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16. A computer-implemented method for processing documents in a document database, the documents having an initial ranking based upon a user search query provided by a user using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising: operating the processor to perform the following selecting N top ranked documents from the retrieved documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents, with at least one of the vocabulary words not being in the user search query; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved documents based on counting how many times a respective vocabulary word is used in the N top ranked documents; and counting how many of the N top ranked documents uses the respective vocabulary word; generating a re-ranking of the N top ranked documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the documents, and for each document being displayed, also to display its initial ranking.

16. A computer-implemented method for processing documents in a document database, the documents having an initial ranking based upon a user search query provided by a user using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising: operating the processor to perform the following selecting N top ranked documents from the retrieved documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents, with at least one of the vocabulary words not being in the user search query; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved documents based on counting how many times a respective vocabulary word is used in the N top ranked documents; and counting how many of the N top ranked documents uses the respective vocabulary word; generating a re-ranking of the N top ranked documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the documents, and for each document being displayed, also to display its initial ranking. 25. A computer-implemented method according to claim 16 further comprising determining which documents from the N top ranked documents are relevant to the user search query; and wherein generating the re-ranking of the retrieved documents is also based on the relevant documents.

1. A method, comprising: a first party providing an advertisement on a media channel on behalf of an advisor, wherein the advertisement is listed to a user and includes at least a reference to establish a real-time communication connection with the advisor and indicates whether the advisor is currently available to communicate via real-time communication at a time when the user is viewing the advertisement; while the advisor is currently available, receiving a user selection of the reference corresponding to the advisor; and a central controller using the selection from the user to establish a real-time communication connection between the advisor and the user prior to the user submitting a question for the advisor, including the central controller establishing a real-time communication with the user and the central controller establishing a real-time communication with the advisor; and the first party charging an amount for the real-time communication connection established between the advisor and the user according to the advertisement.

1. A method, comprising: a first party providing an advertisement on a media channel on behalf of an advisor, wherein the advertisement is listed to a user and includes at least a reference to establish a real-time communication connection with the advisor and indicates whether the advisor is currently available to communicate via real-time communication at a time when the user is viewing the advertisement; while the advisor is currently available, receiving a user selection of the reference corresponding to the advisor; and a central controller using the selection from the user to establish a real-time communication connection between the advisor and the user prior to the user submitting a question for the advisor, including the central controller establishing a real-time communication with the user and the central controller establishing a real-time communication with the advisor; and the first party charging an amount for the real-time communication connection established between the advisor and the user according to the advertisement. 16. The method of claim 1 , wherein the amount is charged according to a price specified by the advisor.

12. A method of processing an object model located on a computer readable storage medium, the method comprising: receiving a directed relationship of class objects; processing the directed relationship into a tree structure that depicts at least relationships and properties of the class objects, the tree structure comprising one or more nodes corresponding to the received graph of objects, wherein at least one of the nodes includes a plurality of changeable graphical symbols displayed on the node that are configured to change graphics upon activation, and wherein, upon activation of a first changeable graphical symbol, the first changeable graphical symbol dynamically expands to display one or more previously unseen inheritance hierarchy graph objects or collapses to hide one or more previously displayed inheritance hierarchy graph objects, and wherein, upon activation of a second changeable graphical symbol, the second changeable graphical symbol dynamically expands to display one or more previously unseen relationship hierarchy graph objects or collapses to hide one or more previously displayed relationship hierarchy graph objects; presenting the tree structure as a diagram that is interactive, the user interaction comprising receiving inputs from a user that actuate at least one of the displayed changeable graphical symbols to expand or collapse inheritance hierarchy or relationship hierarchy graph objects and further indicate that at least one of the nodes displayed in the editable treelike structure is to be repositioned within the treelike structure, automatically and dynamically expanding at least a portion of the graph of objects to display one or more previously unseen inheritance hierarchy or relationship hierarchy graph objects or collapsing at least a portion of the graph of objects to hide one or more previously displayed inheritance hierarchy or relationship hierarchy graph objects and automatically repositioning the node according to the received input, wherein connecting lines attached to the at least one node are automatically adjusted to an optimal position determined based on the structure's real estate; and automatically highlighting or otherwise automatically graphically indicating indicate the propagation of future user actions from a selected node of the treelike structure through other nodes having directed relationships to said selected node.

12. A method of processing an object model located on a computer readable storage medium, the method comprising: receiving a directed relationship of class objects; processing the directed relationship into a tree structure that depicts at least relationships and properties of the class objects, the tree structure comprising one or more nodes corresponding to the received graph of objects, wherein at least one of the nodes includes a plurality of changeable graphical symbols displayed on the node that are configured to change graphics upon activation, and wherein, upon activation of a first changeable graphical symbol, the first changeable graphical symbol dynamically expands to display one or more previously unseen inheritance hierarchy graph objects or collapses to hide one or more previously displayed inheritance hierarchy graph objects, and wherein, upon activation of a second changeable graphical symbol, the second changeable graphical symbol dynamically expands to display one or more previously unseen relationship hierarchy graph objects or collapses to hide one or more previously displayed relationship hierarchy graph objects; presenting the tree structure as a diagram that is interactive, the user interaction comprising receiving inputs from a user that actuate at least one of the displayed changeable graphical symbols to expand or collapse inheritance hierarchy or relationship hierarchy graph objects and further indicate that at least one of the nodes displayed in the editable treelike structure is to be repositioned within the treelike structure, automatically and dynamically expanding at least a portion of the graph of objects to display one or more previously unseen inheritance hierarchy or relationship hierarchy graph objects or collapsing at least a portion of the graph of objects to hide one or more previously displayed inheritance hierarchy or relationship hierarchy graph objects and automatically repositioning the node according to the received input, wherein connecting lines attached to the at least one node are automatically adjusted to an optimal position determined based on the structure's real estate; and automatically highlighting or otherwise automatically graphically indicating indicate the propagation of future user actions from a selected node of the treelike structure through other nodes having directed relationships to said selected node. 13. The method of claim 12 , further comprising depicting the class objects with associated symbols that facilitate, expanding and collapsing an inheritance hierarchy of the tree structure; expanding and collapsing relationships of the tree structure; and exposing and hiding property information of the class objects.

1. A computer-implemented method for facilitating a semantic search, the method comprising: identifying a corpora of natural language texts including a plurality of sentences; performing a syntactic-semantic analysis on each sentence of the plurality of sentences using a linguistic description associated with a language of the sentence, wherein the syntactic-semantic analysis comprises: generating a graph of generalized constituents for each sentence of the plurality of sentences; and generating one or more syntactic trees based on the graphs of generalized constituents to represent the corresponding sentences; generating at least one syntactic structure for each sentence of the plurality of sentences by selecting a best syntactic tree from the generated one or more syntactic trees to represent the at least one syntactic structure of the sentence; generating a semantic structure for each sentence of the corpora of natural language texts, based on the generated at least one syntactic structure of the sentence, wherein the semantic structure is language independent and wherein the semantic structure comprises semantic classes, semantemes, deep slots, and non-tree links; associating the generated syntactic structures and the generated semantic structures with the respective sentences; creating syntactic index for each meaning of at least one linguistic parameter of each of the generated syntactic structures; creating a semantic index for each meaning of at least one parameter of the semantic structures; receiving a search query comprising semantic language-independent terms; searching the semantic index based on the semantic language-independent terms and the language-independent semantic structures; and receiving semantic search results from the semantic index, wherein the search results from the corpora of natural language texts includes sentences in different languages.

1. A computer-implemented method for facilitating a semantic search, the method comprising: identifying a corpora of natural language texts including a plurality of sentences; performing a syntactic-semantic analysis on each sentence of the plurality of sentences using a linguistic description associated with a language of the sentence, wherein the syntactic-semantic analysis comprises: generating a graph of generalized constituents for each sentence of the plurality of sentences; and generating one or more syntactic trees based on the graphs of generalized constituents to represent the corresponding sentences; generating at least one syntactic structure for each sentence of the plurality of sentences by selecting a best syntactic tree from the generated one or more syntactic trees to represent the at least one syntactic structure of the sentence; generating a semantic structure for each sentence of the corpora of natural language texts, based on the generated at least one syntactic structure of the sentence, wherein the semantic structure is language independent and wherein the semantic structure comprises semantic classes, semantemes, deep slots, and non-tree links; associating the generated syntactic structures and the generated semantic structures with the respective sentences; creating syntactic index for each meaning of at least one linguistic parameter of each of the generated syntactic structures; creating a semantic index for each meaning of at least one parameter of the semantic structures; receiving a search query comprising semantic language-independent terms; searching the semantic index based on the semantic language-independent terms and the language-independent semantic structures; and receiving semantic search results from the semantic index, wherein the search results from the corpora of natural language texts includes sentences in different languages. 10. The computer-implemented method of claim 1 , wherein the method further comprises: performing a search query and sending a search result based at least in part upon the semantic index.

11. A computer-implemented method for providing full-text search integration in XQuery, comprising: implementing a built-in search function defined in an XQuery language and initiating a full-text search, wherein the search function comprises one or more search terms and a relation logic; identifying variants for each search term comprised in the search function and obtaining posting lists for one or more of the variants, each posting list comprising values offset from elements containing the search term associated with the variant to which the posting list corresponds; applying the relation logic to the offset values of the posting lists; selecting those elements with offset values that satisfy the relation logic; and providing the elements that satisfy the relation logic as results of the full-text search.

11. A computer-implemented method for providing full-text search integration in XQuery, comprising: implementing a built-in search function defined in an XQuery language and initiating a full-text search, wherein the search function comprises one or more search terms and a relation logic; identifying variants for each search term comprised in the search function and obtaining posting lists for one or more of the variants, each posting list comprising values offset from elements containing the search term associated with the variant to which the posting list corresponds; applying the relation logic to the offset values of the posting lists; selecting those elements with offset values that satisfy the relation logic; and providing the elements that satisfy the relation logic as results of the full-text search. 13. The computer-implemented method according to claim 11 , wherein the results are ordered by: assigning a score to each result; and ordering the results in descending order based on the assigned score.

1. A method for enabling global grammars for a particular multimodal application, the method implemented with a multimodal browser and a multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the method comprising: loading a multimodal web page; determining whether the loaded multimodal web page is one of a plurality of multimodal web pages of the particular multimodal application; if the loaded multimodal web page is one of the plurality of multimodal web pages of the particular multimodal application, loading any currently unloaded global grammars in the loaded multimodal web page and maintaining any previously loaded global grammars; and if the loaded multimodal web page is not one of the plurality of multimodal web pages of the particular multimodal application, unloading any currently loaded global grammars.

1. A method for enabling global grammars for a particular multimodal application, the method implemented with a multimodal browser and a multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the method comprising: loading a multimodal web page; determining whether the loaded multimodal web page is one of a plurality of multimodal web pages of the particular multimodal application; if the loaded multimodal web page is one of the plurality of multimodal web pages of the particular multimodal application, loading any currently unloaded global grammars in the loaded multimodal web page and maintaining any previously loaded global grammars; and if the loaded multimodal web page is not one of the plurality of multimodal web pages of the particular multimodal application, unloading any currently loaded global grammars. 5. The method of claim 1 , further comprising identifying in dependence upon markup in the loaded multimodal web page any document level grammars and loading the document level grammars identified by the markup.

1. A computer-implemented method comprising: parsing a Short Message with a Server; generating a Context Metadata of the Short Message; and, associating explicitly the Context Metadata to the Short Message; and, delivering the Short Message and its Context Metadata.

1. A computer-implemented method comprising: parsing a Short Message with a Server; generating a Context Metadata of the Short Message; and, associating explicitly the Context Metadata to the Short Message; and, delivering the Short Message and its Context Metadata. 14. The method as in claim 1 , wherein the step of parsing the Short Message further comprises using a Language Parser designed for a Short Message Service Slang.

15. A method, implemented by a computing device, comprising: providing software being tested; at runtime of the software, injecting one or more additional constraints into the software, the injecting including adding a cast to a type in the software wherein the cast pertains to an issue; executing the software with the added cast for a concrete input; and actively checking for an input that causes the issue, wherein runtime testing is extended by actively checking for the input that causes the issue for program executions of the software that follow a same program path.

15. A method, implemented by a computing device, comprising: providing software being tested; at runtime of the software, injecting one or more additional constraints into the software, the injecting including adding a cast to a type in the software wherein the cast pertains to an issue; executing the software with the added cast for a concrete input; and actively checking for an input that causes the issue, wherein runtime testing is extended by actively checking for the input that causes the issue for program executions of the software that follow a same program path. 17. The method of claim 15 , wherein the cast is to a type <nonzero>and wherein the issue comprises division by zero.

1. A computer-implemented method for managing a network-based message board for allowing posting users to post messages for viewing, the message board comprising a plurality of messages received from a plurality of posting users, each message being associated with one or more filter values that indicate the content of the message, the method comprising: providing one or more selectable filters, each filter providing one or more selectable filter values; receiving, from a first user, a first set of selections comprising a selection of one or more filters and, for each selected filter, a selection of one or more filter values; retrieving messages of one or more posting users from the message board based on the first set of selections and an aggregate reputation value of the one or more posting users, the aggregate reputation value of a posting user comprising a combination of at least two individual reputation values of the posting user, each individual reputation value indicating the reputation of the posting user for a filter value, wherein each retrieved message comprises a message from a posting user having an aggregate reputation value above a threshold value, wherein the aggregate reputation value of a posting user is based on at least one rating by at least one rating user of at least one message posted by the posting user and a reputation value of the at least rating user; displaying a custom message board for the first user, the custom message board comprising the retrieved messages, displaying the custom message board comprising: first displaying a first group of messages, each message in the first group having associated filter values matching all of the selected filter values; and second displaying a second group of messages, each message in the second group having associated filter values matching some but not all of the at least three selected filter values; receiving a first message from the first user related to the custom message board; and associating the first message with the custom message board by associating the first message with the filter values of the first set of selections.

1. A computer-implemented method for managing a network-based message board for allowing posting users to post messages for viewing, the message board comprising a plurality of messages received from a plurality of posting users, each message being associated with one or more filter values that indicate the content of the message, the method comprising: providing one or more selectable filters, each filter providing one or more selectable filter values; receiving, from a first user, a first set of selections comprising a selection of one or more filters and, for each selected filter, a selection of one or more filter values; retrieving messages of one or more posting users from the message board based on the first set of selections and an aggregate reputation value of the one or more posting users, the aggregate reputation value of a posting user comprising a combination of at least two individual reputation values of the posting user, each individual reputation value indicating the reputation of the posting user for a filter value, wherein each retrieved message comprises a message from a posting user having an aggregate reputation value above a threshold value, wherein the aggregate reputation value of a posting user is based on at least one rating by at least one rating user of at least one message posted by the posting user and a reputation value of the at least rating user; displaying a custom message board for the first user, the custom message board comprising the retrieved messages, displaying the custom message board comprising: first displaying a first group of messages, each message in the first group having associated filter values matching all of the selected filter values; and second displaying a second group of messages, each message in the second group having associated filter values matching some but not all of the at least three selected filter values; receiving a first message from the first user related to the custom message board; and associating the first message with the custom message board by associating the first message with the filter values of the first set of selections. 13. The method of claim 1 , wherein: the at least one message of the posting user is associated with first and second filter values; and the aggregate reputation value of the posting user is determined using a first individual reputation value of the first filter value and a second individual reputation value of the second filter value of the posting user.

1. In a PostScript graphics language interpreter that accepts PostScript commands indicating both device-dependent and device-independent color specifications, wherein the graphics language interpreter converts the device-dependent and device independent color specifications to internal color specifications before rendering, a color conversion method comprising the following steps: converting device-independent color specifications to device-dependent color specifications using a standard PostScript color rendering dictionary; converting device-dependent color specifications, including those converted from the device-independent color specifications, to internal color specifications using a calibrated n-dimensional operation that is not a standard PostScript operation, where n is greater than 1.

1. In a PostScript graphics language interpreter that accepts PostScript commands indicating both device-dependent and device-independent color specifications, wherein the graphics language interpreter converts the device-dependent and device independent color specifications to internal color specifications before rendering, a color conversion method comprising the following steps: converting device-independent color specifications to device-dependent color specifications using a standard PostScript color rendering dictionary; converting device-dependent color specifications, including those converted from the device-independent color specifications, to internal color specifications using a calibrated n-dimensional operation that is not a standard PostScript operation, where n is greater than 1. 4. A color conversion method as recited in claim 1, wherein the step of converting device-dependent color specifications comprises: referencing an n-dimensional lookup table; interpolating between values of the lookup table.

13. A computer program product for harmonizing business processes tasks, the computer program product comprising: a computer readable storage medium; first program instructions to compare descriptors associated with each of a plurality of business process tasks of different and separate processes of a service oriented architecture, wherein the descriptors associated with each of the tasks comprise a task name, a text description of the task, a predicate task that provides an input to the task in the service oriented architecture, and a subsequent task receives an output generated from the task in the service oriented architecture; wherein the first program instructions are further to identify a first task of the plurality of business process tasks that is within a first process of the service oriented architecture, and a second task of the plurality of business process tasks that is within a second process of the service oriented architecture that is different and separate from the first process, as a candidate task pair for consolidation as a function of determining that they have a text term in common in their task names or in their text descriptions; second program instructions to compare the inputs received from the predicate tasks of each of the candidate pair tasks and the outputs generated by each of the candidate pair tasks to their subsequent tasks, and to confirm consolidation of the candidate pair tasks if the compared inputs to the first and the second tasks are similar and the compared outputs of the first and the second task are similar; and third program instructions to consolidate the confirmed candidate pair tasks by merging the confirmed candidate pair tasks into a new merged task or replacing a one of the first and second tasks with a replacement other of the first and second tasks, and to generate an output from the consolidated candidate pair tasks as a common harmonized output for the subsequent tasks of the first and the second tasks; wherein the first, second and third program instructions are stored on the computer readable storage medium.

