound on said one surface, the second set of tiles also including tiles individually distinctively coloured to represent single letter vowel sounds and tiles individually distinctively coloured to represent double letter vowel sounds, the third set of tiles comprising single letter consonants and two letter digraphs of two-letter combinations of consonants having a single phonetic sound, selecting the first, second and third sets to be distinct, and teaching how to distinguish between pronounciation and spelling of words of the language by interposing the alphabet tiles and the phonetic tiles. 11. The method of claim 9, comprising teaching both the pronounciation and spelling of said any language by interposing tiles of said second set between tiles of said first set to represent both the alphabetical spelling of a word and any combination of the alphabet letters and the vowels of said word.

13. A non-transitory computer recordable medium comprising computer program instructions which, when executed, cause performance of a method comprising: selecting, using a processor, a demeanor for presentation of content of a content provider via the multimodal application, wherein selecting the demeanor comprises considering, by the processor, at least one characteristic of a user of the multimodal application to whom the content is to be provided, the user differing from the content provide, wherein the at least one characteristic of the user comprises whether the user is a repeat user of the multimodal application; and presenting the content to the user using the demeanor; wherein selecting the demeanor comprises selecting a visual demeanor and/or selecting a vocal demeanor; wherein selecting the visual demeanor comprises selecting from the group consisting of background colors, text colors, text fonts, and selection and placement of graphic elements; and wherein selecting the vocal demeanor comprises selecting from the group consisting of speech rate, voice family, pitch, pith range, stress and richness.

13. A non-transitory computer recordable medium comprising computer program instructions which, when executed, cause performance of a method comprising: selecting, using a processor, a demeanor for presentation of content of a content provider via the multimodal application, wherein selecting the demeanor comprises considering, by the processor, at least one characteristic of a user of the multimodal application to whom the content is to be provided, the user differing from the content provide, wherein the at least one characteristic of the user comprises whether the user is a repeat user of the multimodal application; and presenting the content to the user using the demeanor; wherein selecting the demeanor comprises selecting a visual demeanor and/or selecting a vocal demeanor; wherein selecting the visual demeanor comprises selecting from the group consisting of background colors, text colors, text fonts, and selection and placement of graphic elements; and wherein selecting the vocal demeanor comprises selecting from the group consisting of speech rate, voice family, pitch, pith range, stress and richness. 16. The non-transitory computer recordable medium of claim 13 , wherein selecting the demeanor comprises selecting the vocal demeanor.

21. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: determining that a plurality of addresses cannot be geocoded by a geocoding system, wherein each address includes a plurality of terms; generating a plurality of variants of the addresses that can be geocoded by the geocoding system, wherein each variant of a respective address lacks a removed term included in the respective address; receiving a plurality of name terms for each variant provided by the geocoding system; associating each removed term with name terms received for all variants that lack the removed term, including determining, for each associated name term of each removed term, a count of the number of variants for which the geocoding system provided the name term; determining, for each associated name term of each removed term, whether the name term is an address term synonym for the removed term based at least in part on the count of the number of variants.

21. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: determining that a plurality of addresses cannot be geocoded by a geocoding system, wherein each address includes a plurality of terms; generating a plurality of variants of the addresses that can be geocoded by the geocoding system, wherein each variant of a respective address lacks a removed term included in the respective address; receiving a plurality of name terms for each variant provided by the geocoding system; associating each removed term with name terms received for all variants that lack the removed term, including determining, for each associated name term of each removed term, a count of the number of variants for which the geocoding system provided the name term; determining, for each associated name term of each removed term, whether the name term is an address term synonym for the removed term based at least in part on the count of the number of variants. 27. The computer storage medium of claim 21 , wherein determining that a plurality of addresses cannot be geocoded by a geocoding system includes attempting to geocode each potential address in a corpus of potential addresses by sending each potential address to the geocoding system.

14. A non-transitory recording medium storing a machine translation program to be executed by a computer, the program comprising a set of code for causing the computer to: translating the first language sentence of a first language into an intermediate second language sentence of a second language; acquiring a size of a corpus of a third language; determining whether or not the size of the corpus of the third language is larger than a threshold value; translating the intermediate second language sentence into a third language sentence of the third language when the size of the corpus of the third language is larger than the threshold value; outputting the intermediate second language sentence when the size of the corpus of the third language is less than or equal to the threshold value; searching a database storing the corpus of the third language including more example sentences of the third language than example sentences of the first language and the second language using the third language sentence as a search key to acquire one or more other third language sentences; determining, based on the one or more other third language sentences, a final second language sentence of the second language corresponding to the first language sentence as the second language sentence; calculating a degree of coincidence between the search key and each example sentence of the third language in the search result; calculating an average value of the degrees of coincidence; and setting the average value as the degree of coincidence corresponding to the search key.

14. A non-transitory recording medium storing a machine translation program to be executed by a computer, the program comprising a set of code for causing the computer to: translating the first language sentence of a first language into an intermediate second language sentence of a second language; acquiring a size of a corpus of a third language; determining whether or not the size of the corpus of the third language is larger than a threshold value; translating the intermediate second language sentence into a third language sentence of the third language when the size of the corpus of the third language is larger than the threshold value; outputting the intermediate second language sentence when the size of the corpus of the third language is less than or equal to the threshold value; searching a database storing the corpus of the third language including more example sentences of the third language than example sentences of the first language and the second language using the third language sentence as a search key to acquire one or more other third language sentences; determining, based on the one or more other third language sentences, a final second language sentence of the second language corresponding to the first language sentence as the second language sentence; calculating a degree of coincidence between the search key and each example sentence of the third language in the search result; calculating an average value of the degrees of coincidence; and setting the average value as the degree of coincidence corresponding to the search key. 15. The machine translation method according to claim 14 , further comprising: outputting, as the second language sentence, a second language sentence corresponding to the third language sentence serving as the search key where the average value of the degrees of coincidence is the highest.

1. A messaging system for use in a network, the messaging system comprising: a plurality of network entities which include both publishing entities and subscribing entities, the publishing entities publishing content of which the subscribing entities have need, wherein information embedded within the published content defines a data hierarchy for the published content exchanged between the publishing entities and subscribing entities; wherein the data hierarchy defines at least a child tier and a parent tier, where the child tier contains a plurality of published content contributed by a plurality of said publishing entities; and wherein the data hierarchy determines virtual connections formed between the plurality of network entities in response to publication and subscription requests exchanged between the entities, such that the virtual connections established between network entities form a hierarchy corresponding to the data hierarchy, whereby subscription by one of said subscribing entities to the parent tier of the data hierarchy results in the subscribing entity receiving all of said plurality of published content in the child tier; wherein the data hierarchy comprises a plurality of child-tiered data elements that each correspond to a portion of data that forms a parent-tiered data element; wherein different entities publish different ones of the child-tiered data elements; wherein responsive to a subscribing entity's subscription to the parent-tiered data element, the subscribing entity receives the plurality of child-tiered data elements via the virtual connections.

1. A messaging system for use in a network, the messaging system comprising: a plurality of network entities which include both publishing entities and subscribing entities, the publishing entities publishing content of which the subscribing entities have need, wherein information embedded within the published content defines a data hierarchy for the published content exchanged between the publishing entities and subscribing entities; wherein the data hierarchy defines at least a child tier and a parent tier, where the child tier contains a plurality of published content contributed by a plurality of said publishing entities; and wherein the data hierarchy determines virtual connections formed between the plurality of network entities in response to publication and subscription requests exchanged between the entities, such that the virtual connections established between network entities form a hierarchy corresponding to the data hierarchy, whereby subscription by one of said subscribing entities to the parent tier of the data hierarchy results in the subscribing entity receiving all of said plurality of published content in the child tier; wherein the data hierarchy comprises a plurality of child-tiered data elements that each correspond to a portion of data that forms a parent-tiered data element; wherein different entities publish different ones of the child-tiered data elements; wherein responsive to a subscribing entity's subscription to the parent-tiered data element, the subscribing entity receives the plurality of child-tiered data elements via the virtual connections. 4. The messaging system of claim 1 wherein the virtual connections formed between entities can be top-level connections, parent tier connections, or closest tier connections.

1. A voice recognition system for recognizing input voice information pronounced by a user and comprising: a recognition dictionary for storing voice information; a primary voice recognition unit which performs primary voice recognition of the input voice information by the use of said recognition dictionary to produce a primary voice recognition result which is specified by a voice feature of the input voice information; a recognition result judgment unit which judges whether the primary voice recognition result is to be accepted or rejected; a transceiver unit which sends the voice feature to additional voice recognition means for performing secondary voice recognition, when the primary voice recognition result specified by the voice feature is rejected by said recognition result judgment unit and for receiving a secondary voice recognition result produced by the additional voice recognition means; a recognition result output unit which outputs the primary voice recognition result specified by the voice feature and outputted from said recognition result judgment unit or the secondary voice recognition result received by said transceiver unit to an exterior of said voice recognition system; a settled result input unit which receives settlement information on the primary voice recognition result or the secondary voice recognition result outputted to the exterior of said voice recognition system; and a dictionary content control unit which updates said recognition dictionary based on the settlement information inputted by said settled result input unit; wherein: said dictionary content control unit has a word history list which includes an order of use of each word and a frequency of use of each word and deletes, from the recognition dictionary, a word based on at least one of the oldest word and the smallest word of the frequency included in the word history list when an amount of the words in said recognition dictionary exceeds a processing capability of said voice recognition system.

1. A voice recognition system for recognizing input voice information pronounced by a user and comprising: a recognition dictionary for storing voice information; a primary voice recognition unit which performs primary voice recognition of the input voice information by the use of said recognition dictionary to produce a primary voice recognition result which is specified by a voice feature of the input voice information; a recognition result judgment unit which judges whether the primary voice recognition result is to be accepted or rejected; a transceiver unit which sends the voice feature to additional voice recognition means for performing secondary voice recognition, when the primary voice recognition result specified by the voice feature is rejected by said recognition result judgment unit and for receiving a secondary voice recognition result produced by the additional voice recognition means; a recognition result output unit which outputs the primary voice recognition result specified by the voice feature and outputted from said recognition result judgment unit or the secondary voice recognition result received by said transceiver unit to an exterior of said voice recognition system; a settled result input unit which receives settlement information on the primary voice recognition result or the secondary voice recognition result outputted to the exterior of said voice recognition system; and a dictionary content control unit which updates said recognition dictionary based on the settlement information inputted by said settled result input unit; wherein: said dictionary content control unit has a word history list which includes an order of use of each word and a frequency of use of each word and deletes, from the recognition dictionary, a word based on at least one of the oldest word and the smallest word of the frequency included in the word history list when an amount of the words in said recognition dictionary exceeds a processing capability of said voice recognition system. 3. The voice recognition system recited in claim 1 , wherein said primary voice recognition unit includes (i) a voice pre-processing unit operable to analyze the input voice information so as to extract the voice feature thereof, and (ii) a primary voice recognition unit operable to output the primary voice recognition result specified by the voice feature extracted by said voice preprocessing unit.

2. The method of claim 1 , further comprising: the computer maintaining an observed occurrence count of each determined pattern in the corpus of sample documents.

2. The method of claim 1 , further comprising: the computer maintaining an observed occurrence count of each determined pattern in the corpus of sample documents. 7. The method of claim 2 , wherein the computer populating a template using the at least one of the plurality of patterns comprises: the computer selecting the at least one of the plurality of patterns based on proportions of an observed occurrence count of the at least one of the plurality of patterns in relation to a total number of patterns; and the computer populating the template using the at least one of the plurality of patterns.

13. A method for automatic speech recognition comprising: identifying at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the identifying further comprising generating a phone decoder for building an acoustic input training data set; analyzing the acoustic input data set to compute probabilities that portions of the input data set conform to a standard form language and probabilities that the portions of the input data set conform to at least one dialect of the standard form language; performing automatic speech recognition by applying, with at least one hardware processor, a standard form language model and at least one dialect language model to the input data set, the performing including weighting the models in accordance with each of the computed probabilities; and outputting speech recognition results obtained in accordance with said applying.