13. A computer program product for harmonizing business processes tasks, the computer program product comprising: a computer readable storage medium; first program instructions to compare descriptors associated with each of a plurality of business process tasks of different and separate processes of a service oriented architecture, wherein the descriptors associated with each of the tasks comprise a task name, a text description of the task, a predicate task that provides an input to the task in the service oriented architecture, and a subsequent task receives an output generated from the task in the service oriented architecture; wherein the first program instructions are further to identify a first task of the plurality of business process tasks that is within a first process of the service oriented architecture, and a second task of the plurality of business process tasks that is within a second process of the service oriented architecture that is different and separate from the first process, as a candidate task pair for consolidation as a function of determining that they have a text term in common in their task names or in their text descriptions; second program instructions to compare the inputs received from the predicate tasks of each of the candidate pair tasks and the outputs generated by each of the candidate pair tasks to their subsequent tasks, and to confirm consolidation of the candidate pair tasks if the compared inputs to the first and the second tasks are similar and the compared outputs of the first and the second task are similar; and third program instructions to consolidate the confirmed candidate pair tasks by merging the confirmed candidate pair tasks into a new merged task or replacing a one of the first and second tasks with a replacement other of the first and second tasks, and to generate an output from the consolidated candidate pair tasks as a common harmonized output for the subsequent tasks of the first and the second tasks; wherein the first, second and third program instructions are stored on the computer readable storage medium. 14. The computer program product of claim 13 , wherein the third program instructions are further to consolidate the confirmed candidate pair tasks by merging the confirmed candidate pair tasks into a new merged task having a new descriptor and receiving a combined input from each of the predicate tasks that provide the inputs to the respective first and second tasks if the compared inputs from the predicate tasks are the same and the compared outputs generated to the subsequent tasks are the same.

6. The one or more computer storage hardware devices of claim 1 , wherein the index includes an identification of one or more terms included within a received document.

6. The one or more computer storage hardware devices of claim 1 , wherein the index includes an identification of one or more terms included within a received document. 7. The one or more computer storage hardware devices of claim 6 , wherein the index further includes an identification of a position of each of the one or more terms included within the received document.

15. A computer-readable storage device encoded with a computer program, the computer program comprising instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: generating training data for training a predictive model using a machine learning technique to estimate a probability that a given document is plagiarized or is not plagiarized, the training data including, for each of a plurality of training documents, a feature vector that includes (i) data referencing a content of an edit to the training document, (ii) data referencing a type of the edit to the training document, (iii) data referencing a time associated with the edit to the training document, and (iv) a label indicating whether the training document is or is not plagiarized; training the predictive model using the training data; after training the predictive model, identifying a particular document stored in a database; receiving data referencing (i) a content of an edit to the particular document stored in the database, and (ii) a time associated with the edit to the particular document; generating a feature vector based at least on the data referencing (i) the content of the edit to the particular document stored in the database, and (ii) the time associated with the edit to the particular document; and determining a probability that the particular document is plagiarized or is not plagiarized based on classifying the feature vector by the predictive model that is trained using the machine learning technique.

15. A computer-readable storage device encoded with a computer program, the computer program comprising instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: generating training data for training a predictive model using a machine learning technique to estimate a probability that a given document is plagiarized or is not plagiarized, the training data including, for each of a plurality of training documents, a feature vector that includes (i) data referencing a content of an edit to the training document, (ii) data referencing a type of the edit to the training document, (iii) data referencing a time associated with the edit to the training document, and (iv) a label indicating whether the training document is or is not plagiarized; training the predictive model using the training data; after training the predictive model, identifying a particular document stored in a database; receiving data referencing (i) a content of an edit to the particular document stored in the database, and (ii) a time associated with the edit to the particular document; generating a feature vector based at least on the data referencing (i) the content of the edit to the particular document stored in the database, and (ii) the time associated with the edit to the particular document; and determining a probability that the particular document is plagiarized or is not plagiarized based on classifying the feature vector by the predictive model that is trained using the machine learning technique. 20. The device of claim 15 , wherein the operations comprise, for each of the plurality of training documents, pre-processing the content of the edit to insert variable-invariant features.

10. A computer software menu management system consisting of, storing a keyword in a controlled vocabulary and its predetermined code in a database that links each said keyword to a parent keyword at the parent level thereby creating a hierarchical organization having a plurality of levels, selecting a set of keywords from said database that are all linked to the same said parent keyword and are located at an identical level in said hierarchical organization, generating a list menu based on said set of keywords, adding a navigation control to said menu system, adding a search control to said menu system, displaying said list menu, fetching a selection made by an end-user associated with said navigation control, with said search control, and with said set of keywords in said list menu, generating another said list menu representing a parent and a child level in said hierarchical organization depending upon the hype of navigation control selected by said end-user. fetching at least one said keyword selected by said end-user from said list menu selected when said search control is selected by said end-user, generating a database query that includes at least one said keyword selected by said end-user in said list menu when said search control is selected by said end-user.

10. A computer software menu management system consisting of, storing a keyword in a controlled vocabulary and its predetermined code in a database that links each said keyword to a parent keyword at the parent level thereby creating a hierarchical organization having a plurality of levels, selecting a set of keywords from said database that are all linked to the same said parent keyword and are located at an identical level in said hierarchical organization, generating a list menu based on said set of keywords, adding a navigation control to said menu system, adding a search control to said menu system, displaying said list menu, fetching a selection made by an end-user associated with said navigation control, with said search control, and with said set of keywords in said list menu, generating another said list menu representing a parent and a child level in said hierarchical organization depending upon the hype of navigation control selected by said end-user. fetching at least one said keyword selected by said end-user from said list menu selected when said search control is selected by said end-user, generating a database query that includes at least one said keyword selected by said end-user in said list menu when said search control is selected by said end-user. 12. The menu management system of claim 10 wherein said list menu is compatible with at least one computer operating system.

1. An information processing apparatus comprising: a generation unit for generating an electronic document file including document data based on application data and a print instruction document; and a receiving unit for receiving the electronic document file including the document data and the print-instruction document including page layout information, wherein the page layout information is set to a document which includes a plurality of pages, and wherein the layout information includes identification information to identify a sheet number for each page and double-side information to identify on which side of a sheet, a front side or a reverse side, each page is to be printed; a determination unit for determining whether or not a specified printer is capable of double-sided printing; a changing unit for performing a changing process, wherein the changing process changes the print-instruction document by changing a description for the reverse side of the double-side information of the page layout information included in the print-instruction document to a description for the front side of the double-side information and changing a sheet number of the identification information of the page layout information included in the print-instruction document, and wherein the changing unit performs the changing process for the page in a case that the determination unit determines that the specified printer is not capable of double-sided printing; a transmission unit for transmitting printing data based on the print-instruction document changed by the changing unit through a printer driver; a storing unit for storing the electronic document file including the document data and the print-instruction document changed by the changing unit when storage of the print-instruction document is instructed; and a reusing unit for reading the electronic document file including the document data and the print-instruction document stored by the storing unit and executing printing when the printing of the stored print-instruction document is instructed.

1. An information processing apparatus comprising: a generation unit for generating an electronic document file including document data based on application data and a print instruction document; and a receiving unit for receiving the electronic document file including the document data and the print-instruction document including page layout information, wherein the page layout information is set to a document which includes a plurality of pages, and wherein the layout information includes identification information to identify a sheet number for each page and double-side information to identify on which side of a sheet, a front side or a reverse side, each page is to be printed; a determination unit for determining whether or not a specified printer is capable of double-sided printing; a changing unit for performing a changing process, wherein the changing process changes the print-instruction document by changing a description for the reverse side of the double-side information of the page layout information included in the print-instruction document to a description for the front side of the double-side information and changing a sheet number of the identification information of the page layout information included in the print-instruction document, and wherein the changing unit performs the changing process for the page in a case that the determination unit determines that the specified printer is not capable of double-sided printing; a transmission unit for transmitting printing data based on the print-instruction document changed by the changing unit through a printer driver; a storing unit for storing the electronic document file including the document data and the print-instruction document changed by the changing unit when storage of the print-instruction document is instructed; and a reusing unit for reading the electronic document file including the document data and the print-instruction document stored by the storing unit and executing printing when the printing of the stored print-instruction document is instructed. 6. The information processing apparatus according to claim 1 , wherein the specified printer is a default printer in a case that the specified printer is not defined by the print-instruction document.

1. A non-transitory computer-readable medium storing instructions that, when executed by a processor, are configured to cause the processor to perform operations for grading an electronically administered assessment, the operations comprising: displaying a first challenge problem; displaying a digital ink stroke corresponding to an answer to the first challenge problem from a first assessee; receiving, from an assessor via a digital pen, a first feedback tag for association with the digital ink stroke of the first assessee; electronically tagging the digital ink stroke of the first assessee with the first feedback tag made by the assessor via the digital pen; identifying a second digital ink stroke corresponding to an answer to the first challenge problem from a second assessee that matches the electronically tagged digital ink stroke of the first assessee; automatically tagging the matched digital ink stroke of the second assessee with the first feedback tag made by the assessor via the digital pen, wherein each digital ink stroke comprises a notation spatially defined relative to the first challenge problem; and removing the automatically tagged and matched digital ink stroke of the second assessee from a set of answers still requiring assessment by the assessor.

1. A non-transitory computer-readable medium storing instructions that, when executed by a processor, are configured to cause the processor to perform operations for grading an electronically administered assessment, the operations comprising: displaying a first challenge problem; displaying a digital ink stroke corresponding to an answer to the first challenge problem from a first assessee; receiving, from an assessor via a digital pen, a first feedback tag for association with the digital ink stroke of the first assessee; electronically tagging the digital ink stroke of the first assessee with the first feedback tag made by the assessor via the digital pen; identifying a second digital ink stroke corresponding to an answer to the first challenge problem from a second assessee that matches the electronically tagged digital ink stroke of the first assessee; automatically tagging the matched digital ink stroke of the second assessee with the first feedback tag made by the assessor via the digital pen, wherein each digital ink stroke comprises a notation spatially defined relative to the first challenge problem; and removing the automatically tagged and matched digital ink stroke of the second assessee from a set of answers still requiring assessment by the assessor. 2. The non-transitory computer-readable medium of claim 1 , wherein the challenge problem comprises an image over which each of the digital ink strokes is overlaid.

4. The method of claim 2 wherein the step of filling the variable fields includes using the template fixed portions of source code implementing a scenario for checking object life-cycle rules of EJB or CORBA specifications.

4. The method of claim 2 wherein the step of filling the variable fields includes using the template fixed portions of source code implementing a scenario for checking object life-cycle rules of EJB or CORBA specifications. 7. The method of claim 4 wherein the step of filling the variable fields includes using the template fixed portions of source code which implements a scenario for checking persistency of the selected object.

11. The method of claim 1 , wherein performing operations to resolve ambiguities in the reduced set of ambiguities includes: estimating integer ambiguities in the reduced set of ambiguities, including determining a best candidate set and a second best candidate set of integer ambiguity values for each of the integer ambiguities in the reduced set of ambiguities; determining whether the best candidate set of integer ambiguity values for the reduced set of ambiguities meets the discrimination test with respect to the second best candidate set of integer ambiguity values for the reduced set of ambiguities, and if the discrimination test is met, generating a set of result values; if the best candidate set of integer ambiguity values for the reduced set of ambiguities fails to meet the discrimination test, removing from the reduced set of ambiguities each ambiguity for which integer ambiguity values in the best candidate set and second best candidate set of integer ambiguity values for the reduced set of ambiguities fail to meet the predefined criteria to produce a second reduced set of ambiguities; performing operations to resolve the integer ambiguities in the second reduced set of ambiguities; and generating the output in accordance with a result of the operations performed to resolve the integer ambiguities in the second reduced set of ambiguities.

11. The method of claim 1 , wherein performing operations to resolve ambiguities in the reduced set of ambiguities includes: estimating integer ambiguities in the reduced set of ambiguities, including determining a best candidate set and a second best candidate set of integer ambiguity values for each of the integer ambiguities in the reduced set of ambiguities; determining whether the best candidate set of integer ambiguity values for the reduced set of ambiguities meets the discrimination test with respect to the second best candidate set of integer ambiguity values for the reduced set of ambiguities, and if the discrimination test is met, generating a set of result values; if the best candidate set of integer ambiguity values for the reduced set of ambiguities fails to meet the discrimination test, removing from the reduced set of ambiguities each ambiguity for which integer ambiguity values in the best candidate set and second best candidate set of integer ambiguity values for the reduced set of ambiguities fail to meet the predefined criteria to produce a second reduced set of ambiguities; performing operations to resolve the integer ambiguities in the second reduced set of ambiguities; and generating the output in accordance with a result of the operations performed to resolve the integer ambiguities in the second reduced set of ambiguities. 12. The method of claim 11 , wherein: identifying the set of ambiguities comprises identifying respective wide-lane ambiguities corresponding to respective satellites in the identified set of satellites; and the best candidate set and second best candidate set of integer ambiguity values for the reduced set of ambiguities each include first and second integer ambiguity values for respective first and second wide-lane ambiguities.

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 learning the preferred microgenres of content of the user as contained in content items selected by the user, the method comprising: providing access to a content system including a set of content items organized by genre information that characterizes the content items, wherein the genre information is specified by the content system, and wherein the set of content items contains microgenre metadata further characterizing the content items; receiving incremental input entered by the user for incrementally identifying desired content items; in response to the incremental input entered by the user, presenting a subset of content items to the user; receiving actions from the user selecting content items from the subset; analyzing the microgenre metadata within the selected content items to learn the preferred microgenres of the user; analyzing the date, day, and time of the user selection actions and analyzing at least one of the genre information and microgenre metadata of the selected content items to learn a periodicity of user selections of similar content items, wherein similarity is determined by comparing the at least one of the genre information and microgenre metadata of the selected content item with a previously selected content item, and wherein the periodicity indicates the amount of time between user selections of similar content items relative to a reference point; and associating the learned periodicity with the at least one of the genre information and microgenre metadata of the similar content items; in response to receiving subsequent incremental input entered by the user, selecting and ranking a collection of content items, wherein content items containing microgenre metadata matching more learned microgenre preferences of the user relative to other microgenre preferences are ranked more highly than other content items of the collection containing microgenre metadata matching less learned microgenre preferences of the user relative to other microgenre preferences, and wherein the selecting and presenting the collection of content items is further based on promoting the relevance of those content items characterized by genre information or containing microgenre metadata associated with periodicities matching the date, day, and time of the subsequent incremental input; and presenting the ranked collection of content items on a display device in an order reflecting the ranking of the content items.

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 learning the preferred microgenres of content of the user as contained in content items selected by the user, the method comprising: providing access to a content system including a set of content items organized by genre information that characterizes the content items, wherein the genre information is specified by the content system, and wherein the set of content items contains microgenre metadata further characterizing the content items; receiving incremental input entered by the user for incrementally identifying desired content items; in response to the incremental input entered by the user, presenting a subset of content items to the user; receiving actions from the user selecting content items from the subset; analyzing the microgenre metadata within the selected content items to learn the preferred microgenres of the user; analyzing the date, day, and time of the user selection actions and analyzing at least one of the genre information and microgenre metadata of the selected content items to learn a periodicity of user selections of similar content items, wherein similarity is determined by comparing the at least one of the genre information and microgenre metadata of the selected content item with a previously selected content item, and wherein the periodicity indicates the amount of time between user selections of similar content items relative to a reference point; and associating the learned periodicity with the at least one of the genre information and microgenre metadata of the similar content items; in response to receiving subsequent incremental input entered by the user, selecting and ranking a collection of content items, wherein content items containing microgenre metadata matching more learned microgenre preferences of the user relative to other microgenre preferences are ranked more highly than other content items of the collection containing microgenre metadata matching less learned microgenre preferences of the user relative to other microgenre preferences, and wherein the selecting and presenting the collection of content items is further based on promoting the relevance of those content items characterized by genre information or containing microgenre metadata associated with periodicities matching the date, day, and time of the subsequent incremental input; and presenting the ranked collection of content items on a display device in an order reflecting the ranking of the content items. 12. The method of claim 1 , wherein at least one of the incremental input and the subsequent incremental input comprises at least one prefix of a word for describing the desired content items.

1. A method for a user interface system for modifying a document with imaging components using a natural language control system executed via a processor with a memory storing executable instructions having the method, comprising: receiving the document from an image input device; presenting an image modification in real time within an image that is displayed in a first view of a display while the image modification is received as input from a user; and presenting a text-based interface in a second view, the text-based interface presenting text-based categories corresponding to portions of a human readable sentence used to generate the image modification; displaying in a window more than one human readable sentence corresponding respectively to more than one image modification generated; upon receiving a user specified ordering with a corresponding priority of the more than one human readable sentence for the respective one or more image modification generated, sorting the one or more image modification according to a user specified input of the more than one human readable sentence displayed in the window, wherein sentences with a higher user specified priority in the user specified order generate the respective image modifications in the image before other image modifications displayed in descending order of priority in the window, and wherein the order is dynamically changed by the user through a user interface.

1. A method for a user interface system for modifying a document with imaging components using a natural language control system executed via a processor with a memory storing executable instructions having the method, comprising: receiving the document from an image input device; presenting an image modification in real time within an image that is displayed in a first view of a display while the image modification is received as input from a user; and presenting a text-based interface in a second view, the text-based interface presenting text-based categories corresponding to portions of a human readable sentence used to generate the image modification; displaying in a window more than one human readable sentence corresponding respectively to more than one image modification generated; upon receiving a user specified ordering with a corresponding priority of the more than one human readable sentence for the respective one or more image modification generated, sorting the one or more image modification according to a user specified input of the more than one human readable sentence displayed in the window, wherein sentences with a higher user specified priority in the user specified order generate the respective image modifications in the image before other image modifications displayed in descending order of priority in the window, and wherein the order is dynamically changed by the user through a user interface. 2. The method of claim 1 , further comprising: presenting a first text-based category in the text-based interface having various color selections for receiving a color to be modified in the document from the user; presenting a second text-based category in the text-based interface having selections for receiving a magnitude of the image modification or a resultant image modification; presenting a third text-based category in the text-based interface having selections different from the second text-based category for receiving the magnitude or the resultant image modification; receiving a selection respectively from the first, second and third text-based category; and compiling and presenting the human readable sentence in a window of the text-based interface representing the image modification while the modification is displayed in the image.

1. A method of making a data representation of transaction-tax-related information of a transaction, the transaction being represented by a transaction document having transaction-document lines, the transaction-tax-related information having one or more taxation levels, the method comprising: arranging, by a computer, data items representing the transaction-tax-related information according to a data schema for representing transaction-tax related information for different jurisdictions, including jurisdictions with different kinds and numbers of taxation levels; wherein the data schema provides a taxation-line entity for each of the transaction-document lines of the transaction document, wherein the transaction-document lines correspond to respective sub-transactions of the transaction; the data schema provides a taxation-line-item entity, related to the taxation-line entity, for each taxation level of a corresponding transaction-document line, wherein plural taxation-line-item entities are provided for the corresponding transaction-document line associated with plural taxation levels; and wherein an attribute of each taxation-line-item entity is used to indicate the taxation level represented by the taxation-line-item entity.

1. A method of making a data representation of transaction-tax-related information of a transaction, the transaction being represented by a transaction document having transaction-document lines, the transaction-tax-related information having one or more taxation levels, the method comprising: arranging, by a computer, data items representing the transaction-tax-related information according to a data schema for representing transaction-tax related information for different jurisdictions, including jurisdictions with different kinds and numbers of taxation levels; wherein the data schema provides a taxation-line entity for each of the transaction-document lines of the transaction document, wherein the transaction-document lines correspond to respective sub-transactions of the transaction; the data schema provides a taxation-line-item entity, related to the taxation-line entity, for each taxation level of a corresponding transaction-document line, wherein plural taxation-line-item entities are provided for the corresponding transaction-document line associated with plural taxation levels; and wherein an attribute of each taxation-line-item entity is used to indicate the taxation level represented by the taxation-line-item entity. 7. The method of claim 1 , further comprising storing the data representation in a relational database, wherein the taxation-line entities and the taxation-line-item entities are tuples of taxation-line relations and taxation-line-item relations of the relational database.

1. A system for selectively delivering an article, comprising: a communications interface configured to: receive a user preference; and receive a document; a processor configured to: identify a plurality of entity pairs each comprising a concept included in a concept taxonomy and a textual representation relating to the concept included in the document, each concept having a corresponding category vector including a plurality of adjacent nodes of the concept in a taxonomy; compute a document vector (dv) for the document as a sum of the category vectors for the plurality of entity pairs; select a subset of concepts from the plurality of entity pairs according to a comparison of the document vector and the category vectors of the concepts of the plurality of entity pairs by: calculating a similarity score ds for each concept according to ds=dv·cv, where dv is the document vector and cv is a concept vector; selecting the subset of concepts as concepts having similarity scores ds with respect to the document vector hi her than a threshold; categorize the document based at least in part on the selected subset of concepts; and determine that the selected subset of concepts corresponds to the user preference; in response to determining that the selected subset of concepts corresponds to the user preference, notify a user associated with the user preference of the document; and a memory coupled to the processor and configured to provide the processor with instructions.

1. A system for selectively delivering an article, comprising: a communications interface configured to: receive a user preference; and receive a document; a processor configured to: identify a plurality of entity pairs each comprising a concept included in a concept taxonomy and a textual representation relating to the concept included in the document, each concept having a corresponding category vector including a plurality of adjacent nodes of the concept in a taxonomy; compute a document vector (dv) for the document as a sum of the category vectors for the plurality of entity pairs; select a subset of concepts from the plurality of entity pairs according to a comparison of the document vector and the category vectors of the concepts of the plurality of entity pairs by: calculating a similarity score ds for each concept according to ds=dv·cv, where dv is the document vector and cv is a concept vector; selecting the subset of concepts as concepts having similarity scores ds with respect to the document vector hi her than a threshold; categorize the document based at least in part on the selected subset of concepts; and determine that the selected subset of concepts corresponds to the user preference; in response to determining that the selected subset of concepts corresponds to the user preference, notify a user associated with the user preference of the document; and a memory coupled to the processor and configured to provide the processor with instructions. 3. The system of claim 1 wherein the user preference includes a preference for a leaf node concept in the concept taxonomy.

5. The method of claim 1 further comprising forming speaker pool means for each of a plurality of speakers in a speaker pool, the speaker pool means for a speaker being formed by adapting the background model based on speech from the speaker.

5. The method of claim 1 further comprising forming speaker pool means for each of a plurality of speakers in a speaker pool, the speaker pool means for a speaker being formed by adapting the background model based on speech from the speaker. 6. The method of claim 5 wherein each function further comprises a corresponding threshold value wherein each threshold value is based on speaker pool means for a subset of the speakers in the speaker pool.

24. A system for identifying related documents, the system comprising: means, including a processor and memory, for searching at least one database for a set of one or more related second documents based on content of an input document; a support vector machine for identifying one or more of the related second documents as more probably related to the input document than one or more of the other related second documents; and wherein the support vector machine comprises: support-vector processor means, including a processor and memory, for defining a multi-dimensional feature vector for each related second document, with the vector having a set of features including a similarity feature indicating similarity of at least a portion of the related second document to a portion of the input document wherein each of the feature vectors is based on a title similarity score for one or more portions of a said related second document and the input document.

24. A system for identifying related documents, the system comprising: means, including a processor and memory, for searching at least one database for a set of one or more related second documents based on content of an input document; a support vector machine for identifying one or more of the related second documents as more probably related to the input document than one or more of the other related second documents; and wherein the support vector machine comprises: support-vector processor means, including a processor and memory, for defining a multi-dimensional feature vector for each related second document, with the vector having a set of features including a similarity feature indicating similarity of at least a portion of the related second document to a portion of the input document wherein each of the feature vectors is based on a title similarity score for one or more portions of a said related second document and the input document. 25. The system of claim 24 , wherein the document is a judicial opinion.

23. The method of claim 22 further comprising: the computer converting an encoding of the at least one document from a first encoding to a second encoding, wherein the dictionary is stored in the second encoding.

23. The method of claim 22 further comprising: the computer converting an encoding of the at least one document from a first encoding to a second encoding, wherein the dictionary is stored in the second encoding. 24. The method of claim 23 , wherein the dictionary is also stored in another encoding.

15. A non-transitory computer-readable medium having instructions stored thereon which, when executed by one or more processors of a server, causes the server to perform operations comprising: outputting, to a developer of a web page in a source language, an offer to opt-in to a translation feature that enables one or more other users to translate the web page to a different target language; receiving, from the developer, a first request to opt-in to the translation feature; and in response to receiving the first request to opt-in to the translation feature: generating and storing a copy of the web page; obtaining, from the one or more other users, translations of at least a portion of the web page from the source language to the target language; modifying the web page copy based on the obtained translations to obtain a translated web page, the translated web page being a translated version of the web page; detecting a second request for the web page from a computing device associated with the target language; and in response to detecting the second request, outputting, to the computing device, the translated web page with additional content relevant to the computing device or a user associated with the computing device.

15. A non-transitory computer-readable medium having instructions stored thereon which, when executed by one or more processors of a server, causes the server to perform operations comprising: outputting, to a developer of a web page in a source language, an offer to opt-in to a translation feature that enables one or more other users to translate the web page to a different target language; receiving, from the developer, a first request to opt-in to the translation feature; and in response to receiving the first request to opt-in to the translation feature: generating and storing a copy of the web page; obtaining, from the one or more other users, translations of at least a portion of the web page from the source language to the target language; modifying the web page copy based on the obtained translations to obtain a translated web page, the translated web page being a translated version of the web page; detecting a second request for the web page from a computing device associated with the target language; and in response to detecting the second request, outputting, to the computing device, the translated web page with additional content relevant to the computing device or a user associated with the computing device. 20. The computer-readable medium of claim 15 , wherein the operations further comprise in response to receiving the first request to opt-in to the translation feature, modifying a document object model (DOM) of the web page copy to include JavaScript for providing the additional content.

1. A method, comprising: using a computer to perform: collecting information about a user manipulation of a stylus in relation to a tablet device associated with the computer; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, such that: the stylus gesture is one of a plurality of stylus gestures that are recognized by the computer to perform at least one of a plurality of actions in a graphics application that comprises a natural media painting application, at least some of the stylus gestures are mapped to user manipulation of the stylus at a distance from the tablet device, at least some of the stylus gestures involve contact of the stylus with the tablet device, and the stylus gestures include a brush switching gesture in which a proximity of the stylus to the tablet changes from a first position relative to the tablet to a second position that is further away from the tablet and with at least a rate of change that corresponds to the brush switching gesture, the first position being within a first pre-defined distance threshold relative the tablet and the second position being beyond a second pre-defined distance threshold, and switching between paintbrushes of a brush tool being performed responsive to recognition of the brush switching gesture; determining which of the plurality of actions to perform based on the recognized stylus gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions.

1. A method, comprising: using a computer to perform: collecting information about a user manipulation of a stylus in relation to a tablet device associated with the computer; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, such that: the stylus gesture is one of a plurality of stylus gestures that are recognized by the computer to perform at least one of a plurality of actions in a graphics application that comprises a natural media painting application, at least some of the stylus gestures are mapped to user manipulation of the stylus at a distance from the tablet device, at least some of the stylus gestures involve contact of the stylus with the tablet device, and the stylus gestures include a brush switching gesture in which a proximity of the stylus to the tablet changes from a first position relative to the tablet to a second position that is further away from the tablet and with at least a rate of change that corresponds to the brush switching gesture, the first position being within a first pre-defined distance threshold relative the tablet and the second position being beyond a second pre-defined distance threshold, and switching between paintbrushes of a brush tool being performed responsive to recognition of the brush switching gesture; determining which of the plurality of actions to perform based on the recognized stylus gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions. 8. The method of claim 1 , wherein the plurality of stylus gestures includes shaking the stylus towards the tablet, shaking the stylus away from the tablet, and twisting the stylus about the major axis of the stylus; and wherein the action that is performed in response to recognition of shaking the stylus towards the tablet includes splattering paint; wherein the action that is performed in response to recognition of shaking the stylus away from the tablet includes cleaning the brush tool; and wherein the action that is performed in response to recognition of twisting the stylus includes homogenizing the colors of paint on the brush tool.

1. A computer-implemented method comprising: receiving, by a term pre-processor module of a server-based automated speech recognition system that includes (a) the term pre-processor module, (b) a user similarity determiner module, (c) a vocabulary generator module, (d) a language model biaser module, and (e) an automated speech recognizer, and from a device associated with a target user, (i) data including a set of terms associated with the target user that includes terms from one or more queries previously submitted by the target user, and, (ii) from each of multiple other users, data including a set of terms associated with the other user; selecting, by the user similarity determiner module of the server-based automated speech recognition system, a particular other user based at least on comparing the set of terms associated with the target user to the sets of terms associated with the other users; selecting, by the vocabulary generator module of the server-based automated speech recognition system, one or more terms from the set of terms that is associated with the particular other user; obtaining, by the language model biaser module of the server-based automated speech recognition system and based on the selected terms that are associated with the particular other user, a biased language model; using, by the automated speech recognizer of the server-based automated speech recognition system, the biased language model generate a speech recognition output; and providing, by the server-based automated speech recognition system, the speech recognition output to the device associated with the target user.

1. A computer-implemented method comprising: receiving, by a term pre-processor module of a server-based automated speech recognition system that includes (a) the term pre-processor module, (b) a user similarity determiner module, (c) a vocabulary generator module, (d) a language model biaser module, and (e) an automated speech recognizer, and from a device associated with a target user, (i) data including a set of terms associated with the target user that includes terms from one or more queries previously submitted by the target user, and, (ii) from each of multiple other users, data including a set of terms associated with the other user; selecting, by the user similarity determiner module of the server-based automated speech recognition system, a particular other user based at least on comparing the set of terms associated with the target user to the sets of terms associated with the other users; selecting, by the vocabulary generator module of the server-based automated speech recognition system, one or more terms from the set of terms that is associated with the particular other user; obtaining, by the language model biaser module of the server-based automated speech recognition system and based on the selected terms that are associated with the particular other user, a biased language model; using, by the automated speech recognizer of the server-based automated speech recognition system, the biased language model generate a speech recognition output; and providing, by the server-based automated speech recognition system, the speech recognition output to the device associated with the target user. 5. The method of claim 1 , wherein, for each user, the set of terms associated with the user includes terms that are indicated as terms that have been accepted by the user.

11. The searching device according to claim 9 , further comprising an extraction number counting unit counting the number of extraction times facility information is extracted by said extraction unit, wherein said weight storage unit stores, in association with facility information, a weight based on the number counted by said count unit and the extraction number counted by said extraction number counting unit.

11. The searching device according to claim 9 , further comprising an extraction number counting unit counting the number of extraction times facility information is extracted by said extraction unit, wherein said weight storage unit stores, in association with facility information, a weight based on the number counted by said count unit and the extraction number counted by said extraction number counting unit. 12. The searching device according to claim 11 , further comprising: an elapsed time output unit outputting an elapsed time based on a search date or an acquisition date corresponding to facility information stored in said storage unit and a date output from said clock unit; and a delete unit deleting said facility information stored in said storage unit when the elapsed time output by the elapsed time output unit is a given time or more.

5. The method of claim 1 wherein clustering the device into a value level cluster based on the attribute value for each device attribute further comprises: calculating for each value level cluster, by the device clustering module, a similarity index between the device and all devices in the value level cluster; and assigning, by the device clustering module, the device to the value level cluster with the highest average similarity index.

5. The method of claim 1 wherein clustering the device into a value level cluster based on the attribute value for each device attribute further comprises: calculating for each value level cluster, by the device clustering module, a similarity index between the device and all devices in the value level cluster; and assigning, by the device clustering module, the device to the value level cluster with the highest average similarity index. 6. The method of claim 5 wherein calculating for each value level cluster a similarity index between the device and all devices in the value level cluster further comprises: for each value level cluster: calculating, by the device clustering module, the similarity index between the device and each of the devices in the value level cluster; summing, by the device clustering module, the similarity index between the device and each of the devices in the value level cluster, thereby producing a similarity index sum; determining, by the device clustering module, the number of devices in the value level cluster; and dividing, by the device clustering module, the similarity index sum by the number of devices in the value level cluster.

3. The navigation device according to claim 1 , wherein said navigation device further includes a gesture recognizer that recognizes a gesture, and said route guidance expression interpreter interprets the route guidance expression extracted by said route guidance expression extractor on a basis of a result of the recognition by said gesture recognizer to determine the concrete route guidance expression.

3. The navigation device according to claim 1 , wherein said navigation device further includes a gesture recognizer that recognizes a gesture, and said route guidance expression interpreter interprets the route guidance expression extracted by said route guidance expression extractor on a basis of a result of the recognition by said gesture recognizer to determine the concrete route guidance expression. 4. The navigation device according to claim 3 , wherein said navigation device further includes a contradiction determinator that determines whether or not there is a contradiction between the route guidance expression extracted by said route guidance expression extractor and the recognition result obtained by said gesture recognizer, and, when said contradiction determinator determines that there is a contradiction between them, said route guidance expression interpreter selects either one of the route guidance expression extracted by said route guidance expression extractor and the recognition result obtained by said gesture recognizer according to a predetermined rule to determine said concrete route guidance expression.

1. A call center device operating in conjunction with a telephonic or online chat communication station, the call center device comprising: a dialog manager configured to determine a recommended agent dialog act based on past dialog between a call center agent and a second party which is received from the telephonic or online chat communication station; and an utterance generation component configured to generate at least one recommended agent utterance for implementing the recommended dialog act by operations including: ranking a set of word lattices each represented as a weighted finite state automaton (WFSA) by conditional probabilities p(τ|DA type) where τ is a word lattice and DA type is a dialog act type of the recommended dialog act, choosing at least one word lattice from the ranking, and instantiating the chosen at least one word lattice to generate the at least one recommended agent utterance; wherein the dialog manager and the utterance generation component comprise at least one computer programmed to determine the recommended dialog act and to generate the at least one recommended agent utterance.