13. A method for automatic speech recognition comprising: identifying at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the identifying further comprising generating a phone decoder for building an acoustic input training data set; analyzing the acoustic input data set to compute probabilities that portions of the input data set conform to a standard form language and probabilities that the portions of the input data set conform to at least one dialect of the standard form language; performing automatic speech recognition by applying, with at least one hardware processor, a standard form language model and at least one dialect language model to the input data set, the performing including weighting the models in accordance with each of the computed probabilities; and outputting speech recognition results obtained in accordance with said applying. 14. The method of claim 13 , wherein the applying comprises applying a single decoding graph including different decision trees corresponding to the standard form language model and the at least one dialect language model.

13. The graphical user interface of claim 12 , wherein sequentially scrolling through the set is in accordance with one or more navigation commands received from a click wheel.

13. The graphical user interface of claim 12 , wherein sequentially scrolling through the set is in accordance with one or more navigation commands received from a click wheel. 14. The graphical user interface of claim 13 , wherein the one or more navigation commands received from the click wheel are repetitions of a single navigation command.

23. A computer program product, tangibly stored on a computer-readable memory device, the product comprising instructions operable to cause a processor to: examine records in a local search database, each record of the examined records including a web site address and contact information, the contact information corresponding to at least one of a street address or a telephone number, each record of the examined records including a business or organization identifier; map, based on examining the records in the local search database, one of the business or organization identifiers to a plurality of web site addresses; select one web site address of the plurality of web site addresses for the one of the business or organization identifiers; associate, in a search index, the one web site address with the contact information from one of the records in the local search database, the one of the records including the one web site address; receive search results that are responsive to a search query that is associated with a user, one of the search results being associated with a plurality of geographic locations in the search index; automatically ascertain a geographic location of the user based on an Internet protocol address associated with the user; identify, by performing a local search using the ascertained geographic location of the user, geographic location information associated with one of the plurality of geographic locations, the geographic location information including at least a street address; and output the search results, the geographic location information and a link to a map that shows a geographic location specified by the street address, the outputting being performed in response to the search query and not in response to selection of a link by the user.

23. A computer program product, tangibly stored on a computer-readable memory device, the product comprising instructions operable to cause a processor to: examine records in a local search database, each record of the examined records including a web site address and contact information, the contact information corresponding to at least one of a street address or a telephone number, each record of the examined records including a business or organization identifier; map, based on examining the records in the local search database, one of the business or organization identifiers to a plurality of web site addresses; select one web site address of the plurality of web site addresses for the one of the business or organization identifiers; associate, in a search index, the one web site address with the contact information from one of the records in the local search database, the one of the records including the one web site address; receive search results that are responsive to a search query that is associated with a user, one of the search results being associated with a plurality of geographic locations in the search index; automatically ascertain a geographic location of the user based on an Internet protocol address associated with the user; identify, by performing a local search using the ascertained geographic location of the user, geographic location information associated with one of the plurality of geographic locations, the geographic location information including at least a street address; and output the search results, the geographic location information and a link to a map that shows a geographic location specified by the street address, the outputting being performed in response to the search query and not in response to selection of a link by the user. 26. The computer program product of claim 23 , where the one web site address is selected based on a source that provides the one web site address.

18. The method of claim 17 , further comprising determining semantic positions in the semantic space of the portions of the text item based on the semantic positions of the senses, wherein identifying the one or more topics is based on the determined semantic positions of the portions.

18. The method of claim 17 , further comprising determining semantic positions in the semantic space of the portions of the text item based on the semantic positions of the senses, wherein identifying the one or more topics is based on the determined semantic positions of the portions. 19. The method of claim 18 , wherein identifying the senses of words appearing in the corresponding portions of the text item comprises identifying sets of senses of the words appearing in the corresponding portions, wherein each of the sets of senses is a most compatible set of senses from among plural candidate sets of senses for the corresponding portion of the text item, wherein determining the semantic positions in the semantic space of the portions of the text item is based on the corresponding sets of senses.

1. A method for facilitating use of mobile devices to respond to questions submitted to a question and answer customer support system, to improve a rate of response to the questions by customer support personnel, the method comprising: training, using a computing system, predictive models using historical question and answer data, the training resulting in at least one predictive model configured to estimate, based on a received question, an expected answer length, determine whether an answer to the question is likely to include a web link, and determine whether a question answerer is more likely than not to have to perform research in order to answer the question; receiving, with a computing system having a processor and a memory, a first question from a user having a first type; determining that the received question is a first type of question and forming and sending a response to the user with recommendations for the user to reform the question into a different type; receiving a reformed first question from the user, the reformed question being the first question transformed into a second type of question; analyzing, using the one or more predictive models, the reformed first question with a question and answer customer support system of the computing system by determining one or more attributes of the reformed first question and determining that the reformed first question is a mobile device answerable question, because one or more of the determined one or more attributes of the reformed first question satisfy one or more mobile device question criteria; prioritizing, using the computing system, the answering of the reformed first question over the answering of questions that are not mobile device answerable questions; configuring multiple user interface elements, at least partially based on the one or more attributes of the reformed first question by at least prepopulating the user interface elements to include at least one proposed answer to the reformed first question; and providing the user interface elements with the question and answer customer support system for display in a user interface on the mobile device of a first question answerer.

1. A method for facilitating use of mobile devices to respond to questions submitted to a question and answer customer support system, to improve a rate of response to the questions by customer support personnel, the method comprising: training, using a computing system, predictive models using historical question and answer data, the training resulting in at least one predictive model configured to estimate, based on a received question, an expected answer length, determine whether an answer to the question is likely to include a web link, and determine whether a question answerer is more likely than not to have to perform research in order to answer the question; receiving, with a computing system having a processor and a memory, a first question from a user having a first type; determining that the received question is a first type of question and forming and sending a response to the user with recommendations for the user to reform the question into a different type; receiving a reformed first question from the user, the reformed question being the first question transformed into a second type of question; analyzing, using the one or more predictive models, the reformed first question with a question and answer customer support system of the computing system by determining one or more attributes of the reformed first question and determining that the reformed first question is a mobile device answerable question, because one or more of the determined one or more attributes of the reformed first question satisfy one or more mobile device question criteria; prioritizing, using the computing system, the answering of the reformed first question over the answering of questions that are not mobile device answerable questions; configuring multiple user interface elements, at least partially based on the one or more attributes of the reformed first question by at least prepopulating the user interface elements to include at least one proposed answer to the reformed first question; and providing the user interface elements with the question and answer customer support system for display in a user interface on the mobile device of a first question answerer. 13. The method of claim 1 wherein determining that the reformed first question is a mobile device answerable question includes searching the question for “Who” question formats, “What” question formats, “When” question formats, “Where” question formats, and “How” question formats to predict a length of the response to the question.

1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a) providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b) receiving incremental input entered by the user for incrementally identifying desired content items; c) in response to the incremental input entered by the user, presenting a subset of content items; d) receiving selection actions of content items of the subset from the user; e) analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f) expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment and at least one coarse grain segment, wherein the fine grain segment has fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and wherein the coarse grain segment has relatively coarse grain differentiation of measurements associated with preferred descriptive terms within the segment; and g) in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h) wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device.

1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a) providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b) receiving incremental input entered by the user for incrementally identifying desired content items; c) in response to the incremental input entered by the user, presenting a subset of content items; d) receiving selection actions of content items of the subset from the user; e) analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f) expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment and at least one coarse grain segment, wherein the fine grain segment has fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and wherein the coarse grain segment has relatively coarse grain differentiation of measurements associated with preferred descriptive terms within the segment; and g) in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h) wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 20. The method of claim 1 , wherein the display constrained device is at least one of a telephone, a PDA, and a remote control.

1. A method for reducing a size of a Business Process Execution Language (BPEL) data blob for storage, the method comprising: identifying, by a computer system, one or more dehydration points within BPEL code; performing, by the computer system, a liveness analysis for the one or more dehydration points; identifying, by the computer system, at each of the one or more dehydration points, one or more live variables from a set of variables; creating, by the computer system, an optimization data structure that for each dehydration point identifies the one or more live variables; compiling the BPEL code using a BPEL compiler configured to perform the liveness analysis, thereby creating compiled BPEL code; executing a BPEL process using the compiled BPEL code; dehydrating the BPEL process at a dehydration point during execution of the BPEL process using the compiled BPEL code; and identifying, using the optimization data structure, the one or more live variables for the dehydration point.

1. A method for reducing a size of a Business Process Execution Language (BPEL) data blob for storage, the method comprising: identifying, by a computer system, one or more dehydration points within BPEL code; performing, by the computer system, a liveness analysis for the one or more dehydration points; identifying, by the computer system, at each of the one or more dehydration points, one or more live variables from a set of variables; creating, by the computer system, an optimization data structure that for each dehydration point identifies the one or more live variables; compiling the BPEL code using a BPEL compiler configured to perform the liveness analysis, thereby creating compiled BPEL code; executing a BPEL process using the compiled BPEL code; dehydrating the BPEL process at a dehydration point during execution of the BPEL process using the compiled BPEL code; and identifying, using the optimization data structure, the one or more live variables for the dehydration point. 2. The method for reducing the size of the BPEL data blob for storage of claim 1 , wherein at runtime, the optimization data structure is checked when the one or more dehydration points are reached such that the one or more live variables of the set of variables are stored within the BPEL data blob and one or more not-live variables of the set of variables are not stored within the BPEL data blob.

17. The system of claim 14 , wherein an order for automatically selecting for playback the subset of the plurality of stored media assets that has the common attribute is determined based on an asset criteria.

17. The system of claim 14 , wherein an order for automatically selecting for playback the subset of the plurality of stored media assets that has the common attribute is determined based on an asset criteria. 20. The system of claim 17 , wherein the asset criteria is automatically determined by the interactive media guidance application.

21. The apparatus of claim 20, wherein the link management module further comprises a traverse module for traversing the directory services database.

21. The apparatus of claim 20, wherein the link management module further comprises a traverse module for traversing the directory services database. 22. The apparatus of claim 21, wherein the traverse module is programmed to traverse through a plurality of objects in an order beginning at an object having a comparatively close relationship to the link and progressing to objects having a comparatively distant relationship to the link.

6. A computer-implemented method for generating a first recognizability score, the method comprising: receiving a first image; computing, with one or more processors, a plurality of quality feature vectors to measure distortion of the first image including blurriness and coding artifacts and to determine whether the input image is stable to the distortion by applying different levels of the distortion to the input image, measuring distances between the input image and the distorted images and determining whether a combination of the distances is small; generating, with the one or more processors, a recognition score for each of the quality feature vectors; determining recognition results; generating the first recognizability score from the recognition scores; generating a confidence score for each recognition result that reflects a confidence in the recognition result based on the first recognizability score; and merging and sorting the recognition results to produce one or more top results using the confidence scores.

6. A computer-implemented method for generating a first recognizability score, the method comprising: receiving a first image; computing, with one or more processors, a plurality of quality feature vectors to measure distortion of the first image including blurriness and coding artifacts and to determine whether the input image is stable to the distortion by applying different levels of the distortion to the input image, measuring distances between the input image and the distorted images and determining whether a combination of the distances is small; generating, with the one or more processors, a recognition score for each of the quality feature vectors; determining recognition results; generating the first recognizability score from the recognition scores; generating a confidence score for each recognition result that reflects a confidence in the recognition result based on the first recognizability score; and merging and sorting the recognition results to produce one or more top results using the confidence scores. 8. The method of claim 6 , wherein generating the first recognizability score uses one from the group of neural networks, naive based classifiers, Bayesian based classifiers and support vector machine (SVM) based classifiers.

1. In a digital medium classification environment, a method implemented by at least one computing device, the method comprising: aggregating, by the at least one computing device, patterns of neurons in a neural network by progressing through a sequence of layers of the neural network to classify an image as relating to a semantic class; communicating, by the at least one computing device, positive relevancy of the patterns formed by the neurons to the semantic class by progressing backwards through the sequence of layers of the neural network, wherein the communicating of the positive relevancy of the pattern between a plurality of layers from the sequence of layers is based on a probabilistic Winner-Take-All (WTA) approach; localizing, by the at least one computing device, the semantic class within the image based on the communicated positive relevancy of the aggregated patterns to the semantic class; and generating, by the at least one computing device, digital content based on localization of the semantic class within the image.

1. In a digital medium classification environment, a method implemented by at least one computing device, the method comprising: aggregating, by the at least one computing device, patterns of neurons in a neural network by progressing through a sequence of layers of the neural network to classify an image as relating to a semantic class; communicating, by the at least one computing device, positive relevancy of the patterns formed by the neurons to the semantic class by progressing backwards through the sequence of layers of the neural network, wherein the communicating of the positive relevancy of the pattern between a plurality of layers from the sequence of layers is based on a probabilistic Winner-Take-All (WTA) approach; localizing, by the at least one computing device, the semantic class within the image based on the communicated positive relevancy of the aggregated patterns to the semantic class; and generating, by the at least one computing device, digital content based on localization of the semantic class within the image. 4. The method as described in claim 1 , wherein the positive relevancy of the patterns to the semantic class is defined using an activation relevancy map of the image.

1. A computer-implemented method comprising: automatically generating, at a local rule engine, a rule engine vocabulary comprising a context description and a result description that respectively define an input to and an output of an external rule engine, the rule engine vocabulary defining a data type of a result; serializing the rule engine vocabulary in a schema document that, when received at the external rule engine, allows a rule to be defined by the external rule engine based on the context description and the result description; transmitting the schema document to the external rule engine; transmitting a context specified according to the context description as the input to the external rule engine, for evaluation by the rule to provide the result corresponding to the data type; receiving, at the local rule engine, the result specified according to the result description as the output of the external rule engine; and outputting the result.

1. A computer-implemented method comprising: automatically generating, at a local rule engine, a rule engine vocabulary comprising a context description and a result description that respectively define an input to and an output of an external rule engine, the rule engine vocabulary defining a data type of a result; serializing the rule engine vocabulary in a schema document that, when received at the external rule engine, allows a rule to be defined by the external rule engine based on the context description and the result description; transmitting the schema document to the external rule engine; transmitting a context specified according to the context description as the input to the external rule engine, for evaluation by the rule to provide the result corresponding to the data type; receiving, at the local rule engine, the result specified according to the result description as the output of the external rule engine; and outputting the result. 14. The method of claim 1 , wherein the schema document is an eXtensible Markup Language (XML) Schema Document (XSD).

1. Server apparatus, comprising: a processor; a communications interface in data communication with the processor; and a storage device in data communication with the processor, the storage device comprising a storage medium, the storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to: receive a first remotely generated input via said communications interface, said first input relating to a first location; receive a second remotely generated input via said communications interface, said second input relating to a second location, the first and second locations being part of a common journey; identify a first entity associated with the first location; identify a second entity associated with the second location; cause first advertising content related to the first entity to be forwarded via said communication interface to a remotely disposed computerized device which generated said first and second remotely generated inputs; and cause second advertising content related to the second entity to be forwarded via said communication interface to said remotely disposed computerized device.

1. Server apparatus, comprising: a processor; a communications interface in data communication with the processor; and a storage device in data communication with the processor, the storage device comprising a storage medium, the storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to: receive a first remotely generated input via said communications interface, said first input relating to a first location; receive a second remotely generated input via said communications interface, said second input relating to a second location, the first and second locations being part of a common journey; identify a first entity associated with the first location; identify a second entity associated with the second location; cause first advertising content related to the first entity to be forwarded via said communication interface to a remotely disposed computerized device which generated said first and second remotely generated inputs; and cause second advertising content related to the second entity to be forwarded via said communication interface to said remotely disposed computerized device. 9. The server apparatus of claim 1 , wherein the at least one computer program is further configured to receive and utilize digital representations of speech, the digital representations received via said communications interface, in an iterative or hierarchical fashion to progress through a menu structure comprising multiple possible matching entities.

1. A prefiltering method for use in a speech recognition system, said method comprising: receiving an acoustic description of an utterance to be recognized; storing a vocabulary of words; storing a plurality of probabilistic acoustic cluster models and using individual ones of said acoustic cluster models to represent at least a part of more than one vocabulary word; comparing at least a portion of said acoustic description from said utterance against each of said cluster models, and producing a cluster likelihood score for each cluster model against which such a comparison is made; using the cluster likelihood score produced for each cluster model to calculate a prefilter score for words represented by that cluster model; and selecting a subset of said vocabulary words to undergo a more lengthy comparison against said utterance to be recognized based on the prefilter scores associated with said vocabulary words; wherein: said acoustic description of said utterance to be recognized includes a succession of acoustic descriptions representing a sequence of sounds associated with said utterance; said cluster models each comprises a succession of probabilistic acoustic models, for modeling a sequence of sounds associated with each word represented by said cluster model; said comparing includes comparing a succession of said acoustic descriptions from the utterance to be recognized against the succession of acoustic models from each of a plurality of cluster models and producing a cluster likelihood score for each such cluster model as a result of that comparison; and said cluster models are wordstart cluster models, that is, models which only represent the initial portion of many words in said vocabulary.

1. A prefiltering method for use in a speech recognition system, said method comprising: receiving an acoustic description of an utterance to be recognized; storing a vocabulary of words; storing a plurality of probabilistic acoustic cluster models and using individual ones of said acoustic cluster models to represent at least a part of more than one vocabulary word; comparing at least a portion of said acoustic description from said utterance against each of said cluster models, and producing a cluster likelihood score for each cluster model against which such a comparison is made; using the cluster likelihood score produced for each cluster model to calculate a prefilter score for words represented by that cluster model; and selecting a subset of said vocabulary words to undergo a more lengthy comparison against said utterance to be recognized based on the prefilter scores associated with said vocabulary words; wherein: said acoustic description of said utterance to be recognized includes a succession of acoustic descriptions representing a sequence of sounds associated with said utterance; said cluster models each comprises a succession of probabilistic acoustic models, for modeling a sequence of sounds associated with each word represented by said cluster model; said comparing includes comparing a succession of said acoustic descriptions from the utterance to be recognized against the succession of acoustic models from each of a plurality of cluster models and producing a cluster likelihood score for each such cluster model as a result of that comparison; and said cluster models are wordstart cluster models, that is, models which only represent the initial portion of many words in said vocabulary. 2. A prefiltering method as described in claim 1 wherein: said acoustic description of the utterance to be recognized includes, in addition to said succession of acoustic descriptions which are compared against the succession of acoustic models of said wordstart cluster models, one or more additional acoustic descriptions which represent a portion of the utterance occurring after that represented by said succession of acoustic descriptions; said method includes storing additional acoustic description cluster models, which represent sounds occurring in vocabulary words after the sounds represented by wordstart cluster models; said using of the cluster likelihood scores to produce prefilter scores includes using the cluster likelihood score produced for each wordstart cluster model to produce an intial prefilter score for words represented by that wordstart cluster model; said method further includes the following extra prefilter scoring steps for each of a plurality of vocabulary words: comparing one or more of said additional acoustic descriptions from the utterance to be recognized against one or more additional acoustic description cluster models representing sounds of that word, and producing an additional score as a result of that comparison; combining said additional score for a word with its initial prefilter score to produce a combined prefilter score for that word; and said selecting of said subset of vocabulary words to undergo more lengthy comparison is based on the combined prefilter scores associated with the vocabulary words.

4. The method of claim 1 , wherein the auto-correction of the target word is performed by obtaining a word from a first library.

4. The method of claim 1 , wherein the auto-correction of the target word is performed by obtaining a word from a first library. 5. The method of claim 4 , wherein the option for modifying the target word includes presenting a suggested word obtained from a second library, wherein the first library differs from the second library.

11. A computer program product for validating expected cohort behavior, the computer program product comprising: a computer readable medium; program code stored on the computer-readable medium for processing sensory data associated with a cohort group to form a set of actual cohort behavior data, wherein each member of the cohort group shares at least one common attribute; program code stored on the computer-readable medium for comparing the set of actual cohort behavior data to a set of predicted cohort behavior models, wherein the set of actual cohort behavior data comprises information describing actual behavior by members of the cohort group and wherein the set of predicted cohort behavior models comprises information describing an expected behavior of members of the cohort group; and program code stored on the computer-readable medium for generating a comparison result, wherein the comparison result indicates an accuracy of the set of predicted cohort behavior models.

11. A computer program product for validating expected cohort behavior, the computer program product comprising: a computer readable medium; program code stored on the computer-readable medium for processing sensory data associated with a cohort group to form a set of actual cohort behavior data, wherein each member of the cohort group shares at least one common attribute; program code stored on the computer-readable medium for comparing the set of actual cohort behavior data to a set of predicted cohort behavior models, wherein the set of actual cohort behavior data comprises information describing actual behavior by members of the cohort group and wherein the set of predicted cohort behavior models comprises information describing an expected behavior of members of the cohort group; and program code stored on the computer-readable medium for generating a comparison result, wherein the comparison result indicates an accuracy of the set of predicted cohort behavior models. 15. The computer program product of claim 11 wherein the set of multimodal sensors comprises a set of digital video cameras, wherein the set of digital video cameras captures a stream of video data associated with the cohort group, and wherein the stream of video data is transmitted to a central data processing system in real time as the stream of video data is generated, and further comprising: program code stored on the computer-readable medium for analyzing the stream of video data by a video analytics engine associated with the central data processing system to generate video metadata describing the members of the cohort group and objects in the stream of video data; and program code stored on the computer-readable medium for identifying actual behaviors of the members of the cohort group using the video metadata.

1. A method, comprising: maintaining, in an automated fashion, a user-specific profile comprising information relating to at least one user interaction with at least one electronic content through at least one computing device, receiving a search request, the search request comprising at least one search term, determining whether the at least one search term has an association with the information in the user-specific profile, and if a search term has an association with the information in the user-specific profile: determining user-specific semantic information relating to the search term based on the association of the search term with the information in the user-profile, adding the user-specific semantic information to the search term, formulating at least one computer-executable query based on the search request and based on the association of the search term with the information in the user-specific profile, the at least one computer-executable query comprising the user-specific semantic information associated with the search term, formulating a first alternative version of the search request based on a first association of the search term with first information in the user-specific profile and formulating a second alternative version of the search request, and executing a first computer-executable query based on the first alternative version of the search request to generate a first search result, executing a second computer-executable query based on the second alternative version of the search request to generate a second search result, and selecting one of the first and second search results.

1. A method, comprising: maintaining, in an automated fashion, a user-specific profile comprising information relating to at least one user interaction with at least one electronic content through at least one computing device, receiving a search request, the search request comprising at least one search term, determining whether the at least one search term has an association with the information in the user-specific profile, and if a search term has an association with the information in the user-specific profile: determining user-specific semantic information relating to the search term based on the association of the search term with the information in the user-profile, adding the user-specific semantic information to the search term, formulating at least one computer-executable query based on the search request and based on the association of the search term with the information in the user-specific profile, the at least one computer-executable query comprising the user-specific semantic information associated with the search term, formulating a first alternative version of the search request based on a first association of the search term with first information in the user-specific profile and formulating a second alternative version of the search request, and executing a first computer-executable query based on the first alternative version of the search request to generate a first search result, executing a second computer-executable query based on the second alternative version of the search request to generate a second search result, and selecting one of the first and second search results. 20. The method of claim 1 , wherein the user-specific semantic information adds a user-specific meaning to the search term according to the user-specific profile, and wherein the method comprises incorporating the user-specific meaning of the search term into the at least one computer-executable query.