1. A call center device operating in conjunction with a telephonic or online chat communication station, the call center device comprising: a dialog manager configured to determine a recommended agent dialog act based on past dialog between a call center agent and a second party which is received from the telephonic or online chat communication station; and an utterance generation component configured to generate at least one recommended agent utterance for implementing the recommended dialog act by operations including: ranking a set of word lattices each represented as a weighted finite state automaton (WFSA) by conditional probabilities p(τ|DA type) where τ is a word lattice and DA type is a dialog act type of the recommended dialog act, choosing at least one word lattice from the ranking, and instantiating the chosen at least one word lattice to generate the at least one recommended agent utterance; wherein the dialog manager and the utterance generation component comprise at least one computer programmed to determine the recommended dialog act and to generate the at least one recommended agent utterance. 6. The call center device of claim 1 further comprising: a training device comprising at least one computer configured to construct the set of word lattices from training dialogs between call center agents and second parties and to assign to the word lattices τ the conditional probabilities p(τ|DA type) over dialog act types DA type.

12. The method of claim 1 , further comprising applying active learning to identify one of problematic speech units and problematic phrases within the in-domain inventory of synthesis speech units.

12. The method of claim 1 , further comprising applying active learning to identify one of problematic speech units and problematic phrases within the in-domain inventory of synthesis speech units. 17. The method of claim 12 , further comprising: determining a minimal in-domain inventory for recording to meet a selected custom voice synthesis quality; based on the minimal in-domain inventory, recording one of words and phrases according to the one of problematic speech units and problematic phrases; and integrating the one of words and phrases into the in-domain task-independent inventory of synthesis speech units.

1. A system for determining recommendation data, comprising: one or more processors configured to: extract a first set of keywords from a set of user action logs that occurred prior to a predetermined time point; extract a second set of keywords from a set of user action logs that occurred subsequent to the predetermined time point; merge at least a portion of the first set of keywords and at least a portion of the second set of keywords to obtain a third set of keywords; match at least one keyword in the third set of keywords with a database of data that can potentially be recommended to a user; and in the event that a piece of data in the database is determined to match at least one keyword from the third set of keywords, determine that the piece of data is to be recommended to the user; and one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions.

1. A system for determining recommendation data, comprising: one or more processors configured to: extract a first set of keywords from a set of user action logs that occurred prior to a predetermined time point; extract a second set of keywords from a set of user action logs that occurred subsequent to the predetermined time point; merge at least a portion of the first set of keywords and at least a portion of the second set of keywords to obtain a third set of keywords; match at least one keyword in the third set of keywords with a database of data that can potentially be recommended to a user; and in the event that a piece of data in the database is determined to match at least one keyword from the third set of keywords, determine that the piece of data is to be recommended to the user; and one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions. 9. The system of claim 1 , wherein to merge at least a portion of the first set of keywords and at least a portion of the second set of keywords includes: identifying a duplicate keyword that is found in both the first set of keywords and the second set of keywords; and determining a combined weight value for the identified duplicate keyword based at least in part on a weight value of the duplicate keyword determined for the first set of keywords and a weight value of the duplicate keyword determined for the second set of keywords.

1. A computer-implemented method of providing search results, comprising: under the control of one or more computer systems configured with executable instructions, performing a first search in response to a search request; generating for display a first list of results responsive to the search request; analyzing searchable content of each of the results in the first list of results to identify terms in the searchable content that are useful in grouping sets of the first list of results; providing the identified terms in a list of selectable terms to be displayed with the first list of results, the terms being selectable independently of multi-character or single-character textual input; receiving a selection of a user-selected term from the list of selectable terms, the list including selectable objects placed on a user interface adjacent to the terms on the list, the user-selected term being selected by selecting a selectable object adjacent to the term, said selecting being done independently of multi-character or single-character textual input, the selection causing results having content related to the user-selected term to be excluded from a second list of results; and in response to receiving the selection of the user-selected term, performing a second search based at least upon the search request and the user-selected term and generating for display the second list of results that excludes results having content related to the user-selected term, wherein the second list of results is further able to include results not included in the first list of results.

1. A computer-implemented method of providing search results, comprising: under the control of one or more computer systems configured with executable instructions, performing a first search in response to a search request; generating for display a first list of results responsive to the search request; analyzing searchable content of each of the results in the first list of results to identify terms in the searchable content that are useful in grouping sets of the first list of results; providing the identified terms in a list of selectable terms to be displayed with the first list of results, the terms being selectable independently of multi-character or single-character textual input; receiving a selection of a user-selected term from the list of selectable terms, the list including selectable objects placed on a user interface adjacent to the terms on the list, the user-selected term being selected by selecting a selectable object adjacent to the term, said selecting being done independently of multi-character or single-character textual input, the selection causing results having content related to the user-selected term to be excluded from a second list of results; and in response to receiving the selection of the user-selected term, performing a second search based at least upon the search request and the user-selected term and generating for display the second list of results that excludes results having content related to the user-selected term, wherein the second list of results is further able to include results not included in the first list of results. 6. The method of claim 1 , wherein providing the list of selectable terms includes using linking structures within second list of results to analyze content or metadata referenced by the linking structures.

2. The method of claim 1 wherein said grading method is selected from Order Equivalence, Formal Equivalence and Content Equivalence grading methods.

2. The method of claim 1 wherein said grading method is selected from Order Equivalence, Formal Equivalence and Content Equivalence grading methods. 8. The method of claim 2 wherein said comparing comprises determining the similarity between nodes of the syntax trees.

12. A computer readable storage medium encoding computer program code to configure an application on a system, the computer program code comprising functionality to: receive a request to configure the application from a client associated with the application, wherein the system is external to the client, and wherein the request comprises an application context describing a state of the application at runtime; obtain a rule comprising a conditional expression for configuring the application at runtime; parse the rule to extract a symbol and an operator; convert the conditional expression into a tree comprising the symbol and the operator; replace the symbol with a value from the application context using a domain map to find a context data source publishing the value; calculate a correct configuration for the application based on the application context by evaluating the tree after replacing the symbol; obtain an application object associated with a plurality of options for configuring the application; select an option of the plurality of options based on the correct configuration for the application; and send, from the system and in response to the request, an instance of the application object encapsulating the option to the client wherein the application object is used to set a configuration of the application to the correct configuration.

12. A computer readable storage medium encoding computer program code to configure an application on a system, the computer program code comprising functionality to: receive a request to configure the application from a client associated with the application, wherein the system is external to the client, and wherein the request comprises an application context describing a state of the application at runtime; obtain a rule comprising a conditional expression for configuring the application at runtime; parse the rule to extract a symbol and an operator; convert the conditional expression into a tree comprising the symbol and the operator; replace the symbol with a value from the application context using a domain map to find a context data source publishing the value; calculate a correct configuration for the application based on the application context by evaluating the tree after replacing the symbol; obtain an application object associated with a plurality of options for configuring the application; select an option of the plurality of options based on the correct configuration for the application; and send, from the system and in response to the request, an instance of the application object encapsulating the option to the client wherein the application object is used to set a configuration of the application to the correct configuration. 15. The computer readable storage medium of claim 12 , wherein the application context comprises access rights of a user of the application.

7. The method according to claim 1 further comprising: determining whether a user wants multiple copies of said document; and calculating a charge for said multiple copies of said document.

7. The method according to claim 1 further comprising: determining whether a user wants multiple copies of said document; and calculating a charge for said multiple copies of said document. 8. The method according to claim 7 wherein completing the requested standard operation further comprises: providing a certificate allowing authorized reproduction of a number of copies.

1. A method in a data processing system, comprising the steps of: receiving a first markup document and a second markup document, both the first markup document and the second markup document including numerical values and tags reflecting characteristics of the numerical values, wherein the characteristics indicate that the numerical values of the first markup document differ in format from the numerical values of the second markup document; automatically transforming the numerical values of at least one of the first markup document and the second markup document, so that the numerical values of the first markup document and the second markup document have a common format; combining the first markup document and the second markup document into a single data set; and displaying the single data set.

1. A method in a data processing system, comprising the steps of: receiving a first markup document and a second markup document, both the first markup document and the second markup document including numerical values and tags reflecting characteristics of the numerical values, wherein the characteristics indicate that the numerical values of the first markup document differ in format from the numerical values of the second markup document; automatically transforming the numerical values of at least one of the first markup document and the second markup document, so that the numerical values of the first markup document and the second markup document have a common format; combining the first markup document and the second markup document into a single data set; and displaying the single data set. 7. The method of claim 1 , wherein the characteristics include a modifier of the numerical values, and wherein the method further includes: manipulating the display of the single data set using one of the tags, the tag reflecting the modifier of the numerical values.

2. The method of claim 1 wherein the seller engine is enabled simultaneously to process in real-time, a number of multiple interacting variables including revenue, profit, market share, inventory, supplier-break, competitor events, and market demand changes, while automatically optimizing the iterative bidding in real-time on demand—all without the need for manually tracking of said variables or any other manual intervention from the seller, even in the presence of dynamically changing market conditions.

2. The method of claim 1 wherein the seller engine is enabled simultaneously to process in real-time, a number of multiple interacting variables including revenue, profit, market share, inventory, supplier-break, competitor events, and market demand changes, while automatically optimizing the iterative bidding in real-time on demand—all without the need for manually tracking of said variables or any other manual intervention from the seller, even in the presence of dynamically changing market conditions. 3. The method of claim 2 wherein multiple price optimizers within the seller engine are employed and configured based on the sellers said objectives as well as market conditions, including demand, competitive behavior, inventory, and supplier-breaks, with the price optimizers computing when to update the price and by how much, based upon real-time data from the marketplace and upon the seller-configured parameters, and without requiring any further manual intervention from the seller.

33. The system of claim 32 , wherein each second token identifier comprises an M bit integer value.

33. The system of claim 32 , wherein each second token identifier comprises an M bit integer value. 34. The system of claim 33 , wherein each first token identifier comprises an N bit integer value, N and M are positive integers and M is greater than N.

1. A method for transforming data comprising: receiving, by a computing device, input data with categorical labels, the input data comprising vectors and each categorical label denoting a subset of the vectors; forming, by the computing device, higher-order links for each subset of the vectors; calculating, by the computing device, a higher-order transform for each attribute in each subset by calculating a higher-order prior for each attribute in each subset, wherein each higher-order prior represents a probability corresponding to the associated attribute that is based on one or more patterns of occurrence of the attribute, wherein calculating a higher-order prior comprises estimating the higher-order prior by: P ^ ⁡ ( x i = 1 | X ) =  φ ⁡ ( i , X )   Φ ⁡ ( X )  , and ⁢ ⁢ P ^ ⁡ ( x i = 0 | X ) = 1 - P ^ ⁡ ( x i = 1 | X ) where Φ(X) denotes a set of higher-order links of a specified order in a dataset X, φ(i,X) ⊂ Φ(X) denotes a subset of higher-order links that contain attribute i in dataset X, set φ(i,X) defines an event that a randomly chosen higher-order link contains attribute i, sets Φ(X) and φ(i,X) allow for characterization of each attribute i by a probability mass function {circumflex over (P)}(x i |X) defined over two events: presence of attribute i in a randomly chosen higher-order link, and an absence of that attribute from a randomly chosen higher-order link; and transmitting, by the computing device, transformed data to a learner to build a model.

1. A method for transforming data comprising: receiving, by a computing device, input data with categorical labels, the input data comprising vectors and each categorical label denoting a subset of the vectors; forming, by the computing device, higher-order links for each subset of the vectors; calculating, by the computing device, a higher-order transform for each attribute in each subset by calculating a higher-order prior for each attribute in each subset, wherein each higher-order prior represents a probability corresponding to the associated attribute that is based on one or more patterns of occurrence of the attribute, wherein calculating a higher-order prior comprises estimating the higher-order prior by: P ^ ⁡ ( x i = 1 | X ) =  φ ⁡ ( i , X )   Φ ⁡ ( X )  , and ⁢ ⁢ P ^ ⁡ ( x i = 0 | X ) = 1 - P ^ ⁡ ( x i = 1 | X ) where Φ(X) denotes a set of higher-order links of a specified order in a dataset X, φ(i,X) ⊂ Φ(X) denotes a subset of higher-order links that contain attribute i in dataset X, set φ(i,X) defines an event that a randomly chosen higher-order link contains attribute i, sets Φ(X) and φ(i,X) allow for characterization of each attribute i by a probability mass function {circumflex over (P)}(x i |X) defined over two events: presence of attribute i in a randomly chosen higher-order link, and an absence of that attribute from a randomly chosen higher-order link; and transmitting, by the computing device, transformed data to a learner to build a model. 3. The method of claim 1 wherein the transmitting transformed data to a learner further comprises transmitting transformed data to a discriminative learner.

1. A web search system comprising: a memory; a processing unit coupled to the memory, the processing unit configured to execute computer-implemented components comprising: a search engine that receives search queries and identifies web pages relevant to the search queries; an inference component that infers web page information relevant to a current search query by generating one or more questions, initiating a communication session to communicate the one or more questions to a user, and receiving one or more user supplied answers from the user to the one or more questions via the communication session, the inference component further modifies a heuristic rule pertaining to a search domain classified by a topic hierarchy or a topic cluster based on knowledge learned from the inferred web page information associated with the one or more user supplied answers to generate a modified heuristic rule; and a query modification component that alters the current search query based at least on the inferred webpage information, the modified heuristic rule, and a navigated position in the topic hierarchy or the topic cluster.

1. A web search system comprising: a memory; a processing unit coupled to the memory, the processing unit configured to execute computer-implemented components comprising: a search engine that receives search queries and identifies web pages relevant to the search queries; an inference component that infers web page information relevant to a current search query by generating one or more questions, initiating a communication session to communicate the one or more questions to a user, and receiving one or more user supplied answers from the user to the one or more questions via the communication session, the inference component further modifies a heuristic rule pertaining to a search domain classified by a topic hierarchy or a topic cluster based on knowledge learned from the inferred web page information associated with the one or more user supplied answers to generate a modified heuristic rule; and a query modification component that alters the current search query based at least on the inferred webpage information, the modified heuristic rule, and a navigated position in the topic hierarchy or the topic cluster. 4. The system of claim 1 , further comprising at least one component that adds or deletes heuristics based at least on interaction with the search engine.

13. The client of claim 1 , wherein the client is a desktop computer.

13. The client of claim 1 , wherein the client is a desktop computer. 23. The mobile phone of claim 13 , wherein the processing electronics are configured to receive the auxiliary information from a second mobile phone.

8. A method comprising: obtaining, by a network analysis system, sets of configuration data of a plurality of devices in a network; each set of configuration information being associated with a hierarchical level of connectivity information; consolidating, by the network analysis system, the sets of configuration data associated with a first hierarchical level to create a connectivity graph in a computer-readable memory element, consolidating, by the network analysis system, the sets of configuration data associated with a second hierarchical level to identify connections at the second hierarchical level, for each identified connection at the second hierarchical level: determining whether the identified connection is consistent with the first-level connectivity graph, and if consistent, modifying the connectivity graph in the computer-readable memory to include the identified connection, wherein the first hierarchical level corresponds to physical-level links, and the second hierarchical level corresponds to IP-level links.

8. A method comprising: obtaining, by a network analysis system, sets of configuration data of a plurality of devices in a network; each set of configuration information being associated with a hierarchical level of connectivity information; consolidating, by the network analysis system, the sets of configuration data associated with a first hierarchical level to create a connectivity graph in a computer-readable memory element, consolidating, by the network analysis system, the sets of configuration data associated with a second hierarchical level to identify connections at the second hierarchical level, for each identified connection at the second hierarchical level: determining whether the identified connection is consistent with the first-level connectivity graph, and if consistent, modifying the connectivity graph in the computer-readable memory to include the identified connection, wherein the first hierarchical level corresponds to physical-level links, and the second hierarchical level corresponds to IP-level links. 11. The method of claim 8 , including receiving one or more user-defined golden rules, and resolving any conflicts so as to be consistent with the golden rules.

2. A user-interactive method of operating a computer for generating a report, the computer having memory means for storing data, input means for receiving inputs into the computer, and output means for presenting outputs from the computer, said method comprising the steps of: storing data in the computer memory means representative of sets of user inputs representing information needed for generating said report, and data representative of computer actions respectively corresponding to said inputs, said actions including at least one of retrieving report material, presenting a set of user inputs, and implementing computer commands; presenting by way of the computer output means one of said sets of user inputs for selection by user; entering by way of the computer input means a user-selected input; responding in the computer to said user-selected input by performing said actions corresponding thereto: repeating said entering and responding steps in accordance with said corresponding actions until said inputs needed for generating said report have been entered; and compiling in the computer said report material corresponding to said user-selected inputs for generating said report thereby, said method further including the step of providing said output means as a voice synthesizer.

2. A user-interactive method of operating a computer for generating a report, the computer having memory means for storing data, input means for receiving inputs into the computer, and output means for presenting outputs from the computer, said method comprising the steps of: storing data in the computer memory means representative of sets of user inputs representing information needed for generating said report, and data representative of computer actions respectively corresponding to said inputs, said actions including at least one of retrieving report material, presenting a set of user inputs, and implementing computer commands; presenting by way of the computer output means one of said sets of user inputs for selection by user; entering by way of the computer input means a user-selected input; responding in the computer to said user-selected input by performing said actions corresponding thereto: repeating said entering and responding steps in accordance with said corresponding actions until said inputs needed for generating said report have been entered; and compiling in the computer said report material corresponding to said user-selected inputs for generating said report thereby, said method further including the step of providing said output means as a voice synthesizer. 3. The method as set forth in claim 2, further including the step of providing said voice synthesizer with a remote connection between the user and the computer via an RF communication means.