8. A speech recognition model created by a method comprising: retrieving for an individual a list of numbers in a calling history; identifying a local neighborhood associated with each number in the calling history; truncating the local neighborhood associated with each number based on at least one parameter; retrieving a local communication network associated with each number in the calling history and each phone number associated with a local neighborhood; and creating, via a processor, a language model for the individual based on the retrieved local communication network.

8. A speech recognition model created by a method comprising: retrieving for an individual a list of numbers in a calling history; identifying a local neighborhood associated with each number in the calling history; truncating the local neighborhood associated with each number based on at least one parameter; retrieving a local communication network associated with each number in the calling history and each phone number associated with a local neighborhood; and creating, via a processor, a language model for the individual based on the retrieved local communication network. 11. The speech recognition model of claim 8 , wherein the language model is one of a deterministic model or a stochastic model.

2. A data processing system, comprising: means for running a testcase against a simulation model of an electronic design, wherein: the simulation model is formed of representations of instances of a plurality of design entities, the instances of the design entities contain a plurality of signals and functional logic that define functional operation of the electronic design, each instance of at least a particular design entity of the plurality of design entities contains an instance of an instrumentation entity that monitors the containing instance of the particular design entity but does not contribute to functional operation of the electronic design, and each instance of the instrumentation entity contains a trace array logically coupled to receive a monitored signal set including at least one signal among the plurality of signals, wherein the trace array is further logically coupled to receive a control signal among the plurality of signals; means for recording trace data for the monitored signal set within the trace array during the running of the testcase, wherein the recording includes concurrently storing within the trace array multiple values of the monitored signal set obtained over multiple cycles of functional operation of the simulation model, wherein the means for recording trace data includes; means for recording, within the trace array, values assumed by the monitored signal set during only those cycles of functional operation during which the control signal is asserted and for refraining from recording values assumed by the monitored signal set during those cycles of functional operation during which the control signal is not asserted, such that no values assumed by the monitored signal set are recorded for those cycles of functional operation during which the control signal is not asserted; means for recording in the trace array a number of functional cycles elapsed between said values assumed by the monitored signal set; and means for exporting said trace data from said trace array in a trace file and storing said trace file in data storage.

2. A data processing system, comprising: means for running a testcase against a simulation model of an electronic design, wherein: the simulation model is formed of representations of instances of a plurality of design entities, the instances of the design entities contain a plurality of signals and functional logic that define functional operation of the electronic design, each instance of at least a particular design entity of the plurality of design entities contains an instance of an instrumentation entity that monitors the containing instance of the particular design entity but does not contribute to functional operation of the electronic design, and each instance of the instrumentation entity contains a trace array logically coupled to receive a monitored signal set including at least one signal among the plurality of signals, wherein the trace array is further logically coupled to receive a control signal among the plurality of signals; means for recording trace data for the monitored signal set within the trace array during the running of the testcase, wherein the recording includes concurrently storing within the trace array multiple values of the monitored signal set obtained over multiple cycles of functional operation of the simulation model, wherein the means for recording trace data includes; means for recording, within the trace array, values assumed by the monitored signal set during only those cycles of functional operation during which the control signal is asserted and for refraining from recording values assumed by the monitored signal set during those cycles of functional operation during which the control signal is not asserted, such that no values assumed by the monitored signal set are recorded for those cycles of functional operation during which the control signal is not asserted; means for recording in the trace array a number of functional cycles elapsed between said values assumed by the monitored signal set; and means for exporting said trace data from said trace array in a trace file and storing said trace file in data storage. 15. The data processing system of claim 2 , wherein said means for storing comprises: means, for each of a plurality of simulation runs, for grouping all trace files from that simulation run in a respective one of a plurality of file system subdirectories that are each dedicated to one of the plurality of simulation runs.

11. At a computer system, a method for automatically resolving semantic errors in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine that are known to have errors, the method comprising: an act of providing the software routine with one or more known inputs and corresponding one or more expected outputs for portions of a program fragment where an error has been localized; an act of learning a correctly functioning program fragment from pairs of input-output descriptions of the program fragment; an act of determining the program statements that can transform one or more given input states into one or more given output states after execution of those program statements; and an act of altering portions of the software routine with the learned program fragments.

11. At a computer system, a method for automatically resolving semantic errors in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine that are known to have errors, the method comprising: an act of providing the software routine with one or more known inputs and corresponding one or more expected outputs for portions of a program fragment where an error has been localized; an act of learning a correctly functioning program fragment from pairs of input-output descriptions of the program fragment; an act of determining the program statements that can transform one or more given input states into one or more given output states after execution of those program statements; and an act of altering portions of the software routine with the learned program fragments. 18. The method of claim 11 , wherein the known inputs and expected outputs are provided by a computer user.

12. A computer implemented method, comprising an implementation using a portion or whole capacity of one or more non-transitory computer readable media with a set of instructions thereon, executable by one or more processing devices, configured, while being or is executed, for representing a context for a body of knowledge by at least one graph comprising: accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of said body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; identifying, using one or more data processing or computing devices, a plurality of ontological subjects of the body of knowledge based on their significance values and/or the association strength between at least two of the ontological subjects of the body of knowledge, and representing the identified ontological subjects graphically, by graphical objects and/or symbols and/or connecting at least two of the associated ontological subjects with graphical links based on their association strength to each other.

12. A computer implemented method, comprising an implementation using a portion or whole capacity of one or more non-transitory computer readable media with a set of instructions thereon, executable by one or more processing devices, configured, while being or is executed, for representing a context for a body of knowledge by at least one graph comprising: accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of said body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; identifying, using one or more data processing or computing devices, a plurality of ontological subjects of the body of knowledge based on their significance values and/or the association strength between at least two of the ontological subjects of the body of knowledge, and representing the identified ontological subjects graphically, by graphical objects and/or symbols and/or connecting at least two of the associated ontological subjects with graphical links based on their association strength to each other. 23. The computer implemented method of claim 12 , further comprising: making a visually displayable graph or network of graphical objects wherein the graphical objects representing the ontological subjects wherein each graphical object is connected to one or more of other graphical objects having association strength of predefined range of values with that graphical object.

19. A non-transitory, computer readable medium that comprises a computer readable program to integrate legacy COBOL data structures to object instances for object-oriented computer systems, wherein the computer readable program when executed on a computer transforms the computer into a machine and causes the computer to perform: receiving a copybook selection and dynamic COBOL construct criteria; importing a copybook from a database, the copybook corresponding with a set of common business oriented language (COBOL) data stored in the database that includes a REDEFINE clause; creating an object model for the copybook; storing the object model in a model library; receiving the set of COBOL data; retrieve the object model; forming, based at least in part on the set of COBOL data, an object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the REDEFINE clause without requiring custom coding for the forming of the object instance; identifying an instance of the REDEFINE clause; and automatically forming the REDEFINE clause as an object instance.

19. A non-transitory, computer readable medium that comprises a computer readable program to integrate legacy COBOL data structures to object instances for object-oriented computer systems, wherein the computer readable program when executed on a computer transforms the computer into a machine and causes the computer to perform: receiving a copybook selection and dynamic COBOL construct criteria; importing a copybook from a database, the copybook corresponding with a set of common business oriented language (COBOL) data stored in the database that includes a REDEFINE clause; creating an object model for the copybook; storing the object model in a model library; receiving the set of COBOL data; retrieve the object model; forming, based at least in part on the set of COBOL data, an object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the REDEFINE clause without requiring custom coding for the forming of the object instance; identifying an instance of the REDEFINE clause; and automatically forming the REDEFINE clause as an object instance. 23. The non-transitory, computer readable medium of claim 19 wherein the computer readable program when executed on the computer further causes the computer to perform: identifying a controlling numeric value for a dynamic COBOL construct clause; identifying an instance of the dynamic COBOL construct clause affecting a dynamic COBOL construct subset; recursively rereading the dynamic COBOL construct subset based at least in part on a new definition specified by the customized object model; and automatically forming each reread portion of the dynamic COBOL construct subset as the object instance.

3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set.

3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. 16. The method of claim 3 , wherein the method is performed by software executing on a machine housing the centralized storage location.

1. A method of automatically creating a hierarchical storyline, the method comprising: receiving a plurality of labelled contextual slices derived from contextual data of a user, each labelled contextual slice comprising a time range, a location, and a contextual label indicating a semantic description of the labelled contextual slice, wherein receiving the plurality of labelled contextual slices comprises: receiving a plurality of contextual slices derived from associated context data collected from a plurality of observation sources, each contextual slice is bound by the time range at the location; and for each of the plurality of contextual slices: identifying a set of candidate labels based on context data associated with the contextual slice, the candidate labels each comprising semantic data describing context data associated with the contextual slice, the semantic data selected from a group consisting of venue geography boundary, venue name, venue type, and venue activity name, venue activity location, venue activity popularity and calendar event; ranking the set of candidate labels by likelihood based on a proximity threshold to the venue geography boundary and ordered by the venue activity popularity, the proximity threshold from the centroid location of the venue geography boundary; and applying one or more of the candidate labels to the contextual slice to make one of the plurality of labelled contextual slices; retrieving, from a storage, a contextual pattern specifying a sequence of contextual labels, wherein the sequence includes a plurality of contextual labels with semantic descriptions that when aggregated correspond to a common semantic description; searching the received labelled contextual slices for a temporally contiguous group of contextual slices having the sequence of contextual labels specified by the pattern; identifying, by a processor, the temporally contiguous group of contextual slices as a matching group responsive to the temporally contiguous group of contextual slices having the sequence of contextual labels specified by the pattern and rank; ordering the matching group of labelled contextual slices by rank; grouping the matching group of labelled contextual slices having at least a minimum threshold rank based on visit year; and applying the common semantic description to the ranked matching group of labelled contextual slices as the user's storyline.

1. A method of automatically creating a hierarchical storyline, the method comprising: receiving a plurality of labelled contextual slices derived from contextual data of a user, each labelled contextual slice comprising a time range, a location, and a contextual label indicating a semantic description of the labelled contextual slice, wherein receiving the plurality of labelled contextual slices comprises: receiving a plurality of contextual slices derived from associated context data collected from a plurality of observation sources, each contextual slice is bound by the time range at the location; and for each of the plurality of contextual slices: identifying a set of candidate labels based on context data associated with the contextual slice, the candidate labels each comprising semantic data describing context data associated with the contextual slice, the semantic data selected from a group consisting of venue geography boundary, venue name, venue type, and venue activity name, venue activity location, venue activity popularity and calendar event; ranking the set of candidate labels by likelihood based on a proximity threshold to the venue geography boundary and ordered by the venue activity popularity, the proximity threshold from the centroid location of the venue geography boundary; and applying one or more of the candidate labels to the contextual slice to make one of the plurality of labelled contextual slices; retrieving, from a storage, a contextual pattern specifying a sequence of contextual labels, wherein the sequence includes a plurality of contextual labels with semantic descriptions that when aggregated correspond to a common semantic description; searching the received labelled contextual slices for a temporally contiguous group of contextual slices having the sequence of contextual labels specified by the pattern; identifying, by a processor, the temporally contiguous group of contextual slices as a matching group responsive to the temporally contiguous group of contextual slices having the sequence of contextual labels specified by the pattern and rank; ordering the matching group of labelled contextual slices by rank; grouping the matching group of labelled contextual slices having at least a minimum threshold rank based on visit year; and applying the common semantic description to the ranked matching group of labelled contextual slices as the user's storyline. 5. The method of claim 1 , wherein the retrieved contextual pattern was obtained by: receiving additional groups of labelled contextual slices identified by the user; and identifying the contextual pattern from a common temporal sequence of contextual labels identified at least a threshold number of instances among the additional groups of labelled contextual slices.