1. A system for analyzing a mishap that has occurred, the system comprising: a reconfigurable ontology associated with a selected mishap, including a list of at least first and second ontology classes related to the selected mishap, at least one definition or property for each of the at least two ontology classes, a value range associated with each of the at least two ontology classes, and at least one relationship or link between the at least two ontology classes, wherein at least one of the at least first and second ontology classes includes information on at least one of the following: a collection of one or more persons assembled to investigate the mishap; a project with which the mishap is associated; a process or procedure associated with the mishap; at least one person involved in or responsible one or more events leading directly to the mishap; at least one location or site associated with the mishap; a characterization of the mishap; a record associated with the mishap; a document associated with the mishap; physical evidence associated with the mishap; a value of a parameter that is part of a description associated with the mishap; a characterization or classification of a sub-system associated with the mishap; an interview of at least one person associated with the mishap; a description of at least one operation associated with the mishap; at least one inspection associated with the mishap; at least one design record of at least one component associated with the mishap; an analysis of at least one aspect of the mishap; and at least one result of an investigation of the mishap; a semantic network that receives, indexes, stores and integrates, for retrieval, the at least two ontology classes, the definition and the value ranges of the at least two ontology classes and the at least one link between the at least two ontology classes; a network browser interface, having a display screen, that implements a procedure for retrieving and viewing each of the at least two ontology classes in the semantic network, wherein the browser interface (i) displays at least one screen having at least a first group and a second group of possible conclusions concerning a contributing factor to the mishap, where no possible conclusion in the first group also belongs to the second group and (ii) displays at least one conclusion in the first group or in the second group that is characterized as at least one of the following: not a credible conclusion; an unlikely conclusion; a credible conclusion; conclusion needs analysis; conclusion needs supporting data; conclusion proposed to be closed; and an un-reviewed conclusion; and a rule-based inference engine, including a collection of at least two rules, associated with one or more of the at least two ontology classes and applied to support the at least one conclusion displayed in the browser interface.

1. A system for analyzing a mishap that has occurred, the system comprising: a reconfigurable ontology associated with a selected mishap, including a list of at least first and second ontology classes related to the selected mishap, at least one definition or property for each of the at least two ontology classes, a value range associated with each of the at least two ontology classes, and at least one relationship or link between the at least two ontology classes, wherein at least one of the at least first and second ontology classes includes information on at least one of the following: a collection of one or more persons assembled to investigate the mishap; a project with which the mishap is associated; a process or procedure associated with the mishap; at least one person involved in or responsible one or more events leading directly to the mishap; at least one location or site associated with the mishap; a characterization of the mishap; a record associated with the mishap; a document associated with the mishap; physical evidence associated with the mishap; a value of a parameter that is part of a description associated with the mishap; a characterization or classification of a sub-system associated with the mishap; an interview of at least one person associated with the mishap; a description of at least one operation associated with the mishap; at least one inspection associated with the mishap; at least one design record of at least one component associated with the mishap; an analysis of at least one aspect of the mishap; and at least one result of an investigation of the mishap; a semantic network that receives, indexes, stores and integrates, for retrieval, the at least two ontology classes, the definition and the value ranges of the at least two ontology classes and the at least one link between the at least two ontology classes; a network browser interface, having a display screen, that implements a procedure for retrieving and viewing each of the at least two ontology classes in the semantic network, wherein the browser interface (i) displays at least one screen having at least a first group and a second group of possible conclusions concerning a contributing factor to the mishap, where no possible conclusion in the first group also belongs to the second group and (ii) displays at least one conclusion in the first group or in the second group that is characterized as at least one of the following: not a credible conclusion; an unlikely conclusion; a credible conclusion; conclusion needs analysis; conclusion needs supporting data; conclusion proposed to be closed; and an un-reviewed conclusion; and a rule-based inference engine, including a collection of at least two rules, associated with one or more of the at least two ontology classes and applied to support the at least one conclusion displayed in the browser interface. 12. The system of claim 1 , wherein said information on said characterization of said mishap event includes information on at least one of the following: type of said mishap; immediate consequences of said mishap; indirect consequences of said mishap; speculative factors that may have contributed to said mishap; confirmed factors that appear to have contributed to said mishap; recommended changes in at least one procedure to avoid or reduce a likelihood of another occurrence of said mishap; and recommended changes in at least one equipment item or component to avoid or reduce the likelihood of another occurrence of said mishap.

27. A method for generating a modified schema, comprising: using a computer system, receiving an input schema, the input schema specifying how to represent one or more elements in a document; using a computer system, receiving one or more instance documents; and using a computer system, generating one or more rules from the one or more instance documents; using a computer system, analyzing the input schema for conformance to the one or more rules; and using a computer system, if the input schema does not conform to the one or more rules, generating a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the document in conformance with the one or more rules.

27. A method for generating a modified schema, comprising: using a computer system, receiving an input schema, the input schema specifying how to represent one or more elements in a document; using a computer system, receiving one or more instance documents; and using a computer system, generating one or more rules from the one or more instance documents; using a computer system, analyzing the input schema for conformance to the one or more rules; and using a computer system, if the input schema does not conform to the one or more rules, generating a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the document in conformance with the one or more rules. 41. The method of claim 27 , wherein the modified schema is a Simple Network Management Protocol (SNMP) Management Information Base (MIB) schema.

1. A method performed by one or more devices, the method comprising: identifying, by one or more processors of the one or more devices, a plurality of documents, a first document, of the identified plurality of documents, being linked to by a second document, of the identified plurality of documents, the second document and a third document, of the identified plurality of documents, being in a set of affiliated documents; calculating, by one or more processors of the one or more devices, a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determining, by one or more processors of the one or more devices, that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assigning, by one or more processors of the one or more devices, a ranking score to the first document based on the first value calculated for the third document; and storing, by one or more processors of the one or more devices, the ranking score.

1. A method performed by one or more devices, the method comprising: identifying, by one or more processors of the one or more devices, a plurality of documents, a first document, of the identified plurality of documents, being linked to by a second document, of the identified plurality of documents, the second document and a third document, of the identified plurality of documents, being in a set of affiliated documents; calculating, by one or more processors of the one or more devices, a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determining, by one or more processors of the one or more devices, that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assigning, by one or more processors of the one or more devices, a ranking score to the first document based on the first value calculated for the third document; and storing, by one or more processors of the one or more devices, the ranking score. 7. The method of claim 1 , where affiliation among a plurality of documents in the set of affiliated documents is defined by a binary model of affiliation.

1. A system comprising: a first computer-readable storage media having stored thereon a reference dictionary file data structure, the reference dictionary file data structure including terms parsed from a plurality of documents stored in a document repository, and terms parsed from a new document received by the system but not stored in the document repository, the plurality of documents and the new document parsed without regard to any user profile, a user profile updated based at least in part on terms from the new document included in the reference dictionary file data structure and feedback from a user regarding relevance of a document received by the user before the system determines whether the new document is relevant to any user, the user profile specifying one or more areas of interest of the user; the first computer-readable storage media having stored thereon a parsed term data structure, the parsed term data structure including a one or more parsed terms and a term selection value associated with each of the one or more parsed terms, each of the parsed terms either: present in the reference dictionary file data structure indicating at least one document indicated as relevant to the user contains the term, or present in an original user profile, at least one of the parsed terms present in an original user profile and not present in the reference dictionary file data, the term selection value used for determining whether the associated term is to be included in the undated user profile; and a second computer-readable storage media having stored thereon a document dictionary index data structure and the document repository, the document dictionary index data structure including only terms located in the plurality of documents stored in the document repository.

1. A system comprising: a first computer-readable storage media having stored thereon a reference dictionary file data structure, the reference dictionary file data structure including terms parsed from a plurality of documents stored in a document repository, and terms parsed from a new document received by the system but not stored in the document repository, the plurality of documents and the new document parsed without regard to any user profile, a user profile updated based at least in part on terms from the new document included in the reference dictionary file data structure and feedback from a user regarding relevance of a document received by the user before the system determines whether the new document is relevant to any user, the user profile specifying one or more areas of interest of the user; the first computer-readable storage media having stored thereon a parsed term data structure, the parsed term data structure including a one or more parsed terms and a term selection value associated with each of the one or more parsed terms, each of the parsed terms either: present in the reference dictionary file data structure indicating at least one document indicated as relevant to the user contains the term, or present in an original user profile, at least one of the parsed terms present in an original user profile and not present in the reference dictionary file data, the term selection value used for determining whether the associated term is to be included in the undated user profile; and a second computer-readable storage media having stored thereon a document dictionary index data structure and the document repository, the document dictionary index data structure including only terms located in the plurality of documents stored in the document repository. 17. A system as defined in claim 1 , further comprising an adaptive document filtering module operable to receive a stream of new documents, to update the reference dictionary file data structure after the receipt of each new document in the stream of new documents, and to periodically update the document dictionary index data structure.

15. A computing system comprising: a processor; and computer storage memory having computer-executable instructions stored thereon which, when executed by the processor, configure the computing system to: receive a user input at an input mechanism (“IME”) program running on a computing device, the IME program enabling an associated input mechanism that provides input to multiple applications on the computing device, the user input comprising letters that do not presently constitute a full word; communicate the user input from the IME program to an active application running on the computing device; communicating the user input from the IME program to a remote contextual-service provider; receiving at the IME program a contextual-service instruction comprising information needed to provide one or more contextual services from the remote contextual-service provider; generate, by the IME program, a contextual interface that offers to provide one or more contextual services related to the user input and context in the active application; receive a user selection of a contextual service offered in the contextual interface; and initiate the contextual service.

15. A computing system comprising: a processor; and computer storage memory having computer-executable instructions stored thereon which, when executed by the processor, configure the computing system to: receive a user input at an input mechanism (“IME”) program running on a computing device, the IME program enabling an associated input mechanism that provides input to multiple applications on the computing device, the user input comprising letters that do not presently constitute a full word; communicate the user input from the IME program to an active application running on the computing device; communicating the user input from the IME program to a remote contextual-service provider; receiving at the IME program a contextual-service instruction comprising information needed to provide one or more contextual services from the remote contextual-service provider; generate, by the IME program, a contextual interface that offers to provide one or more contextual services related to the user input and context in the active application; receive a user selection of a contextual service offered in the contextual interface; and initiate the contextual service. 16. The computing system of claim 15 , wherein the contextual interface is an overlay presented with an interface associated with the active application.

28. A non-transitory recording medium storing a program which allows a computer to function as: speech recognition means which acquires speech data representing a speech and specifies words candidates included in the speech by performing speech recognition on the speech data and calculates a likelihood of each of the specified words candidates; specifying means which specifies words included in the speech based on likelihoods calculated by the speech recognition means and specifies a content of the speech uttered by an utterer based on the specified words a database which stores preceding controls, subsequent controls, and weighting factors, each of which is associated with one another therein; and process execution means which specifies content of a subsequent control to be performed on an external device to be a control target based on a currently executed control, a weighting factor stored in association with the currently executed control, and the content of the uttered speech specified by the specifying means, and performs the subsequent control, wherein the process execution means obtains the weighting factor by calculating a product of transition constants defined on routes from the currently executed control to the subsequent control associated with the currently executed control, writes the obtained weighting factor into the database, and, among the subsequent controls stored in the database associated with the currently executed control, identifies a control in which a product is a largest product of the weighting factor and the calculated likelihood.

28. A non-transitory recording medium storing a program which allows a computer to function as: speech recognition means which acquires speech data representing a speech and specifies words candidates included in the speech by performing speech recognition on the speech data and calculates a likelihood of each of the specified words candidates; specifying means which specifies words included in the speech based on likelihoods calculated by the speech recognition means and specifies a content of the speech uttered by an utterer based on the specified words a database which stores preceding controls, subsequent controls, and weighting factors, each of which is associated with one another therein; and process execution means which specifies content of a subsequent control to be performed on an external device to be a control target based on a currently executed control, a weighting factor stored in association with the currently executed control, and the content of the uttered speech specified by the specifying means, and performs the subsequent control, wherein the process execution means obtains the weighting factor by calculating a product of transition constants defined on routes from the currently executed control to the subsequent control associated with the currently executed control, writes the obtained weighting factor into the database, and, among the subsequent controls stored in the database associated with the currently executed control, identifies a control in which a product is a largest product of the weighting factor and the calculated likelihood. 35. The non-transitory recording medium according to claim 28 , wherein the process execution means specifies a content of a speech process to be performed based on the specified content of the uttered speech, and performs the specified speech process, or controls an external device in such a way as to cause the external device to perform the specified speech process.

1. A system for enabling searches of content at a server, comprising: a server which is configured to receive queries from clients for content; a communication protocol which enables an asynchronous connection between the clients and the server, and allows each client to communicate, under control of a user and as part of a session, a plurality of consecutive query strings to query the server for content; and a query and result cache that stores one or more query strings previously communicated from the clients, or content results previously returned from the server; wherein each of the clients provides an input field, which allows the user to enter as an input a query comprised of a plurality of consecutive query strings, and wherein the client transmits to the server within the session a plurality of queries to retrieve content from the server matching or related to the plurality of consecutive query strings, wherein each of the plurality of queries form an increasingly lengthening query string for retrieving content from the server; and wherein the server receives the plurality of queries from the requesting client, and in response to receiving each of one or more additional characters in the increasingly lengthening query string as they are being entered at the input field, automatically matches the increasingly lengthening query string initially by matching the query string against the content of the query and result cache, and subsequently by matching the query string against other content available to the server, and asynchronously returns, while the increasingly lengthening query string is being entered by the user at the input field at the client, increasingly relevant content to the client.

1. A system for enabling searches of content at a server, comprising: a server which is configured to receive queries from clients for content; a communication protocol which enables an asynchronous connection between the clients and the server, and allows each client to communicate, under control of a user and as part of a session, a plurality of consecutive query strings to query the server for content; and a query and result cache that stores one or more query strings previously communicated from the clients, or content results previously returned from the server; wherein each of the clients provides an input field, which allows the user to enter as an input a query comprised of a plurality of consecutive query strings, and wherein the client transmits to the server within the session a plurality of queries to retrieve content from the server matching or related to the plurality of consecutive query strings, wherein each of the plurality of queries form an increasingly lengthening query string for retrieving content from the server; and wherein the server receives the plurality of queries from the requesting client, and in response to receiving each of one or more additional characters in the increasingly lengthening query string as they are being entered at the input field, automatically matches the increasingly lengthening query string initially by matching the query string against the content of the query and result cache, and subsequently by matching the query string against other content available to the server, and asynchronously returns, while the increasingly lengthening query string is being entered by the user at the input field at the client, increasingly relevant content to the client. 8. The system of claim 1 , wherein the system is provided as a system for searching for documents in full-text databases.

1. A non-transitory computer-readable medium embodying a program executable in a computing device, wherein, when executed, the program causes the computing device to at least: identify a plurality of third party profiles corresponding to a plurality of third party users based at least in part on at least one third party selection criterion, the at least one third party selection criterion being received from a first network page rendered on a client device, wherein identifying the plurality of third party profiles based at least in part on the at least one third party selection criterion comprises comparing a plurality of significant terms extracted from a first profile and a second profile associated with a single user account to a respective description for individual ones of the plurality of third party profiles, the plurality of significant terms being extracted from the first profile and the second profile based at least in part on identifying at least one of a grammatically emphasized term or a frequently used term; generate a second network page associated with a topic received from the client device, the second network page comprising a user interface to facilitate an input of a plurality of suggestions from at least one of a plurality of devices associated with the plurality of third party users, wherein the plurality of suggestions are associated with at least one item offered by an electronic commerce system; and cause the second network page to be transmitted to the client device and the plurality of devices associated with the plurality of third party users.

1. A non-transitory computer-readable medium embodying a program executable in a computing device, wherein, when executed, the program causes the computing device to at least: identify a plurality of third party profiles corresponding to a plurality of third party users based at least in part on at least one third party selection criterion, the at least one third party selection criterion being received from a first network page rendered on a client device, wherein identifying the plurality of third party profiles based at least in part on the at least one third party selection criterion comprises comparing a plurality of significant terms extracted from a first profile and a second profile associated with a single user account to a respective description for individual ones of the plurality of third party profiles, the plurality of significant terms being extracted from the first profile and the second profile based at least in part on identifying at least one of a grammatically emphasized term or a frequently used term; generate a second network page associated with a topic received from the client device, the second network page comprising a user interface to facilitate an input of a plurality of suggestions from at least one of a plurality of devices associated with the plurality of third party users, wherein the plurality of suggestions are associated with at least one item offered by an electronic commerce system; and cause the second network page to be transmitted to the client device and the plurality of devices associated with the plurality of third party users. 3. The non-transitory computer-readable medium of claim 1 , wherein the program further causes the computing device to at least: generate a group request user interface configured to receive the at least one third party selection criterion as a percentage similarity and the topic from the client device; and cause data encoding the group request user interface to be transmitted to the client device.

16. The system of claim 1 , wherein the generic decoder is configured to: in response to not matching at least a portion of the second one or more parts to the first predetermined pattern, skip the first predetermined number of bytes in the second one or more parts; and search the second one or more parts for a second predetermined pattern.

16. The system of claim 1 , wherein the generic decoder is configured to: in response to not matching at least a portion of the second one or more parts to the first predetermined pattern, skip the first predetermined number of bytes in the second one or more parts; and search the second one or more parts for a second predetermined pattern. 18. The system of claim 16 , wherein the generic decoder is configured to: in response to not matching at least a portion of the second one or more parts to the second predetermined pattern, refraining from generating the error signal; and in response to matching at least a portion of the second one or more parts to the second predetermined pattern storing a second predetermined number of bytes of the second one or more parts in an array, determining a number of bytes stored in the array, and generating the error signal in response to the number of bytes stored in the array being greater than a third predetermined number of bytes.

16. A system for determining a relevancy ranking score, comprising: a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive a query including one or more constraints, wherein one of the one or more constraints includes an operator, wherein the operator comprises one or more of the following: CONTAINS, DOES_NOT_CONTAIN, BEGINS_WITH, ENDS_WITH, ALWAYS_WITHIN, AND, OR, NOT, EQUALS, NOT_EQUALS, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL_TO, LESS_THAN_OR_EQUAL_TO; receive a search result based on the query; and determine the relevancy ranking score for the received search result based at least in part on the operator associated with the one or more constraints of the query, wherein the relevancy ranking score comprises a sum of three or more feature scores each multiplied by a separate weight, wherein the three or more feature scores comprise a scope or depth score, an accuracy or validity score, a clarity score, a currency score, or a source score, and wherein the scope or depth score comprises a score indicating satisfied constraints, and wherein the accuracy or validity score comprises a score indicating constraints improving query precision, and wherein the clarity score comprises a score indicating information presented in a clear manner, and wherein the currency score comprises a score indicating more recent results, and wherein the source score comprises a score indicating source quality, wherein presented in the clear manner for the clarity score comprises having a higher score in an event in which a title, an abstract, or a date is present.

16. A system for determining a relevancy ranking score, comprising: a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive a query including one or more constraints, wherein one of the one or more constraints includes an operator, wherein the operator comprises one or more of the following: CONTAINS, DOES_NOT_CONTAIN, BEGINS_WITH, ENDS_WITH, ALWAYS_WITHIN, AND, OR, NOT, EQUALS, NOT_EQUALS, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL_TO, LESS_THAN_OR_EQUAL_TO; receive a search result based on the query; and determine the relevancy ranking score for the received search result based at least in part on the operator associated with the one or more constraints of the query, wherein the relevancy ranking score comprises a sum of three or more feature scores each multiplied by a separate weight, wherein the three or more feature scores comprise a scope or depth score, an accuracy or validity score, a clarity score, a currency score, or a source score, and wherein the scope or depth score comprises a score indicating satisfied constraints, and wherein the accuracy or validity score comprises a score indicating constraints improving query precision, and wherein the clarity score comprises a score indicating information presented in a clear manner, and wherein the currency score comprises a score indicating more recent results, and wherein the source score comprises a score indicating source quality, wherein presented in the clear manner for the clarity score comprises having a higher score in an event in which a title, an abstract, or a date is present. 18. A system as in claim 16 , wherein the search result includes a ranking from a search source.

13. A computer-implemented method of determining search results related to a search query, the method comprising: receiving a search query from a computer via a computer network; submitting the search query to a plurality of search engines; receiving, from the plurality of search engines, at least a first ranked list that includes at least two actual relevance values and includes one or more search results without actual relevance values; determining an estimated relevance value for each search result of the first ranked list without an actual relevance value, wherein the estimated relevance value of a particular search result of the first ranked list without an actual relevance value is based on a rank of the particular search result in the first ranked list and the actual relevance values and ranks of at least two other search results from the first ranked list; determining, for each of the plurality of search engines, a weighting value, wherein determining the weighting value for each of the plurality of search engines comprises applying a first weighting factor to a search engine for a specialized information base that pertains to the search query and a second weighting factor to a search engine for a general information base, and wherein the first weighting factor is greater than the second weighting factor; determining, for each ranked list, a weighted relevance value for each search result based on the estimated relevance value when the actual relevance value was not received for the search result, the actual relevance value of the search result when the actual relevance value was received for the search result, and the weighting value associated with the search engine that provided the ranked list; combining the search results into a single list; sorting the search results in the single list based on the weighted relevance values; and sending at least a portion of the single list to the computer via the computer network for display to a user.

13. A computer-implemented method of determining search results related to a search query, the method comprising: receiving a search query from a computer via a computer network; submitting the search query to a plurality of search engines; receiving, from the plurality of search engines, at least a first ranked list that includes at least two actual relevance values and includes one or more search results without actual relevance values; determining an estimated relevance value for each search result of the first ranked list without an actual relevance value, wherein the estimated relevance value of a particular search result of the first ranked list without an actual relevance value is based on a rank of the particular search result in the first ranked list and the actual relevance values and ranks of at least two other search results from the first ranked list; determining, for each of the plurality of search engines, a weighting value, wherein determining the weighting value for each of the plurality of search engines comprises applying a first weighting factor to a search engine for a specialized information base that pertains to the search query and a second weighting factor to a search engine for a general information base, and wherein the first weighting factor is greater than the second weighting factor; determining, for each ranked list, a weighted relevance value for each search result based on the estimated relevance value when the actual relevance value was not received for the search result, the actual relevance value of the search result when the actual relevance value was received for the search result, and the weighting value associated with the search engine that provided the ranked list; combining the search results into a single list; sorting the search results in the single list based on the weighted relevance values; and sending at least a portion of the single list to the computer via the computer network for display to a user. 18. The method of claim 13 , wherein the portion of the single list provided for display to the user includes hyperlinks to electronic documents.

2. The computer implemented method of claim 1 further comprising selecting, by the computer one or more secondary themes from a plurality of secondary themes.

2. The computer implemented method of claim 1 further comprising selecting, by the computer one or more secondary themes from a plurality of secondary themes. 3. The computer implemented method of claim 2 further comprising generating, by the computer, the one or more secondary queries by selecting one or more keywords associated with the selected one or more secondary themes.

14. The computer system according to claim 1 , wherein the emotion generator outputs the emotion response message in emotion categories having differing validity time periods based on at least one of the social response message stored in the event buffer, one or more outputs from the predefined personality trait register, or one or more outputs from the emotional state register.

14. The computer system according to claim 1 , wherein the emotion generator outputs the emotion response message in emotion categories having differing validity time periods based on at least one of the social response message stored in the event buffer, one or more outputs from the predefined personality trait register, or one or more outputs from the emotional state register. 15. The computer system according to claim 14 , wherein the emotion categories comprise at least a lasting emotion category, a short-lived emotion category and a momentary emotion category.

15. A speech recognition error detection system, the system comprising: a computer processor; and a computer readable storage medium storing executable code when executed by the computer processor performs actions comprising: analyzing an utterance received from an audio input device; generating a text sentence of one or more words based on the utterance; generating a N-best list of predicted error sequences of the generated text sentence, wherein each of the one or more words of the text sentence is assigned a label in the N-best list of predicted error sequences, wherein the label represents a likelihood of error that is associated with each word of the one of more words of the text sentence, wherein the label is assigned a probability score indicative of a probability that the label is accurate, wherein the probability score for the label is determined by a weighted sum of at least two word features; rescoring each label of the N-best list of the predicted error sequences, wherein rescoring each label of the N-best list of predicted error sequences comprises using optimal metacost parameters to rescore each label, wherein the optimal metacost parameters are parameters of a metacost matrix; and selecting a best rescored error sequence from the N-best list of the predicted error sequences based on rescored labels; and executing a dialog action based on the best rescored error sequence and a dialog action policy, wherein the dialog action policy indicates the dialog action based on the rescored labels of the best rescored error sequence, wherein executing the dialog action includes controlling an electronic computing device to execute at least one of: playing back of at least a portion of the text sentence and requesting a confirmation of accuracy of the text sentence when the best rescored error sequence comprises a major error, and discarding the text sentence and requesting to repeat the utterance when the best rescored error sequence comprises at least two of the major errors, wherein the best rescored error sequence comprises the major error when the one or more words of the text sentence include a noun, a proper-noun, or a verb, wherein executing the dialog action includes controlling the electronic computing device to compare the dialog action of the best rescored error sequence to a previously determined dialog action of a previously selected best rescored error sequence to determine if the dialog action of the best rescored error sequence is less or more severe than the previously determined dialog action policy of the previously selected best rescored error sequence, wherein the electronic computing device is controlled to update optimal metacost parameters of a metacost matrix when it is determined that the dialog action of the best rescored error sequence is more severe than the previously determined dialog action policy of the previously selected best rescored error sequence.

15. A speech recognition error detection system, the system comprising: a computer processor; and a computer readable storage medium storing executable code when executed by the computer processor performs actions comprising: analyzing an utterance received from an audio input device; generating a text sentence of one or more words based on the utterance; generating a N-best list of predicted error sequences of the generated text sentence, wherein each of the one or more words of the text sentence is assigned a label in the N-best list of predicted error sequences, wherein the label represents a likelihood of error that is associated with each word of the one of more words of the text sentence, wherein the label is assigned a probability score indicative of a probability that the label is accurate, wherein the probability score for the label is determined by a weighted sum of at least two word features; rescoring each label of the N-best list of the predicted error sequences, wherein rescoring each label of the N-best list of predicted error sequences comprises using optimal metacost parameters to rescore each label, wherein the optimal metacost parameters are parameters of a metacost matrix; and selecting a best rescored error sequence from the N-best list of the predicted error sequences based on rescored labels; and executing a dialog action based on the best rescored error sequence and a dialog action policy, wherein the dialog action policy indicates the dialog action based on the rescored labels of the best rescored error sequence, wherein executing the dialog action includes controlling an electronic computing device to execute at least one of: playing back of at least a portion of the text sentence and requesting a confirmation of accuracy of the text sentence when the best rescored error sequence comprises a major error, and discarding the text sentence and requesting to repeat the utterance when the best rescored error sequence comprises at least two of the major errors, wherein the best rescored error sequence comprises the major error when the one or more words of the text sentence include a noun, a proper-noun, or a verb, wherein executing the dialog action includes controlling the electronic computing device to compare the dialog action of the best rescored error sequence to a previously determined dialog action of a previously selected best rescored error sequence to determine if the dialog action of the best rescored error sequence is less or more severe than the previously determined dialog action policy of the previously selected best rescored error sequence, wherein the electronic computing device is controlled to update optimal metacost parameters of a metacost matrix when it is determined that the dialog action of the best rescored error sequence is more severe than the previously determined dialog action policy of the previously selected best rescored error sequence. 17. The speech recognition error detection system of claim 15 , wherein controlling the electronic computing device to update the optimal metacost parameters includes applying a random adjustment to the optimal metacost parameters; and controlling the electronic computing device to execute the dialog action based on the best rescored error sequence when it is determined that the dialog action of the best rescored error sequence is less severe than the previously determined dialog action policy of the previously selected best rescored error sequence.

9. A computer implemented method comprising: rendering an interface for a resource application of a client device that includes a display area configured to present a resource; presenting the resource in the display area; exposing an annotation portion in the interface that is configured to enable input of annotations for the presented resource in accordance with a location setting of the client device associated with a user profile, the presented resource unmodified by the annotations, wherein the user profile is one of at least two user profiles associated with a user of the client device, and wherein each of the at least two user profiles is associated with a different location of the client device; receiving an annotation input via the annotation portion; and communicating with an annotation server to store the annotation for the presented resource at predetermined times in response to the receiving the annotation.

9. A computer implemented method comprising: rendering an interface for a resource application of a client device that includes a display area configured to present a resource; presenting the resource in the display area; exposing an annotation portion in the interface that is configured to enable input of annotations for the presented resource in accordance with a location setting of the client device associated with a user profile, the presented resource unmodified by the annotations, wherein the user profile is one of at least two user profiles associated with a user of the client device, and wherein each of the at least two user profiles is associated with a different location of the client device; receiving an annotation input via the annotation portion; and communicating with an annotation server to store the annotation for the presented resource at predetermined times in response to the receiving the annotation. 10. The computer implemented method of claim 9 , wherein the communicating comprises communicating according to a scheduled interval.

1. A computer-implemented method comprising: receiving, by a computer-implemented agent specific to a user device, data representing properties of another computer-implemented agent including receiving an identification of a selection of a particular spoken style of speech for the other computer-implemented agent from among two or more different spoken styles of speech for a particular language; receiving, by the computer-implemented agent, a digital representation of speech encoding an utterance after receiving the data representing the properties of the other computer-implemented agent; determining, by the computer-implemented agent, that the utterance specifies a requirement to establish a communication with the other computer-implemented agent; establishing, by the computer-implemented agent, a communication between the other computer-implemented agent and the user device; receiving, by the user device, identification of a response to the utterance from the other computer-implemented agent; determining, by the computer-implemented agent, the particular spoken style of speech for the other computer-implemented agent, for the presentation of the response; and presenting, by the user device, the response to the utterance received from the other computer-implemented agent according to the particular spoken style of speech.

1. A computer-implemented method comprising: receiving, by a computer-implemented agent specific to a user device, data representing properties of another computer-implemented agent including receiving an identification of a selection of a particular spoken style of speech for the other computer-implemented agent from among two or more different spoken styles of speech for a particular language; receiving, by the computer-implemented agent, a digital representation of speech encoding an utterance after receiving the data representing the properties of the other computer-implemented agent; determining, by the computer-implemented agent, that the utterance specifies a requirement to establish a communication with the other computer-implemented agent; establishing, by the computer-implemented agent, a communication between the other computer-implemented agent and the user device; receiving, by the user device, identification of a response to the utterance from the other computer-implemented agent; determining, by the computer-implemented agent, the particular spoken style of speech for the other computer-implemented agent, for the presentation of the response; and presenting, by the user device, the response to the utterance received from the other computer-implemented agent according to the particular spoken style of speech. 6. The method of claim 1 comprising: providing a representation of the utterance to the other computer-implemented agent.

5. A system comprising: a processor; a data bus coupled to the processor; and a computer-usable memory embodying computer program code, the computer-usable memory being coupled to the data bus, the computer program code comprising instructions executable by the processor and configured for: transmitting a Shareable Content Object Reference Model (SCORM) package to a SCORM Learning Management System (LMS), wherein the SCORM package includes a manifest listing of resources needed to deploy the SCORM package from the LMS; parsing out the manifest listing from the SCORM package; iterating through the manifest listing to create an inventory of the resources in the SCORM package, wherein the inventory of the resources includes an attribute file; comparing names of all resources in the manifest listing with named resources in the attribute file in the inventory of resources available to the LMS; in response to a name in the manifest listing not completely matching any named resources in the attribute file in the inventory of resources available to the LMS, updating a character casing of the name to match a character casing of a corresponding name of a named resource in the attribute file in the inventory of resources available to the LMS, wherein the character casing of the corresponding name of the named resource includes one or more upper case letters and on or more lower case letters; and deploying the SCORM package by launching the SCORM package with a corrected list of resources matching the attribute file in the inventory of resource available to the LMS.

5. A system comprising: a processor; a data bus coupled to the processor; and a computer-usable memory embodying computer program code, the computer-usable memory being coupled to the data bus, the computer program code comprising instructions executable by the processor and configured for: transmitting a Shareable Content Object Reference Model (SCORM) package to a SCORM Learning Management System (LMS), wherein the SCORM package includes a manifest listing of resources needed to deploy the SCORM package from the LMS; parsing out the manifest listing from the SCORM package; iterating through the manifest listing to create an inventory of the resources in the SCORM package, wherein the inventory of the resources includes an attribute file; comparing names of all resources in the manifest listing with named resources in the attribute file in the inventory of resources available to the LMS; in response to a name in the manifest listing not completely matching any named resources in the attribute file in the inventory of resources available to the LMS, updating a character casing of the name to match a character casing of a corresponding name of a named resource in the attribute file in the inventory of resources available to the LMS, wherein the character casing of the corresponding name of the named resource includes one or more upper case letters and on or more lower case letters; and deploying the SCORM package by launching the SCORM package with a corrected list of resources matching the attribute file in the inventory of resource available to the LMS. 6. The system of claim 5 , wherein the manifest listing of resources needed to deploy the SCORM package is located in a SCORM “imsmanifest.xml” file that is part of the SCORM package.

15. An electronic computing system comprising: a display device; a processing unit comprising at least one integrated circuit; and a data storage system comprising at least one computer-readable data storage medium, the data storage system comprising instructions that, when executed by the processing unit cause the electronic computing device to: display a graphical user interface on the display device, the graphical user interface comprising a document area and a control ribbon, the document area containing at least a portion of a document that a user is currently editing, the control ribbon containing a first horizontal control gallery, the first horizontal control gallery containing a plurality of class controls, each class control in the plurality of class controls associated with a different class in a plurality of classes, each class control in the plurality of class controls containing a class icon graphically describing the class associated with the class control, each class in the plurality of classes being a subset of related commands in an overall set of commands; select one of the plurality of class controls displayed in the first horizontal control gallery; in response to the selection of one of the plurality of class controls, display a preview of a default slide transition effect (STE) associated with the one of the plurality of class controls; receive a class selection input from the user, the class selection input indicating a selected class control from among the plurality of class controls, the selected class control associated with a selected class in the plurality of classes; modify, in response to receiving the class selection input, the document by executing a default command associated with the selected class; after receiving the class selection input, display, in the graphical user interface, a second vertical control gallery in the graphical user interface, the second control gallery containing a plurality of variation controls, each variation control in the plurality of variation controls associated with a different command in the selected class, the second vertical control gallery not containing any variation controls in ones of the classes other than the selected class; select one of the plurality of variation controls displayed in the second vertical control gallery; in response to the selection of one of the plurality of variation controls in the second vertical gallery, display a preview of a default slide transition effect (STE) associated with the one of the plurality of variation controls; receive, while the second vertical control gallery is displayed, a variation selection input from the user, the variation selection input indicating a selected variation control in the plurality of variation controls in the second vertical control gallery; and modify, in response to receiving the variation selection input, the document by executing the command associated with the selected variation control.