1. A compressed voice communication system, comprising: at least two customer premise devices connected by a transmission media for allowing signals to be transmitted between said customer premise devices; each of said at least two customer premise devices comprising: means for receiving speech from an individual; a speech profile defining coefficients of speech for the individual in a mathematical model; means for detecting changes in the individual's speech, said changes being defined by at least one of said coefficients of speech; means for converting said speech to text which operates in response to means for detecting to add hypertext characters to said text indicative of said detected changes; means for transmitting said text from one customer premise device over said transmission media for receipt at another one of the at least two customer premise devices; means for converting said text received from said transmission media to speech; and means for delivering speech to the individual.

1. A compressed voice communication system, comprising: at least two customer premise devices connected by a transmission media for allowing signals to be transmitted between said customer premise devices; each of said at least two customer premise devices comprising: means for receiving speech from an individual; a speech profile defining coefficients of speech for the individual in a mathematical model; means for detecting changes in the individual's speech, said changes being defined by at least one of said coefficients of speech; means for converting said speech to text which operates in response to means for detecting to add hypertext characters to said text indicative of said detected changes; means for transmitting said text from one customer premise device over said transmission media for receipt at another one of the at least two customer premise devices; means for converting said text received from said transmission media to speech; and means for delivering speech to the individual. 9. The system according to claim 1, wherein said means for converting text received from said transmission media to speech uses the speech profile of the individual whose speech is being converted.

12. The method of claim 10 , wherein the routed search results comprise shared search results and wherein the method further comprises providing the shared search results to at least the first and the second user.

12. The method of claim 10 , wherein the routed search results comprise shared search results and wherein the method further comprises providing the shared search results to at least the first and the second user. 13. The method of claim 12 , wherein the first role of the first user comprises managing the providing the shared search results to at least the first and the second user.

12. A computer-readable storage medium having computer-executable instructions for interacting with a document, comprising: interpreting a published XSD (Extensible Markup Language (XML) Schema Definition), wherein the XSD defines rules relating to the XML file format for documents associated with an application having a rich set of features; and creating an element in an XML file, wherein the element is selected from a set of elements, including: a style element; a hints element that is interpreted according to a hints schema that includes information to assist an external application in displaying text of the of the document; a bookmark element; wherein the bookmark element includes an identifier attribute that associates a start bookmark element with an end bookmark element; wherein two bookmark elements are used in book marking the portion of the document; wherein each of the two bookmark elements include a opening tag and an ending tag; a document properties element; a text element that contains text of the document; wherein all of the text of the document is stored within text elements such that only the text of the document is contained between start text tags and end text tags; wherein there are no intervening tags between each of the start text tags and each of the corresponding end text tags and wherein each of the start text tags do not include formatting information for the text between each of the start text tags and the end text tags; a text run element that includes the formatting information for the text within text elements; a font element; a formatting element; a section element; a paragraphs element; a table element; an outline element; and a proofing element and storing the element in the XML file.

12. A computer-readable storage medium having computer-executable instructions for interacting with a document, comprising: interpreting a published XSD (Extensible Markup Language (XML) Schema Definition), wherein the XSD defines rules relating to the XML file format for documents associated with an application having a rich set of features; and creating an element in an XML file, wherein the element is selected from a set of elements, including: a style element; a hints element that is interpreted according to a hints schema that includes information to assist an external application in displaying text of the of the document; a bookmark element; wherein the bookmark element includes an identifier attribute that associates a start bookmark element with an end bookmark element; wherein two bookmark elements are used in book marking the portion of the document; wherein each of the two bookmark elements include a opening tag and an ending tag; a document properties element; a text element that contains text of the document; wherein all of the text of the document is stored within text elements such that only the text of the document is contained between start text tags and end text tags; wherein there are no intervening tags between each of the start text tags and each of the corresponding end text tags and wherein each of the start text tags do not include formatting information for the text between each of the start text tags and the end text tags; a text run element that includes the formatting information for the text within text elements; a font element; a formatting element; a section element; a paragraphs element; a table element; an outline element; and a proofing element and storing the element in the XML file. 15. The computer-readable medium of claim 12 , wherein the non-structured element includes non-structured feature tags that span other features and are recognized and parsed separately from other XML elements including at least one of: an opening tag and a closing tag.

1. A method implemented in a computing environment for presenting educational materials in a video game environment, the method comprising: a computing system providing a game interface for displaying game characters, each character comprising corresponding attributes that include at least an attack attribute and a defense attribute, the computing system comprising memory operatively coupled to one or more processors; assigning a first character to a first human participant; assigning a second character to a second human participant; the computing system presenting a game environment within the game interface that involves the first character in a storyline and that includes game actions that the first character participates in, wherein the first human participant is presented with educational materials corresponding to a first subject matter, and wherein the game actions include at least one of modifying the attributes that correspond to the first character, obtaining possessions for the first character and using the first character to interact with at least the second game character; the computing system presenting questions to the first human participant when the first character participates in a particular game action within the game environment, wherein the presented questions correspond to educational materials of the first subject matter, and wherein at least one question is presented to the first human participant, corresponding to a virtual attack of the first character by the second character within the game environment; the computing system displaying a first health display element within the game environment that reflects a health status of the first character and that reflects at least a decrease in the health status of the first character as a consequence to damage inflicted by the virtual attack if the first human participant provides an incorrect answer to the at least one question; the computing system displaying a questions menu option within the game environment to the first human participant with which the first human participant is enabled to select or create one or more questions for use in connection with an offensive virtual attack applied by the first character within the game environment; the computing system displaying a second health display element that reflects a health status of the second character and that reflects at least a decrease in the health status of the second character in connection with damage inflicted by the offensive virtual attack by the first character within the game environment; and the computing system providing at least one portal within the game interface which, when entered by the first character, transports the first character to a new world where educational materials presented to the first character correspond to a second subject matter that is different than the first subject matter.

1. A method implemented in a computing environment for presenting educational materials in a video game environment, the method comprising: a computing system providing a game interface for displaying game characters, each character comprising corresponding attributes that include at least an attack attribute and a defense attribute, the computing system comprising memory operatively coupled to one or more processors; assigning a first character to a first human participant; assigning a second character to a second human participant; the computing system presenting a game environment within the game interface that involves the first character in a storyline and that includes game actions that the first character participates in, wherein the first human participant is presented with educational materials corresponding to a first subject matter, and wherein the game actions include at least one of modifying the attributes that correspond to the first character, obtaining possessions for the first character and using the first character to interact with at least the second game character; the computing system presenting questions to the first human participant when the first character participates in a particular game action within the game environment, wherein the presented questions correspond to educational materials of the first subject matter, and wherein at least one question is presented to the first human participant, corresponding to a virtual attack of the first character by the second character within the game environment; the computing system displaying a first health display element within the game environment that reflects a health status of the first character and that reflects at least a decrease in the health status of the first character as a consequence to damage inflicted by the virtual attack if the first human participant provides an incorrect answer to the at least one question; the computing system displaying a questions menu option within the game environment to the first human participant with which the first human participant is enabled to select or create one or more questions for use in connection with an offensive virtual attack applied by the first character within the game environment; the computing system displaying a second health display element that reflects a health status of the second character and that reflects at least a decrease in the health status of the second character in connection with damage inflicted by the offensive virtual attack by the first character within the game environment; and the computing system providing at least one portal within the game interface which, when entered by the first character, transports the first character to a new world where educational materials presented to the first character correspond to a second subject matter that is different than the first subject matter. 14. A method as recited in claim 1 , wherein the method further includes displaying the game interface with a question menu display element, a live chat display element, the first character, at least one other character, health status bar elements, and menu options corresponding to at least a character profile, and an empire map.

11. A system of generating a representation of a plurality of learned rules from a learning engine of an application firewall based on a history of uniform resource locator (URL) communications with a web server, comprising: a learning engine of an application firewall, determining a plurality of learned rules based on a history of URL communications with a web server, each of the plurality of learned rules assigned a URL string, each URL string comprising a path to a resource; and a visualizer executing on a device, categorizing a subset of the plurality of learned rules under a first check type of a plurality of check types, generating a first tree representation of URL strings of the subset of learned rules, each node of the first tree representation corresponding to a segment of the URL strings identified based on application of a first delimiter to the URL strings to segment the URL strings into a first plurality of segments, each of the first plurality of URL strings comprising multiple segments identified based on application of the first selected delimiter, and generating, responsive to changing the first delimiter to a second selected delimiter for the same URL strings via the visualizer responsive to a user operating the visualizer, a second tree representation of the same URL strings of the subset of learned rules change, each node of the second tree corresponding to a segment of the URL strings identified based on application of the second selected delimiter to the URL strings to segment the URL strings into a second plurality of segments, the change allowing a visual comparison of hierarchical distributions of the first plurality of segments and the second plurality of segments between the first tree and the second tree, and distributions of the subset of learned rules corresponding to the first plurality of segments and the second plurality of segments.

11. A system of generating a representation of a plurality of learned rules from a learning engine of an application firewall based on a history of uniform resource locator (URL) communications with a web server, comprising: a learning engine of an application firewall, determining a plurality of learned rules based on a history of URL communications with a web server, each of the plurality of learned rules assigned a URL string, each URL string comprising a path to a resource; and a visualizer executing on a device, categorizing a subset of the plurality of learned rules under a first check type of a plurality of check types, generating a first tree representation of URL strings of the subset of learned rules, each node of the first tree representation corresponding to a segment of the URL strings identified based on application of a first delimiter to the URL strings to segment the URL strings into a first plurality of segments, each of the first plurality of URL strings comprising multiple segments identified based on application of the first selected delimiter, and generating, responsive to changing the first delimiter to a second selected delimiter for the same URL strings via the visualizer responsive to a user operating the visualizer, a second tree representation of the same URL strings of the subset of learned rules change, each node of the second tree corresponding to a segment of the URL strings identified based on application of the second selected delimiter to the URL strings to segment the URL strings into a second plurality of segments, the change allowing a visual comparison of hierarchical distributions of the first plurality of segments and the second plurality of segments between the first tree and the second tree, and distributions of the subset of learned rules corresponding to the first plurality of segments and the second plurality of segments. 16. The system of claim 11 , wherein the first delimiter is specified as one of: a special character, a non-alphabetical character and a non-alphanumeric character.

29. A system for resolving contradicting output data from an Optical Character Recognition (OCR) system, wherein the output data comprises at least one word with at least one uncertainly recognized character, wherein the at least one uncertainly recognized character is reported in the output data together with probable alternatives for the at least one uncertainly recognized character, and the words wherein this at least one uncertainly recognized character has been encountered in an image of a text being processed by the OCR system, the system comprises: a system component using an Internet search engine with search arguments established according to a search strategy comprising: a) the system component provides initial search arguments by forming spelling alternatives for the words comprising the at least one uncertainly recognized character by substituting the at least one uncertainly recognized character with the reported probable alternatives for the at least one character, one by one, and in possible combinations in each encountered word, or by removing a character, thereby forming a plurality of spelling alternatives, and then measuring and recording number of hits for search results of each respective spelling alternative that has been formed in this manner, b) the system component compares the measured number of hits for each of the spelling alternatives with an upper predefined relative threshold level and a lower predefined relative threshold level, wherein each of the respective comparisons of the plurality of measurements falls into one of three possible outcomes: i) if the measurement of a spelling alternative is above the predefined relative upper threshold level, the corresponding spelling alternative for this measurement is the correct spelling alternative for the word, and terminate the Internet search, ii) if the measurement of a spelling alternative is below the lower predefined relative threshold level, the corresponding spelling alternative for this measurement is deemed non-existing, and the word with this spelling alternative is discarded from further investigations, and continue with other spelling alternatives that has been formed as search arguments for the Internet search engine, iii) if the measurement of a spelling alternative falls between the upper relative threshold level and the lower relative threshold level, exit the Internet search engine and modify the search strategy providing further search arguments as a combination of members of the remaining spelling alternatives and other words encountered in the document, other character alternatives for the at least one uncertainly recognized character, phrases, adapting the upper relative threshold level, adapting the lower relative threshold level, and/or other information related to the output data from the OCR system, before continuing using the search strategy providing further measurements and comparisons for resolving the contradicting output data, c) the system component is processing step b) a number of predefined times, or until there is only one spelling alternative left, whatever occurs first, providing an iteration amongst a plurality of different search arguments used in the search strategy before terminating step b), and using the remaining spelling alternative having the highest measurement above the upper relative threshold level as the correct spelling alternative.