15. An electronic computing system comprising: a display device; a processing unit comprising at least one integrated circuit; and a data storage system comprising at least one computer-readable data storage medium, the data storage system comprising instructions that, when executed by the processing unit cause the electronic computing device to: display a graphical user interface on the display device, the graphical user interface comprising a document area and a control ribbon, the document area containing at least a portion of a document that a user is currently editing, the control ribbon containing a first horizontal control gallery, the first horizontal control gallery containing a plurality of class controls, each class control in the plurality of class controls associated with a different class in a plurality of classes, each class control in the plurality of class controls containing a class icon graphically describing the class associated with the class control, each class in the plurality of classes being a subset of related commands in an overall set of commands; select one of the plurality of class controls displayed in the first horizontal control gallery; in response to the selection of one of the plurality of class controls, display a preview of a default slide transition effect (STE) associated with the one of the plurality of class controls; receive a class selection input from the user, the class selection input indicating a selected class control from among the plurality of class controls, the selected class control associated with a selected class in the plurality of classes; modify, in response to receiving the class selection input, the document by executing a default command associated with the selected class; after receiving the class selection input, display, in the graphical user interface, a second vertical control gallery in the graphical user interface, the second control gallery containing a plurality of variation controls, each variation control in the plurality of variation controls associated with a different command in the selected class, the second vertical control gallery not containing any variation controls in ones of the classes other than the selected class; select one of the plurality of variation controls displayed in the second vertical control gallery; in response to the selection of one of the plurality of variation controls in the second vertical gallery, display a preview of a default slide transition effect (STE) associated with the one of the plurality of variation controls; receive, while the second vertical control gallery is displayed, a variation selection input from the user, the variation selection input indicating a selected variation control in the plurality of variation controls in the second vertical control gallery; and modify, in response to receiving the variation selection input, the document by executing the command associated with the selected variation control. 19. The electronic computing system of claim 15 , wherein the at least one computer-readable data storage medium is a random access memory unit and the at least one integrated circuit is a microprocessor.

3. The system of claim 2 , wherein the one or more terms comprises the candidate.

3. The system of claim 2 , wherein the one or more terms comprises the candidate. 4. The system of claim 3 , wherein the memory stores instructions that, when executed by the processor, configure the processor to search in the stored sequences for a sequence comprising a context sequence in combination with each candidate, wherein the context sequence is user inputted text that precedes the input sequence and comprises one or more terms separated by one or more term boundaries.

12. The computer-implemented method of claim 9 further comprising: under direction of the one or more hardware processors configured with specific software instructions, further in response to receiving the command and the node identifier: deleting the first portion of the textual record.

12. The computer-implemented method of claim 9 further comprising: under direction of the one or more hardware processors configured with specific software instructions, further in response to receiving the command and the node identifier: deleting the first portion of the textual record. 13. The computer-implemented method of claim 12 , wherein a cursor is placed at a previous location of the deleted first portion of the textual record after the first portion of the textual record is deleted.

1. A computer program product embodied on a non-transitory computer readable recording medium having a computer program stored thereon, the computer program comprising: a code module for initializing a hierarchical directory folder structure by propagating one or more folders of an initial hierarchical layer; a code module for providing a terminal with identification information of said one or more folders propagated at the initial hierarchical layer, any intervening hierarchical layers, and a current hierarchical layer to be displayed by the terminal, wherein the identification information of each folder includes an indication of a respective character; a code module for receiving input from the terminal of a selected folder of the current hierarchical layer; a code module for identifying the respective character of the selected folder input from the terminal; a code module for evaluating a folder path by concatenating the respective character of the selected folder of the current hierarchical layer with any respective characters of any folders of any of the initial hierarchical layer and intervening hierarchical layers to create a character sequence; a code module for searching a memory for files using the character sequence as a search keyword; a code module for propagating one or more folders for a next hierarchical layer and for submitting the results of searching using the search keyword to be displayed at the next hierarchical layer; and a code module for referencing a folder ID table storage, wherein, when one of the folders of the current hierarchical layer is selected by the terminal, the respective character of the selected folder is identified by referencing the folder ID table storage and is concatenated onto the character sequence to be used as the search keyword.

1. A computer program product embodied on a non-transitory computer readable recording medium having a computer program stored thereon, the computer program comprising: a code module for initializing a hierarchical directory folder structure by propagating one or more folders of an initial hierarchical layer; a code module for providing a terminal with identification information of said one or more folders propagated at the initial hierarchical layer, any intervening hierarchical layers, and a current hierarchical layer to be displayed by the terminal, wherein the identification information of each folder includes an indication of a respective character; a code module for receiving input from the terminal of a selected folder of the current hierarchical layer; a code module for identifying the respective character of the selected folder input from the terminal; a code module for evaluating a folder path by concatenating the respective character of the selected folder of the current hierarchical layer with any respective characters of any folders of any of the initial hierarchical layer and intervening hierarchical layers to create a character sequence; a code module for searching a memory for files using the character sequence as a search keyword; a code module for propagating one or more folders for a next hierarchical layer and for submitting the results of searching using the search keyword to be displayed at the next hierarchical layer; and a code module for referencing a folder ID table storage, wherein, when one of the folders of the current hierarchical layer is selected by the terminal, the respective character of the selected folder is identified by referencing the folder ID table storage and is concatenated onto the character sequence to be used as the search keyword. 5. The computer program product of claim 1 , wherein the terminal is provided selection recognition of a folder through selection input by means other than with use of a pseudo device interface or a physical input device in which characters are presented.

53. A non-transitory computer-readable medium encoded with a system to process at least one document image comprising a plurality of text rows and a plurality of characters, each text row having at least one character, the system comprising a plurality of modules to execute on at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; and a classification system comprising: a subsets module to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine an initial subset of rows for each column, each initial subset of rows comprising one or more of the text rows of the at least one document image having at least one alignment of at least one character block in a selected column, each initial subset of rows having a set of columns comprising the selected column and other columns in the one or more text rows of a corresponding initial subset of rows in which the selected column is present; an optimum set module to determine an optimum set of columns for each initial subset of rows by: generating a histogram of column frequencies of the set of columns in the corresponding initial subset of rows, each column frequency comprising a number of times a particular column occurs in the corresponding initial subset of rows; determining a threshold of the column frequencies for the corresponding initial subset of rows; and selecting particular columns having the column frequency above the threshold to be included in a corresponding optimum set; a division module to: determine a final subset of rows for each initial subset of rows, each final subset of rows comprising at least one text row of the corresponding initial subset of rows having physical structures most similar to the corresponding optimum set when compared to physical structures of all text rows in the corresponding initial subset of rows; determine a confidence factor for each final subset of rows; and determine a best confidence factor for each particular text row in the at least one document image; and a classifier module to create at least one class of text rows, the at least one class comprising at least one particular text row having a same best confidence factor.

53. A non-transitory computer-readable medium encoded with a system to process at least one document image comprising a plurality of text rows and a plurality of characters, each text row having at least one character, the system comprising a plurality of modules to execute on at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; and a classification system comprising: a subsets module to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine an initial subset of rows for each column, each initial subset of rows comprising one or more of the text rows of the at least one document image having at least one alignment of at least one character block in a selected column, each initial subset of rows having a set of columns comprising the selected column and other columns in the one or more text rows of a corresponding initial subset of rows in which the selected column is present; an optimum set module to determine an optimum set of columns for each initial subset of rows by: generating a histogram of column frequencies of the set of columns in the corresponding initial subset of rows, each column frequency comprising a number of times a particular column occurs in the corresponding initial subset of rows; determining a threshold of the column frequencies for the corresponding initial subset of rows; and selecting particular columns having the column frequency above the threshold to be included in a corresponding optimum set; a division module to: determine a final subset of rows for each initial subset of rows, each final subset of rows comprising at least one text row of the corresponding initial subset of rows having physical structures most similar to the corresponding optimum set when compared to physical structures of all text rows in the corresponding initial subset of rows; determine a confidence factor for each final subset of rows; and determine a best confidence factor for each particular text row in the at least one document image; and a classifier module to create at least one class of text rows, the at least one class comprising at least one particular text row having a same best confidence factor. 54. The system of claim 53 wherein: the subsets module determines the initial subset of rows for each column having more than one character block aligned in that column in the text rows of the at least one document image; and in the division module: each final subset of rows comprises at least one of the one or more text rows of the corresponding initial subset of rows having a corresponding physical structure that is most similar to the corresponding optimum set when compared to physical structures of all of the one or more text rows of the corresponding initial subset of rows; each confidence factor measures a similarity of corresponding physical structures of the at least one of the one or more text rows in one corresponding final subset of rows to each other; and each particular text row has at least one confidence factor corresponding to at least one final subset of rows in which the particular text row is an element.

8. A non-transitory, computer-readable medium comprising computer-executable instructions for causing one or more computer processors of an analytics processing system to: monitor a communication being conducted by a particular agent of a contact center and a contact party in real-time; detecting an occurrence of a particular keyphrase during the monitoring; and in response to detecting the occurrence of the particular keyphrase: query memory based on the particular keyphrase to identify a particular information resource, wherein the particular keyphrase had been previously identified in at least two prior communications conducted between agents at the contact center and contact parties by performing at least one of speech analytics and text analytics on the prior communications and the particular information resource had been previously associated with the particular keyphrase by determining a pattern of utilization of one or more information resources used by the agents during the prior communications conducted with the contact parties in which the one or more information resources provided different information that may have been helpful to the agents during the prior communications and selecting the particular information resource based on the pattern of utilization; and make the particular information resource available to the particular agent during the communication.

8. A non-transitory, computer-readable medium comprising computer-executable instructions for causing one or more computer processors of an analytics processing system to: monitor a communication being conducted by a particular agent of a contact center and a contact party in real-time; detecting an occurrence of a particular keyphrase during the monitoring; and in response to detecting the occurrence of the particular keyphrase: query memory based on the particular keyphrase to identify a particular information resource, wherein the particular keyphrase had been previously identified in at least two prior communications conducted between agents at the contact center and contact parties by performing at least one of speech analytics and text analytics on the prior communications and the particular information resource had been previously associated with the particular keyphrase by determining a pattern of utilization of one or more information resources used by the agents during the prior communications conducted with the contact parties in which the one or more information resources provided different information that may have been helpful to the agents during the prior communications and selecting the particular information resource based on the pattern of utilization; and make the particular information resource available to the particular agent during the communication. 13. The non-transitory, computer-readable medium of claim 8 , wherein the particular information resource is made available to the particular agent through a computer workstation being used by the particular agent.

3. The method of claim 1 , further comprising converting the value of each attribute to text and storing the text as the indication of the value of the attribute.

3. The method of claim 1 , further comprising converting the value of each attribute to text and storing the text as the indication of the value of the attribute. 4. The method of claim 3 , wherein storing the indication of the value of each attribute in the indexed composite document comprises concatenating the indication of the value of each attribute and the assigned metadata to the indexed composite document.

23. One or more non-transitory storage media as recited in claim 16 , wherein the particular portion is at least part of a first document, wherein the instructions, when executed by the one or more computing devices, cause performance of: determining that the unstructured database column in the database stores a second document of non-marked up text; in response to determining that the unstructured database column in the database stores the second document of non-marked up text, skipping the second document when evaluating the expression.

23. One or more non-transitory storage media as recited in claim 16 , wherein the particular portion is at least part of a first document, wherein the instructions, when executed by the one or more computing devices, cause performance of: determining that the unstructured database column in the database stores a second document of non-marked up text; in response to determining that the unstructured database column in the database stores the second document of non-marked up text, skipping the second document when evaluating the expression. 33. One or more non-transitory storage media as recited in claim 23 , wherein the first document and the second document are stored in the unstructured database column without indicating whether the first document conforms to the markup language, and without indicating whether the second document conforms to the markup language.

1. A device for detecting an emotional state change in an audio signal, the device comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations including: receiving a plurality of segments of the audio signal, the plurality of segments being sequential; sequentially analyzing each segment of the plurality of segments and determining, for each segment, an emotional state from among a plurality of emotional states and a confidence score of the emotional state; sequentially analyzing the emotional state and the confidence score of each segment and tracking a current emotional state of the audio signal throughout each of the plurality of segments; and determining, for each segment, whether the current emotional state of the audio signal changes to an other emotional state of the plurality of emotional states based on the emotional state and the confidence score of the segment, wherein the processor determines that the current emotional state of the audio signal changes to the other emotional state of the plurality of emotional states when the emotional state of a predetermined number of the plurality of segments is the other emotional state with the confidence score of the emotional state of each of the predetermined number of the plurality of segments being below a predetermined threshold.

1. A device for detecting an emotional state change in an audio signal, the device comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations including: receiving a plurality of segments of the audio signal, the plurality of segments being sequential; sequentially analyzing each segment of the plurality of segments and determining, for each segment, an emotional state from among a plurality of emotional states and a confidence score of the emotional state; sequentially analyzing the emotional state and the confidence score of each segment and tracking a current emotional state of the audio signal throughout each of the plurality of segments; and determining, for each segment, whether the current emotional state of the audio signal changes to an other emotional state of the plurality of emotional states based on the emotional state and the confidence score of the segment, wherein the processor determines that the current emotional state of the audio signal changes to the other emotional state of the plurality of emotional states when the emotional state of a predetermined number of the plurality of segments is the other emotional state with the confidence score of the emotional state of each of the predetermined number of the plurality of segments being below a predetermined threshold. 6. The device according to claim 1 , further comprising: a database that stores the audio signal and tracked emotional states in association with a customer service agent.

12. An apparatus for mapping an XML encoded dataset into a set of SQL tables, said apparatus comprising: at least one processor for identifying at least one hierarchical structure associated with said XML encoded dataset; and a converter for converting said XML encoded dataset associated with said identified hierarchical structure, said converter comprising: at least one processor for determining a node element set for said identified hierarchical structure of said XML encoded dataset, wherein a node element in said node element set is a discrete level of said identified hierarchical structure of said dataset; at least one processor for determining one or more nodes of said XML encoded dataset, said node being an instance of a node element; an allocator for allocating to said node a unique node identifier; and a generator for generating an SQL node table containing one or more records, said record corresponding to a respective one or more of said allocated node identifiers; wherein said XML encoded dataset includes a plurality of predefined portions of text-based data, said predefined portions of said text-based data being encoded using XML, and being associated with a plurality of attributes for organizing said predefined portions of said text-based data; and wherein said predefined portions include at least one modified and stored predefined portion encoded using XML, said modified predefined portion being associated with one or more attributes for organizing said predefined portions and said modified predefined portion of said text-based data.

12. An apparatus for mapping an XML encoded dataset into a set of SQL tables, said apparatus comprising: at least one processor for identifying at least one hierarchical structure associated with said XML encoded dataset; and a converter for converting said XML encoded dataset associated with said identified hierarchical structure, said converter comprising: at least one processor for determining a node element set for said identified hierarchical structure of said XML encoded dataset, wherein a node element in said node element set is a discrete level of said identified hierarchical structure of said dataset; at least one processor for determining one or more nodes of said XML encoded dataset, said node being an instance of a node element; an allocator for allocating to said node a unique node identifier; and a generator for generating an SQL node table containing one or more records, said record corresponding to a respective one or more of said allocated node identifiers; wherein said XML encoded dataset includes a plurality of predefined portions of text-based data, said predefined portions of said text-based data being encoded using XML, and being associated with a plurality of attributes for organizing said predefined portions of said text-based data; and wherein said predefined portions include at least one modified and stored predefined portion encoded using XML, said modified predefined portion being associated with one or more attributes for organizing said predefined portions and said modified predefined portion of said text-based data. 14. The apparatus according to claim 12 , wherein said record of said node table contains said node identifier.

1. A method for automatic speech recognition, the method comprising: receiving a frame of a speech signal; expanding, by a processor, a search network based on the frame; determining, by the processor, a best hypothesis in the search network; modifying, by the processor, a beam threshold based on a time the frame was received to produce a modified beam threshold, wherein modifying a beam threshold further comprises modifying the beam threshold based on a speed with which the search network is increasing in size; and pruning, by the processor, the search network using the best hypothesis and the modified beam threshold.

1. A method for automatic speech recognition, the method comprising: receiving a frame of a speech signal; expanding, by a processor, a search network based on the frame; determining, by the processor, a best hypothesis in the search network; modifying, by the processor, a beam threshold based on a time the frame was received to produce a modified beam threshold, wherein modifying a beam threshold further comprises modifying the beam threshold based on a speed with which the search network is increasing in size; and pruning, by the processor, the search network using the best hypothesis and the modified beam threshold. 3. The method of claim 1 , wherein modifying the beam threshold based on a speed further comprises increasing the beam threshold by an empirically determined amount if an acceleration of the speed of the size increase for the frame exceeds an empirically determined threshold.