29. A system for resolving contradicting output data from an Optical Character Recognition (OCR) system, wherein the output data comprises at least one word with at least one uncertainly recognized character, wherein the at least one uncertainly recognized character is reported in the output data together with probable alternatives for the at least one uncertainly recognized character, and the words wherein this at least one uncertainly recognized character has been encountered in an image of a text being processed by the OCR system, the system comprises: a system component using an Internet search engine with search arguments established according to a search strategy comprising: a) the system component provides initial search arguments by forming spelling alternatives for the words comprising the at least one uncertainly recognized character by substituting the at least one uncertainly recognized character with the reported probable alternatives for the at least one character, one by one, and in possible combinations in each encountered word, or by removing a character, thereby forming a plurality of spelling alternatives, and then measuring and recording number of hits for search results of each respective spelling alternative that has been formed in this manner, b) the system component compares the measured number of hits for each of the spelling alternatives with an upper predefined relative threshold level and a lower predefined relative threshold level, wherein each of the respective comparisons of the plurality of measurements falls into one of three possible outcomes: i) if the measurement of a spelling alternative is above the predefined relative upper threshold level, the corresponding spelling alternative for this measurement is the correct spelling alternative for the word, and terminate the Internet search, ii) if the measurement of a spelling alternative is below the lower predefined relative threshold level, the corresponding spelling alternative for this measurement is deemed non-existing, and the word with this spelling alternative is discarded from further investigations, and continue with other spelling alternatives that has been formed as search arguments for the Internet search engine, iii) if the measurement of a spelling alternative falls between the upper relative threshold level and the lower relative threshold level, exit the Internet search engine and modify the search strategy providing further search arguments as a combination of members of the remaining spelling alternatives and other words encountered in the document, other character alternatives for the at least one uncertainly recognized character, phrases, adapting the upper relative threshold level, adapting the lower relative threshold level, and/or other information related to the output data from the OCR system, before continuing using the search strategy providing further measurements and comparisons for resolving the contradicting output data, c) the system component is processing step b) a number of predefined times, or until there is only one spelling alternative left, whatever occurs first, providing an iteration amongst a plurality of different search arguments used in the search strategy before terminating step b), and using the remaining spelling alternative having the highest measurement above the upper relative threshold level as the correct spelling alternative. 37. The system according to claim 29 , wherein the system component comprises a unit using at least one preceding word further away relative to the word under investigation which comprise a number of characters above a predefined threshold in combination with the word under investigation as the spelling alternative.

11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing.

11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing. 14. The apparatus of claim 11 , further comprising: said processor analyzing all observations; and via said analysis, said processor generating a set of recommendations comprising distilled experiences from a community of users; wherein said recommendations age over time and are discarded if they have relatively little value; and wherein recommendations which are most valuable based on repeated usage are stored into a long term memory.

1. A computer method comprises: receiving a query from a user system; generating a query string that substantially matches characters of the query; searching a plurality of data objects of a first type for data objects of the first type that substantially match the query wherein i) each data object of the first type is associated with at least one data object of a second type, ii) each data object of the first type includes a query, and iii) each data object of the second type includes an answer to a query; generating a first-relevance score for each data object of the second type that is associated with at least one of the data objects of the first type that was identified in the searching step; searching a plurality of data objects of the second type for data objects of the second type that substantially match the query string; generating a second-relevance score for each data object of the second type that substantially matches the query; generating a list of data objects of the second type that are identified in the search of the data objects of the first type and that are identified in the search of the data objects of the second type; ranking the data objects of the second type in the list of data objects based on the first and second relevance scores; and transferring the list of data objects to the user system.

1. A computer method comprises: receiving a query from a user system; generating a query string that substantially matches characters of the query; searching a plurality of data objects of a first type for data objects of the first type that substantially match the query wherein i) each data object of the first type is associated with at least one data object of a second type, ii) each data object of the first type includes a query, and iii) each data object of the second type includes an answer to a query; generating a first-relevance score for each data object of the second type that is associated with at least one of the data objects of the first type that was identified in the searching step; searching a plurality of data objects of the second type for data objects of the second type that substantially match the query string; generating a second-relevance score for each data object of the second type that substantially matches the query; generating a list of data objects of the second type that are identified in the search of the data objects of the first type and that are identified in the search of the data objects of the second type; ranking the data objects of the second type in the list of data objects based on the first and second relevance scores; and transferring the list of data objects to the user system. 2. The method of claim 1 , wherein the data objects of the first type are case objects.

6. The method as claimed in claim 1 , wherein the obtaining comprises: identifying at least one unanswered static attributes from amongst the at least one static attribute of the new case-based document and the plurality of previously processed case-based documents; and computing a static similarity score corresponding to each of the plurality of previously processed case-based documents based at least on a mismatch option associated with the new case-based document.

6. The method as claimed in claim 1 , wherein the obtaining comprises: identifying at least one unanswered static attributes from amongst the at least one static attribute of the new case-based document and the plurality of previously processed case-based documents; and computing a static similarity score corresponding to each of the plurality of previously processed case-based documents based at least on a mismatch option associated with the new case-based document. 11. The method as claimed in claim 6 , wherein a value of the match category is one of confirm, disqualify, both and default.

26. A computing device comprising: a processor; a memory, wherein the memory coupled to the processor which are configured to execute programmed instructions stored in the memory comprising: a) parsing an XML event from the first XML document or the second XML document when an XML event indicator is set, wherein the parsed XML event comprises a start element, the tag value element, and an end element; b) storing the parsed XML event and storing data associated with a tag value element of the parsed XML event as a node in a first data structure or a second data structure, when the parsed XML event is from the first XML document or the second XML document, respectively, the storing further comprising storing, a tag name, a set of tag attributes, and values of the set of tag attributes of the parsed XML event in in the first data structure or the second data structure when the parsed XML event is the start element parsed from the first XML document or the second XML document; c) comparing the stored node of the parsed XML event with one or more nodes stored in the first data structure or the second data structure, based on the parsed XML event and a plurality of parameters wherein the comparing further comprises comparing the tag name of the stored node of the parsed XML event with the tag name of a node stored in the second data structure or the first data structure, when the parsed XML event is the start element from the first XML document or the second XML document, and wherein setting the node comparison indicator of the stored node of the parsed XML event, the node comparison indicator of the node, and the status comparison indicator to TaqMatch, when the taq name of the stored node of the parsed XML event is equal to the taq name of the node and setting the node comparison indicator of the stored node of the parsed XML event, the node comparison indicator of the node, the status comparison indicator to TagMismatch, and the node mismatch indicator to ‘True’, when the tag name of the stored node of the parsed XML event differs from the tag name of the node; d) outputting a comparison result based on the parsed XML event and the plurality of parameters, when a node in the one or more nodes stored in the first data structure or the second data structure is a comparable stored node of the stored node of the parsed XML event; e) deleting the compared stored nodes from the first data structure and the second data structure, based on the parsed XML event and the plurality of parameters, when the compared stored nodes are outputted in the comparison result; f) setting the XML event indicator to the first XML document or the second XML document on processing the step of parsing, the step of storing, the step of comparing, the step of outputting a comparison result, or the step of deleting, based on the plurality of parameters, performing the step (f), whereby the XML event indicator is set to the first XML document; and g) repeating, the steps (a) through (e), or the step (f), in each iteration, until the first XML document and the second XML document are parsed completely.

26. A computing device comprising: a processor; a memory, wherein the memory coupled to the processor which are configured to execute programmed instructions stored in the memory comprising: a) parsing an XML event from the first XML document or the second XML document when an XML event indicator is set, wherein the parsed XML event comprises a start element, the tag value element, and an end element; b) storing the parsed XML event and storing data associated with a tag value element of the parsed XML event as a node in a first data structure or a second data structure, when the parsed XML event is from the first XML document or the second XML document, respectively, the storing further comprising storing, a tag name, a set of tag attributes, and values of the set of tag attributes of the parsed XML event in in the first data structure or the second data structure when the parsed XML event is the start element parsed from the first XML document or the second XML document; c) comparing the stored node of the parsed XML event with one or more nodes stored in the first data structure or the second data structure, based on the parsed XML event and a plurality of parameters wherein the comparing further comprises comparing the tag name of the stored node of the parsed XML event with the tag name of a node stored in the second data structure or the first data structure, when the parsed XML event is the start element from the first XML document or the second XML document, and wherein setting the node comparison indicator of the stored node of the parsed XML event, the node comparison indicator of the node, and the status comparison indicator to TaqMatch, when the taq name of the stored node of the parsed XML event is equal to the taq name of the node and setting the node comparison indicator of the stored node of the parsed XML event, the node comparison indicator of the node, the status comparison indicator to TagMismatch, and the node mismatch indicator to ‘True’, when the tag name of the stored node of the parsed XML event differs from the tag name of the node; d) outputting a comparison result based on the parsed XML event and the plurality of parameters, when a node in the one or more nodes stored in the first data structure or the second data structure is a comparable stored node of the stored node of the parsed XML event; e) deleting the compared stored nodes from the first data structure and the second data structure, based on the parsed XML event and the plurality of parameters, when the compared stored nodes are outputted in the comparison result; f) setting the XML event indicator to the first XML document or the second XML document on processing the step of parsing, the step of storing, the step of comparing, the step of outputting a comparison result, or the step of deleting, based on the plurality of parameters, performing the step (f), whereby the XML event indicator is set to the first XML document; and g) repeating, the steps (a) through (e), or the step (f), in each iteration, until the first XML document and the second XML document are parsed completely. 31. The device of claim 26 , wherein the comparable stored node of a node in the first data structure or the second data structure is a stored node of second data structure or the first data structure, respectively, whereby the tag name and XML level of the comparable stored node and the node are equal.

10. A system for database implementation of electronic checklists, the system comprising: a processor; a template editor controller configured to: display at a user interface, a first electronic checklist template within a template editor define a modified electronic checklist template, wherein the modified electronic checklist template comprises the first electronic checklist template modified based on inputs received at the template editor; an electronic checklist application controller configured to generate a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column.

10. A system for database implementation of electronic checklists, the system comprising: a processor; a template editor controller configured to: display at a user interface, a first electronic checklist template within a template editor define a modified electronic checklist template, wherein the modified electronic checklist template comprises the first electronic checklist template modified based on inputs received at the template editor; an electronic checklist application controller configured to generate a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column. 18. The system according to claim 10 , comprising a checklist instance generator configured to respond to input for a checklist instance of the database implemented electronic checklist template by: retrieving checklist definition information corresponding to the database implemented electronic checklist template; retrieving one or more predefined rules of system behaviour associated with all system controlled columns within the database implemented electronic checklist template; and generating a checklist instance for display at the user interface based on the retrieved checklist definition information; wherein data input within data fields of each system controlled column within the displayed checklist instance is controlled by the retrieved predefined rules of system behaviour associated with said system controlled column.

13. A specification verification system, comprising: a processor device configured to: (a) retain a plurality of abstract documents, each said abstract document of said plurality indicating a value corresponding to a metadata of that document; (b) separate a group of abstract documents based on an input condition of an operation; (c) add a new abstract document to the separated group by using, based on an output condition, at least one said operation within a group of said operations; (d) separate said abstract documents according to overlapping ranges of values designated by each said metadata of abstract documents indicated in said group; (e) unify said group of abstract documents according to overlapping ranges designated by each said metadata of abstract documents indicated in said group; (f) repeat functions (b) to (e) until a termination condition is satisfied; and (g) verify whether an incomplete abstract document exists when said termination condition is satisfied; wherein said plurality of abstract documents associated with a plurality of said metadata are processed; wherein said group of said operations are applied collectively by an operation specification specifying document processing operations; wherein said input condition that is a condition of a range of values of said metadata capable of application of a respective operation is retained for each of said operation; and wherein an output condition that is a change of said metadata value after use of said respective operation is retained for each of said operation.

13. A specification verification system, comprising: a processor device configured to: (a) retain a plurality of abstract documents, each said abstract document of said plurality indicating a value corresponding to a metadata of that document; (b) separate a group of abstract documents based on an input condition of an operation; (c) add a new abstract document to the separated group by using, based on an output condition, at least one said operation within a group of said operations; (d) separate said abstract documents according to overlapping ranges of values designated by each said metadata of abstract documents indicated in said group; (e) unify said group of abstract documents according to overlapping ranges designated by each said metadata of abstract documents indicated in said group; (f) repeat functions (b) to (e) until a termination condition is satisfied; and (g) verify whether an incomplete abstract document exists when said termination condition is satisfied; wherein said plurality of abstract documents associated with a plurality of said metadata are processed; wherein said group of said operations are applied collectively by an operation specification specifying document processing operations; wherein said input condition that is a condition of a range of values of said metadata capable of application of a respective operation is retained for each of said operation; and wherein an output condition that is a change of said metadata value after use of said respective operation is retained for each of said operation. 15. The system according to claim 13 , wherein said termination condition comprises detecting that said abstract documents have not been changed by said applied operations.

1. A computer-implemented method for scanning a text index and a metadata index, in parallel, to identify entries that satisfy both a metadata condition and a text condition included in a query, comprising: in response to receiving the query, executing a query processing application on a processor, wherein the application is configured to iteratively scan the text index and the metadata index, wherein the scanning comprises: advancing a current position in the text index and a current position in the metadata index to a respective next entry in the text index and the metadata index which references a respective document that satisfies the respective text condition and metadata condition, upon determining that the current position in the text index and the current position in the metadata index each advanced to a position referencing the same document, adding that document to a set of query results for the query, and upon determining that the respective current positions in the text index and the metadata index are different relative to one another, advancing the current position of one of the text index and the metadata index to the current position of the other index.

1. A computer-implemented method for scanning a text index and a metadata index, in parallel, to identify entries that satisfy both a metadata condition and a text condition included in a query, comprising: in response to receiving the query, executing a query processing application on a processor, wherein the application is configured to iteratively scan the text index and the metadata index, wherein the scanning comprises: advancing a current position in the text index and a current position in the metadata index to a respective next entry in the text index and the metadata index which references a respective document that satisfies the respective text condition and metadata condition, upon determining that the current position in the text index and the current position in the metadata index each advanced to a position referencing the same document, adding that document to a set of query results for the query, and upon determining that the respective current positions in the text index and the metadata index are different relative to one another, advancing the current position of one of the text index and the metadata index to the current position of the other index. 8. The computer-implemented method of claim 1 , wherein the text index and the metadata index are sorted according to a common ordering.

7. A computer-implemented method comprising: locating a plurality of digital images at a plurality of websites; storing the plurality of digital images in a first database with a link to the corresponding website of the plurality of websites from which each digital image of the plurality of digital images was located; calculating an image index file for each of the stored digital images, each image index file comprising a plurality of image metrics representative of two or more regions of the corresponding stored digital image and comprising the link to the corresponding website from which the digital image was located; storing the image index files in a second database; deleting the plurality of stored digital images from the first database when the corresponding image index file of each of the plurality of digital images is stored in the second database; and clustering the stored digital images, wherein clustering the stored digital images comprises: dividing each stored digital image into a plurality of cells; calculating a plurality of image metrics for each of the plurality of cells; aligning the plurality of image metrics with the plurality of the cells to generate a plurality of numerical descriptors for the plurality of image metrics; and grouping the digital image with other similar stored digital images based on a comparison of the numerical descriptors.

7. A computer-implemented method comprising: locating a plurality of digital images at a plurality of websites; storing the plurality of digital images in a first database with a link to the corresponding website of the plurality of websites from which each digital image of the plurality of digital images was located; calculating an image index file for each of the stored digital images, each image index file comprising a plurality of image metrics representative of two or more regions of the corresponding stored digital image and comprising the link to the corresponding website from which the digital image was located; storing the image index files in a second database; deleting the plurality of stored digital images from the first database when the corresponding image index file of each of the plurality of digital images is stored in the second database; and clustering the stored digital images, wherein clustering the stored digital images comprises: dividing each stored digital image into a plurality of cells; calculating a plurality of image metrics for each of the plurality of cells; aligning the plurality of image metrics with the plurality of the cells to generate a plurality of numerical descriptors for the plurality of image metrics; and grouping the digital image with other similar stored digital images based on a comparison of the numerical descriptors. 14. The computer-implemented method of claim 7 , wherein calculating the image index file for each of the stored digital images comprises: dividing each stored digital image into a plurality of cells; calculating a plurality of image metrics for each of the plurality of cells; and aligning the plurality of image metrics with the plurality of cells to generate a plurality of numerical descriptors for the plurality of image metrics, wherein each image index file further comprises the plurality of numerical descriptors.

21. A spine stabilization device comprising: a first element; a second element; and a self-centering joint connecting the first element and the second element; wherein the self-centering joint includes, a housing having a socket; a retainer received in the socket such that the retainer is deflectable relative to the housing; and a centering rod having an inner core and an outer sheath, the centering rod received partially within retainer and partially within the housing; and whereby deflection of the retainer bends the centering rod and the centering rod exerts a restoring force on the retainer.

21. A spine stabilization device comprising: a first element; a second element; and a self-centering joint connecting the first element and the second element; wherein the self-centering joint includes, a housing having a socket; a retainer received in the socket such that the retainer is deflectable relative to the housing; and a centering rod having an inner core and an outer sheath, the centering rod received partially within retainer and partially within the housing; and whereby deflection of the retainer bends the centering rod and the centering rod exerts a restoring force on the retainer. 23. The spine stabilization device of claim 21 , wherein said inner core of said centering rod is made of nitinol.

6. The method of claim 1 , wherein the step of using the graphical user interface to create an aggregation further comprises creating the graphical representations of the annotations and search terms by: creating a separate display window within the graphical user interface for each annotation and for each search term; and entering an annotation or search term into each display window.

6. The method of claim 1 , wherein the step of using the graphical user interface to create an aggregation further comprises creating the graphical representations of the annotations and search terms by: creating a separate display window within the graphical user interface for each annotation and for each search term; and entering an annotation or search term into each display window. 7. The method of claim 6 , wherein the step of entering an annotation or search term into each display window further comprises at least one of typing an annotation or search term into a given display window and selecting an annotation or search term from an exposable drop-down list of annotations and search terms associated with each display window.

13. A doctor and patient communication system comprising: an audio visual asset recorded by a doctor using a predetermined script to communicate with a patient; a plurality of audio visual segments created by partitioning the audio visual asset such that a variable final message compilation is anticipated; at least one of a naming paradigm and a data tagging system to tag the plurality of audio visual segments such that the plurality of audio visual segments are accessible via an audio visual data tag and are exported to the variable final message compilation; a multimedia synthesis compiler to compile the variable final message compilation upon uploading of the plurality of audio visual segments into the multimedia synthesis compiler; and a message sent to the patient from the variable final message compilation based on the plurality of audio visual segments.

13. A doctor and patient communication system comprising: an audio visual asset recorded by a doctor using a predetermined script to communicate with a patient; a plurality of audio visual segments created by partitioning the audio visual asset such that a variable final message compilation is anticipated; at least one of a naming paradigm and a data tagging system to tag the plurality of audio visual segments such that the plurality of audio visual segments are accessible via an audio visual data tag and are exported to the variable final message compilation; a multimedia synthesis compiler to compile the variable final message compilation upon uploading of the plurality of audio visual segments into the multimedia synthesis compiler; and a message sent to the patient from the variable final message compilation based on the plurality of audio visual segments. 15. The method of claim 13 wherein the multimedia synthesis compiler compiles the variable final message compilation such that the final message compilation is outputted in a plurality of audio visual formats.

7. The computer program of claim 1 , wherein the database further comprises one or more URL addresses, wherein the engine is operative to display the URL addresses at the user interface, and wherein further the one or more URL addresses are associated with the predefined questions and answers of the database so that the display of the URL addresses at the user interface is dependent upon a user's answers to questions from the database.

7. The computer program of claim 1 , wherein the database further comprises one or more URL addresses, wherein the engine is operative to display the URL addresses at the user interface, and wherein further the one or more URL addresses are associated with the predefined questions and answers of the database so that the display of the URL addresses at the user interface is dependent upon a user's answers to questions from the database. 8. The computer program of claim 7 , wherein the engine is operative to display a plurality of the URL addresses at the user interface in a sequence the order of which is defined by a user's answers to questions from the database.

11. A system comprising: a user interface device; and one or more computers operable to interact with the user interface device and to: receive from a first user of the user interface device a first media object and a first query relating to content in the first media object, wherein the first query requests information identifying content presented in the first media object; provide for presentation the first media object and the first query to a plurality of second users different from the first user; receive a suggested answer to the first query from each of a group of second users of the plurality of second users, where at least two of the suggested answers are distinct, and wherein a suggested answer from a particular second user is either a new suggested answer submitted by the particular second user in response to the first query or a previous suggested answer to the first query selected by the particular second user, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the first query; group similar suggested answers based on a semantic similarity measure; rank the suggested answers where each group of similar suggested answers is given a combined ranking; and provide for presentation one or more of the ranked suggested answers to the first user on the user interface device.

11. A system comprising: a user interface device; and one or more computers operable to interact with the user interface device and to: receive from a first user of the user interface device a first media object and a first query relating to content in the first media object, wherein the first query requests information identifying content presented in the first media object; provide for presentation the first media object and the first query to a plurality of second users different from the first user; receive a suggested answer to the first query from each of a group of second users of the plurality of second users, where at least two of the suggested answers are distinct, and wherein a suggested answer from a particular second user is either a new suggested answer submitted by the particular second user in response to the first query or a previous suggested answer to the first query selected by the particular second user, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the first query; group similar suggested answers based on a semantic similarity measure; rank the suggested answers where each group of similar suggested answers is given a combined ranking; and provide for presentation one or more of the ranked suggested answers to the first user on the user interface device. 18. The system of claim 11 , where the one or more computers are further operable to: provide data to the first user on the user interface device for presentation, the data relating to one or more media object and query pairs received from the first user or one or more suggested answers submitted or selected by the first user in response to media object and query pairs received from second users.

9. The information processing system of claim 7 , further comprising: associating a third set of data within the cognitive graph with a third cognitive graph vector of the plurality of cognitive graph vectors; and, wherein the refining the cognitive insights based upon the limitation relating to one of the plurality of cognitive graph vectors further comprises identifying a limitation on one of the first, second and third cognitive graph vectors and refining another of the first, second and third cognitive graph vectors based upon the limitation of one of the first, second and third cognitive graph vectors.

9. The information processing system of claim 7 , further comprising: associating a third set of data within the cognitive graph with a third cognitive graph vector of the plurality of cognitive graph vectors; and, wherein the refining the cognitive insights based upon the limitation relating to one of the plurality of cognitive graph vectors further comprises identifying a limitation on one of the first, second and third cognitive graph vectors and refining another of the first, second and third cognitive graph vectors based upon the limitation of one of the first, second and third cognitive graph vectors. 10. The information processing system of claim 9 , wherein: the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from a cognitive graph nexus; the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph nexus; the third cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third cognitive graph vector away from the cognitive graph nexus; the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices; the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices and data within a third; and the refining further comprising limiting the third set of data to data within a third certain index of the third cognitive graph vector indices.

10. The method of claim 9 further comprising: storing the first token of the sequence of tokens associated with the label B of the BIO encoding scheme as a beginning of a brand name token; and concatenating to the brand name token each subsequent token of the sequence of tokens that is associated with the label I of the BIO encoding scheme.

10. The method of claim 9 further comprising: storing the first token of the sequence of tokens associated with the label B of the BIO encoding scheme as a beginning of a brand name token; and concatenating to the brand name token each subsequent token of the sequence of tokens that is associated with the label I of the BIO encoding scheme. 11. The method of claim 10 wherein normalizing the attribute for each token of the sequence of tokens to create the standardized representations of the attribute for each token of the sequence of tokens comprises: comparing the brand name token with a normalization dictionary to determine a standardized representation of the brand name, wherein the standardized representations comprise the standardized representation; and writing the standardized representation of the brand name to a database entry associated with the product.

11. A system, comprising: one or more computer processors; a memory containing a program, which when executed by the one or more computer processors is configured to perform an operation comprising: receiving a database request having a projection operation for all of a plurality of columns in one or more tables, wherein the projection operation comprises a SELECT statement having a column list that includes having (i) a shorthand that specifies all of the plurality of columns and (ii) a substitute clause that specifies a column from the plurality of columns and an expression, wherein the shorthand comprises a wildcard that expands to specify all of the plurality of columns, the shorthand being less than a plurality of column references to the plurality of columns; responsive to the request, retrieving one or more data records having the plurality of columns including the specified column; evaluating the specified expression to generate an expression result corresponding to a respective data record of the one or more data records; and generating a result set comprised of the one of more data records having the plurality of columns, such that, for the respective data record, a value for the specified column is replaced with the corresponding expression result, wherein a number of columns in the result set is the same as the number of the plurality of columns in the one or more tables and specified by the shorthand.

11. A system, comprising: one or more computer processors; a memory containing a program, which when executed by the one or more computer processors is configured to perform an operation comprising: receiving a database request having a projection operation for all of a plurality of columns in one or more tables, wherein the projection operation comprises a SELECT statement having a column list that includes having (i) a shorthand that specifies all of the plurality of columns and (ii) a substitute clause that specifies a column from the plurality of columns and an expression, wherein the shorthand comprises a wildcard that expands to specify all of the plurality of columns, the shorthand being less than a plurality of column references to the plurality of columns; responsive to the request, retrieving one or more data records having the plurality of columns including the specified column; evaluating the specified expression to generate an expression result corresponding to a respective data record of the one or more data records; and generating a result set comprised of the one of more data records having the plurality of columns, such that, for the respective data record, a value for the specified column is replaced with the corresponding expression result, wherein a number of columns in the result set is the same as the number of the plurality of columns in the one or more tables and specified by the shorthand. 12. The system of claim 11 , wherein the substitute clause comprises a SUBSTITUTE key word and a comma-delimited argument list comprised of a column reference to the specified column and the expression.

1. An electronic document analysis method receiving N electronic documents pertaining to a case encompassing a set of issues including at least one issue and establishing relevance of at least the N electronic documents to at least one individual issue in the set of issues, the method performed with a processor, the method comprising, for at least one individual issue from among said set of issues: i. receiving an output of a categorization process applied to documents in at least control subsets of said at least N electronic documents, said output including, for each document in said subsets, one of a relevant-to-said-individual issue indication and a non-relevant-to-said-individual issue indication; ii. seeking an input as to whether or not to initiate a new iteration I; if a new iteration is initiated, perform steps iii-x; and if a new iteration is not initiated, go to step xi; iii. selecting m electronic documents from among a subset of the N electronic documents that are not in the control set and that were not used in previous rounds for training the classifier; iv. receiving an output of a categorization process applied to the m electronic documents; v. adding the m electronic documents to an existing training subset and building a text classifier simulating said categorization process using said output for all documents in said training subset of documents; vi. evaluating said text classifier's quality using said output for documents in said control subset; vii. selecting a cut-off point for binarizing said rankings of said documents in said control subset; viii. using said cut-off point, computing and storing at least one quality criterion characterizing said binarizing of said rankings of said documents in said control subset, thereby to define a quality of performance indication of a current iteration I; ix. displaying a comparison of the quality of performance indication of the current iteration I to quality of performance indications of previous iterations; x. returning to step ii; and xi. generating a computer display of said output of said categorization process received in step i as most recently performed, including, for each document in said subsets, one of a relevant-to-said-individual issue indication and a non-relevant-to-said-individual issue indication.

1. An electronic document analysis method receiving N electronic documents pertaining to a case encompassing a set of issues including at least one issue and establishing relevance of at least the N electronic documents to at least one individual issue in the set of issues, the method performed with a processor, the method comprising, for at least one individual issue from among said set of issues: i. receiving an output of a categorization process applied to documents in at least control subsets of said at least N electronic documents, said output including, for each document in said subsets, one of a relevant-to-said-individual issue indication and a non-relevant-to-said-individual issue indication; ii. seeking an input as to whether or not to initiate a new iteration I; if a new iteration is initiated, perform steps iii-x; and if a new iteration is not initiated, go to step xi; iii. selecting m electronic documents from among a subset of the N electronic documents that are not in the control set and that were not used in previous rounds for training the classifier; iv. receiving an output of a categorization process applied to the m electronic documents; v. adding the m electronic documents to an existing training subset and building a text classifier simulating said categorization process using said output for all documents in said training subset of documents; vi. evaluating said text classifier's quality using said output for documents in said control subset; vii. selecting a cut-off point for binarizing said rankings of said documents in said control subset; viii. using said cut-off point, computing and storing at least one quality criterion characterizing said binarizing of said rankings of said documents in said control subset, thereby to define a quality of performance indication of a current iteration I; ix. displaying a comparison of the quality of performance indication of the current iteration I to quality of performance indications of previous iterations; x. returning to step ii; and xi. generating a computer display of said output of said categorization process received in step i as most recently performed, including, for each document in said subsets, one of a relevant-to-said-individual issue indication and a non-relevant-to-said-individual issue indication. 2. The method according to claim 1 wherein said receiving comprises receiving an output of a categorization process performed by a human operator.

2. The method according to claim 1 , further comprising receiving, by the computer, at least one characteristic of the user, wherein the plurality of attributes are matched against the at least one characteristic of the user.

2. The method according to claim 1 , further comprising receiving, by the computer, at least one characteristic of the user, wherein the plurality of attributes are matched against the at least one characteristic of the user. 3. The method according to claim 2 , wherein the at least one characteristic of the user comprises the individual's domain knowledge.

1. A collaborative language translation system that allocates as between automated and manual language translation services, said collaborative language translation system comprising: (a) a credential protected language translation data portal for a manual language translator to gain access to a manual language translator section; (b) a unique database associated with the manual language translator in said manual language translator section, said unique database includes information selected from the group consisting of manual language translator specific languages capability for translation, accuracy skill level for each language translated, a technical scientific language lexicon expertise skill set based upon the manual language translator's specific science background, confidentiality capabilities, scope of language translation project required, and language translation turnaround time availability forming a unique database criteria; (c) a credential protected language translation portal for a language translation client to gain access to a language translation client section, wherein the language translation client initiates a selected language translation to be completed; (d) a unique information set associated with the language translation client in said language translation client section, said unique information set includes a client original language, a client required language, a client required confidentiality level, a client required scope of translated material, a client required translation format, and a plurality of selectable sliding bar scales all within a single display panel for the language translation client to select information to specify the language translation needs of the client, each of said plurality of selectable sliding bar scales are associated with a client selected language translation accuracy from low to high, a client selected language translation speed from low to high, a client selected language translation cost from low to high, and a client selected language translation technical lexicon that are all associated with said selected language translation to be completed, wherein said unique information set forming a unique information set criteria is stored for the language translation client and said unique information set is retrievable for the language translation client for said unique information set criteria of the language translation needs of the client for future language translations; (e) an automated language translation database including an automated language translation database criteria of accuracy, speed, cost, and scientific technical language lexicon; (f) one or more processors; (g) memory; (h) one or more programs, wherein said one or more programs are stored in said memory and configured to be executed by said one or more processors, said one or more programs including: (h)(i) instructions for allocating a flow of said unique information set criteria as between said unique database criteria and said automated language translation database criteria based upon the client initiated said unique information set criteria associated with said selected language translation to be completed; and (h)(ii) instructions to perform said selected language translation to be completed for the language translation client.

1. A collaborative language translation system that allocates as between automated and manual language translation services, said collaborative language translation system comprising: (a) a credential protected language translation data portal for a manual language translator to gain access to a manual language translator section; (b) a unique database associated with the manual language translator in said manual language translator section, said unique database includes information selected from the group consisting of manual language translator specific languages capability for translation, accuracy skill level for each language translated, a technical scientific language lexicon expertise skill set based upon the manual language translator's specific science background, confidentiality capabilities, scope of language translation project required, and language translation turnaround time availability forming a unique database criteria; (c) a credential protected language translation portal for a language translation client to gain access to a language translation client section, wherein the language translation client initiates a selected language translation to be completed; (d) a unique information set associated with the language translation client in said language translation client section, said unique information set includes a client original language, a client required language, a client required confidentiality level, a client required scope of translated material, a client required translation format, and a plurality of selectable sliding bar scales all within a single display panel for the language translation client to select information to specify the language translation needs of the client, each of said plurality of selectable sliding bar scales are associated with a client selected language translation accuracy from low to high, a client selected language translation speed from low to high, a client selected language translation cost from low to high, and a client selected language translation technical lexicon that are all associated with said selected language translation to be completed, wherein said unique information set forming a unique information set criteria is stored for the language translation client and said unique information set is retrievable for the language translation client for said unique information set criteria of the language translation needs of the client for future language translations; (e) an automated language translation database including an automated language translation database criteria of accuracy, speed, cost, and scientific technical language lexicon; (f) one or more processors; (g) memory; (h) one or more programs, wherein said one or more programs are stored in said memory and configured to be executed by said one or more processors, said one or more programs including: (h)(i) instructions for allocating a flow of said unique information set criteria as between said unique database criteria and said automated language translation database criteria based upon the client initiated said unique information set criteria associated with said selected language translation to be completed; and (h)(ii) instructions to perform said selected language translation to be completed for the language translation client. 4. A collaborative language translation system according to claim 1 wherein said unique database criteria further includes a specific manual language translator identifier and said unique information set criteria further includes a client required specific manual language translator identifier.

1. A method of filtering documents considered to be relevant to a subject, comprising: selecting a set of documents considered to be relevant to a subject, wherein each document is an electronic document that comprise two or more distinct fields including at least a first field and a second field, each of the two or more distinct fields providing data corresponding to a category of data about the respective document; clustering documents in the set of documents into a cluster hierarchy according to data contained in the first field, the cluster hierarchy comprising a plurality of branches, each branch having a sub-tree; merging a received number of levels of the cluster hierarchy; and re-clustering the merged levels according to data contained in the second field.

1. A method of filtering documents considered to be relevant to a subject, comprising: selecting a set of documents considered to be relevant to a subject, wherein each document is an electronic document that comprise two or more distinct fields including at least a first field and a second field, each of the two or more distinct fields providing data corresponding to a category of data about the respective document; clustering documents in the set of documents into a cluster hierarchy according to data contained in the first field, the cluster hierarchy comprising a plurality of branches, each branch having a sub-tree; merging a received number of levels of the cluster hierarchy; and re-clustering the merged levels according to data contained in the second field. 17. The method of claim 1 , wherein at least one of the documents is an e-mail and the first field and the second field each comprise one of: a sender, a recipient, a subject line, body text, and an attachment.