47. Electronic musical apparatus for enabling a performer to control the production of at least first and second musical accompaniments during a musical performance, said apparatus comprising the combination of: first memory means for storing a first plurality of music signals defining at least in part the first musical accompaniment and a second plurality of music signals defining at least in part the second musical accompaniment and for storing with respect to at least portions of said first and second accompaniments information about the musical parameters of instrumentation pattern, duration, and pitch; accompaniment selection means operative during the performance for generatng a first selection signal in response to selection of the first musical accompaniment by the performer and for generating a second selection signal in response to selection of the second musical accompaniment by the performer; harmony selection means for enabling a performer to select one harmony from a plurality of different harmonies; second memory means for storing digital instructions for processing the music signals during the performance according to the one harmony; central processor means responsive to the selected selection signal and to selection of the one harmony for reading the music signals corresponding to the selected musical accompaniment from the first memory means and for processing the music signals corresponding to the selected musical accompaniment according to said instructions to form time-spaced digital parameter signals having changing digital values which define a segment of music including a plurality of pitched accompaniment notes arranged to express the selected musical accompaniment in the one harmony; and output means for converting the changing values of the parameter signals to sound, whereby a performer of limited skill or musical knowledge can play an orchestrated accompaniment to a variety of melodies.

47. Electronic musical apparatus for enabling a performer to control the production of at least first and second musical accompaniments during a musical performance, said apparatus comprising the combination of: first memory means for storing a first plurality of music signals defining at least in part the first musical accompaniment and a second plurality of music signals defining at least in part the second musical accompaniment and for storing with respect to at least portions of said first and second accompaniments information about the musical parameters of instrumentation pattern, duration, and pitch; accompaniment selection means operative during the performance for generatng a first selection signal in response to selection of the first musical accompaniment by the performer and for generating a second selection signal in response to selection of the second musical accompaniment by the performer; harmony selection means for enabling a performer to select one harmony from a plurality of different harmonies; second memory means for storing digital instructions for processing the music signals during the performance according to the one harmony; central processor means responsive to the selected selection signal and to selection of the one harmony for reading the music signals corresponding to the selected musical accompaniment from the first memory means and for processing the music signals corresponding to the selected musical accompaniment according to said instructions to form time-spaced digital parameter signals having changing digital values which define a segment of music including a plurality of pitched accompaniment notes arranged to express the selected musical accompaniment in the one harmony; and output means for converting the changing values of the parameter signals to sound, whereby a performer of limited skill or musical knowledge can play an orchestrated accompaniment to a variety of melodies. 50. Apparatus, as claimed in claim 47, wherein the parameter signals define a first voice line and a second voice line for producing a segment of music and wherein the output means comprises: first oscillator means associated with the first voice and second oscillator means associated with the second voice for generating tone pulses at a rate determined by the parameter signals; filter means associated with the first and second oscillator means for filtering the tone signals in a manner determined by the parameter signals to produce filtered tone signals; envelope means associated with the filter means for generating an attack-decay envelope signal in response to the parameter signals; modulator means for modulating the filtered tone signals with the attack-decay envelope signal to produce an audio signal; and transducer means for converting each audio signal to sound, whereby notes sounding with different voices can be produced simultaneously in order to simulate multiple instruments.

1. A computer usable program product comprising a computer readable storage device including computer usable code for improving a future user interface (UI) design, the computer usable code comprising: computer usable code for analyzing, using a processor and a memory of a data processing system, a set of data, a data in a first subset of the set of data including (i) a description of a UI layout that includes a description of a UI element positioned in a first area of a touch-sensitive device, the first area having a first sensitivity to touch, wherein the first sensitivity is below a level of sensitivity, and (ii) a second area of the touch-sensitive device, the second area having a second sensitivity to touch, wherein the second sensitivity is at least equal to the level of sensitivity; computer usable code for extracting a first visual characteristic of the UI element, wherein a threshold number of data in the first subset include some UI element with the first visual characteristic, wherein the first visual characteristic includes at least one of a color or an animation of the UI element; computer usable code for determining, for a first area in each data in the subset, that the first visual characteristic causes a sensitivity to reduce to below the level of sensitivity; and computer usable code for constructing, responsive to the determining, an instruction for a UI design tool, the instruction causing the UI design tool to move a UI element in the future UI design to a second area and replacing use of the first visual characteristic of the UI element with a second visual characteristic in the future UI design, the second visual characteristic associated with a lower number of instances of screen rot than the first visual characteristic.

1. A computer usable program product comprising a computer readable storage device including computer usable code for improving a future user interface (UI) design, the computer usable code comprising: computer usable code for analyzing, using a processor and a memory of a data processing system, a set of data, a data in a first subset of the set of data including (i) a description of a UI layout that includes a description of a UI element positioned in a first area of a touch-sensitive device, the first area having a first sensitivity to touch, wherein the first sensitivity is below a level of sensitivity, and (ii) a second area of the touch-sensitive device, the second area having a second sensitivity to touch, wherein the second sensitivity is at least equal to the level of sensitivity; computer usable code for extracting a first visual characteristic of the UI element, wherein a threshold number of data in the first subset include some UI element with the first visual characteristic, wherein the first visual characteristic includes at least one of a color or an animation of the UI element; computer usable code for determining, for a first area in each data in the subset, that the first visual characteristic causes a sensitivity to reduce to below the level of sensitivity; and computer usable code for constructing, responsive to the determining, an instruction for a UI design tool, the instruction causing the UI design tool to move a UI element in the future UI design to a second area and replacing use of the first visual characteristic of the UI element with a second visual characteristic in the future UI design, the second visual characteristic associated with a lower number of instances of screen rot than the first visual characteristic. 2. The computer usable program product of claim 1 , further comprising: computer usable code for constructing a second instruction for the UI design tool, wherein the second instruction causes the UI element in the future UI design to be rendered at a first area and migrate to the second area over a period.

3. The method as in claim 1 , comprising an initial step of applying said change to said ontology system.

3. The method as in claim 1 , comprising an initial step of applying said change to said ontology system. 4. The method as in claim 3 , whereby one or more conditions are imposed for applying said change.

1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user.

1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user. 5. The computer-implemented method of claim 1 comprising: before the second user inputs the second suggestion, permitting the second user to view the first suggestion made by the first user.

1. A multi-function apparatus, comprising: a scan device to scan a document having a text and a barcode and to output a scan image of the document, wherein the barcode includes information of the text of the document; a barcode decoding unit to decode the barcode included in the scan image, to extract the text of the document from the barcode, and to output the extracted text; a document editing unit to include at least one of the scan image and the extracted text in another document and to produce the another document; an e-mail transmitting unit to attach the text extracted by the barcode decoding unit or the another document produced by the document editing unit to an e-mail and transmit the e-mail; and a control unit to set a scan resolution of the scan device according to one of a plurality of modes, wherein the plurality of modes include a first mode to transmit the extracted text via the e-mail without the scan image and a second mode to transmit the extracted text via the e-mail together with the scan image.

1. A multi-function apparatus, comprising: a scan device to scan a document having a text and a barcode and to output a scan image of the document, wherein the barcode includes information of the text of the document; a barcode decoding unit to decode the barcode included in the scan image, to extract the text of the document from the barcode, and to output the extracted text; a document editing unit to include at least one of the scan image and the extracted text in another document and to produce the another document; an e-mail transmitting unit to attach the text extracted by the barcode decoding unit or the another document produced by the document editing unit to an e-mail and transmit the e-mail; and a control unit to set a scan resolution of the scan device according to one of a plurality of modes, wherein the plurality of modes include a first mode to transmit the extracted text via the e-mail without the scan image and a second mode to transmit the extracted text via the e-mail together with the scan image. 3. The multi-function apparatus of claim 1 , wherein the barcode is a two-dimensional barcode recorded in the document.

1. A computer-implemented method comprising: identifying queries that each include (i) one or more first terms that are associated with a particular topic and (ii) one or more second terms, different than the one or more first terms, that are associated with a particular author; identifying web resources for which the particular author has been identified as an author; determining a quantity of selections of search results that (i) are generated in response to one or more of the queries and (ii) reference one or more of the web resources for which the particular author has been identified as an author; associating the particular author with the particular topic, as a topic-to-author association, when the quantity of selections satisfies a threshold that is associated with more than one selection; and using the topic-to-author association in ranking a search result, which references one or more of the web resources, that is generated in response to one or more subsequently received queries that includes one or more of the first terms that are associated with the particular topic.

1. A computer-implemented method comprising: identifying queries that each include (i) one or more first terms that are associated with a particular topic and (ii) one or more second terms, different than the one or more first terms, that are associated with a particular author; identifying web resources for which the particular author has been identified as an author; determining a quantity of selections of search results that (i) are generated in response to one or more of the queries and (ii) reference one or more of the web resources for which the particular author has been identified as an author; associating the particular author with the particular topic, as a topic-to-author association, when the quantity of selections satisfies a threshold that is associated with more than one selection; and using the topic-to-author association in ranking a search result, which references one or more of the web resources, that is generated in response to one or more subsequently received queries that includes one or more of the first terms that are associated with the particular topic. 3. The method of claim 1 , wherein the web resources are websites or webpages having respective associated web addresses.

17. A computer-readable data storage device comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving an image, wherein the image comprises a people tag assigned thereto by an assignor, wherein the people tag comprises first data that is indicative of an identity of a first individual that is included in the image, wherein the first data comprises a unique identifier assigned to the first individual by a service; receiving contact data pertaining to a plurality of contacts of a second individual responsive to the second individual providing identification authentication data to the service, wherein the contact data comprises data that is indicative of identities of the contacts of the second individual, wherein the first individual is a contact of the second individual, and wherein the contact data comprises the unique identifier and second data generated by the second individual to identify the first individual to the second individual; comparing the first data with the contact data, the comparing comprising determining that both the contact data and the first data comprise the unique identifier; determining that the first individual is a contact of the second individual based at least in part upon the comparing of the first data with the contact data; and causing the image to be displayed in conjunction with the second data when the second individual is logged into the service at a computing device being utilized to view the image based at least in part upon the first data comprising the unique identifier and the contact data comprising the unique identifier.

17. A computer-readable data storage device comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving an image, wherein the image comprises a people tag assigned thereto by an assignor, wherein the people tag comprises first data that is indicative of an identity of a first individual that is included in the image, wherein the first data comprises a unique identifier assigned to the first individual by a service; receiving contact data pertaining to a plurality of contacts of a second individual responsive to the second individual providing identification authentication data to the service, wherein the contact data comprises data that is indicative of identities of the contacts of the second individual, wherein the first individual is a contact of the second individual, and wherein the contact data comprises the unique identifier and second data generated by the second individual to identify the first individual to the second individual; comparing the first data with the contact data, the comparing comprising determining that both the contact data and the first data comprise the unique identifier; determining that the first individual is a contact of the second individual based at least in part upon the comparing of the first data with the contact data; and causing the image to be displayed in conjunction with the second data when the second individual is logged into the service at a computing device being utilized to view the image based at least in part upon the first data comprising the unique identifier and the contact data comprising the unique identifier. 20. The computer-readable data storage device of claim 17 comprised by a mobile telephone.

7. A method for generating a topic page for a search query on a search webpage, comprising: receiving a query at the search webpage; analyzing the query to identify a plurality of dimensions of the query, the query includes one or more keywords entered by a user to initiate a search, the one or more of the plurality of dimensions of the query identified based on at least one other dimension of the query; selecting one or more content modules, including at least one interactive advertising module, from a plurality of sources that match one or more of the plurality of dimensions, the selection of the content modules based on a weight associated with each of the plurality of dimensions used for selecting the content modules, the weight defining a ranking of the content modules, wherein the content modules selected from the plurality of sources include one or more secondary content modules, each of the secondary content modules having one or more dimensions that match the one or more of the plurality of dimensions defined in a specific content module selected for the query, the secondary content modules having a lower weight than the corresponding content modules; generating a topic page from the selected content modules, the content modules presented in an order based on the corresponding weight of the content modules, the order indicating relevancy of the content modules to the query, wherein generating of the topic page further includes, determining if a particular one of the content modules poses a conflict within the topic page; and resolving the conflict posed by the particular content module so as to enable the topic page to be successfully rendered, in response to the query.

7. A method for generating a topic page for a search query on a search webpage, comprising: receiving a query at the search webpage; analyzing the query to identify a plurality of dimensions of the query, the query includes one or more keywords entered by a user to initiate a search, the one or more of the plurality of dimensions of the query identified based on at least one other dimension of the query; selecting one or more content modules, including at least one interactive advertising module, from a plurality of sources that match one or more of the plurality of dimensions, the selection of the content modules based on a weight associated with each of the plurality of dimensions used for selecting the content modules, the weight defining a ranking of the content modules, wherein the content modules selected from the plurality of sources include one or more secondary content modules, each of the secondary content modules having one or more dimensions that match the one or more of the plurality of dimensions defined in a specific content module selected for the query, the secondary content modules having a lower weight than the corresponding content modules; generating a topic page from the selected content modules, the content modules presented in an order based on the corresponding weight of the content modules, the order indicating relevancy of the content modules to the query, wherein generating of the topic page further includes, determining if a particular one of the content modules poses a conflict within the topic page; and resolving the conflict posed by the particular content module so as to enable the topic page to be successfully rendered, in response to the query. 12. The method of claim 7 , wherein analyzing the query by identifying a plurality of dimensions further including, determining a geo location associated with the query, the geo location driving the selection of the content modules; determining a topic of the query; and identifying one or more intents for the topic, the intent defined for the query based on the geo location.

9. A computer program product comprising a non-transitory computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code stored in the non-transitory storage medium configured to receive a plurality of product feedback search parameters, wherein said plurality of product feedback search parameters pertain to at least one of a product and a group of products; computer usable program code stored in the non-transitory storage medium configured to perform a search on plurality of product feedback data sources using the product feedback search parameters to gather product feedback; computer usable program code stored in the non-transitory storage medium configured to obtain a plurality of product feedback search results applicable to the plurality of product feedback search parameters, wherein each product feedback search result comprises at least one of a rating value upon a rating scale and feedback content in a textual format; computer usable program code stored in the non-transitory storage medium configured to, for each product represented in the obtained plurality of product feedback search results, synthesize a composite rating value for each rating category of a predefined rating scale from rating values contained in product feedback search results that are applicable to the product, wherein the computer usable code to synthesize further comprises: computer usable program code stored in the non-transitory storage medium configured to convert the rating value for each product feedback search result to an equivalent rating value with respect to the predefined rating scale; computer usable program code stored in the non-transitory storage medium configured to assign each product feedback search result to a rating category of the predefined rating scale, wherein the converted rating value of a product feedback search result falls within a rating value range defined for the rating category to which it is assigned; and computer usable program code stored in the non-transitory storage medium configured to express a quantity of product feedback search results assigned to each rating category as a percentage of a total quantity of product feedback search results that are applicable to the product; computer usable program code stored in the non-transitory storage medium configured to, for each product represented in the obtained plurality of product feedback search results, analyze the plurality of product feedback search results for at least one analytic parameter, wherein each analytic parameter represents a commonality among a subset of the product feedback search results that are applicable to the product, wherein said analysis utilizes natural language processing techniques; and computer usable program code stored in the non-transitory storage medium configured to present the plurality of product feedback search results, composite rating values, and the at least one analytic parameter in an organized manner within a user interface, wherein the at least one analytic parameter presented provides a context for the corresponding composite rating value.

9. A computer program product comprising a non-transitory computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code stored in the non-transitory storage medium configured to receive a plurality of product feedback search parameters, wherein said plurality of product feedback search parameters pertain to at least one of a product and a group of products; computer usable program code stored in the non-transitory storage medium configured to perform a search on plurality of product feedback data sources using the product feedback search parameters to gather product feedback; computer usable program code stored in the non-transitory storage medium configured to obtain a plurality of product feedback search results applicable to the plurality of product feedback search parameters, wherein each product feedback search result comprises at least one of a rating value upon a rating scale and feedback content in a textual format; computer usable program code stored in the non-transitory storage medium configured to, for each product represented in the obtained plurality of product feedback search results, synthesize a composite rating value for each rating category of a predefined rating scale from rating values contained in product feedback search results that are applicable to the product, wherein the computer usable code to synthesize further comprises: computer usable program code stored in the non-transitory storage medium configured to convert the rating value for each product feedback search result to an equivalent rating value with respect to the predefined rating scale; computer usable program code stored in the non-transitory storage medium configured to assign each product feedback search result to a rating category of the predefined rating scale, wherein the converted rating value of a product feedback search result falls within a rating value range defined for the rating category to which it is assigned; and computer usable program code stored in the non-transitory storage medium configured to express a quantity of product feedback search results assigned to each rating category as a percentage of a total quantity of product feedback search results that are applicable to the product; computer usable program code stored in the non-transitory storage medium configured to, for each product represented in the obtained plurality of product feedback search results, analyze the plurality of product feedback search results for at least one analytic parameter, wherein each analytic parameter represents a commonality among a subset of the product feedback search results that are applicable to the product, wherein said analysis utilizes natural language processing techniques; and computer usable program code stored in the non-transitory storage medium configured to present the plurality of product feedback search results, composite rating values, and the at least one analytic parameter in an organized manner within a user interface, wherein the at least one analytic parameter presented provides a context for the corresponding composite rating value. 12. The computer program product of claim 9 , wherein the analyzing of the plurality of product feedback search results further comprises: computer usable program code stored in the non-transitory storage medium configured to, upon completion of the analysis of a product feedback search result, store the analyzed product feedback search result in an analytic search results library, wherein the analytic search results library is a knowledgebase of product feedback search results previously processed.

15. The system of claim 14 , wherein the instructions cause the one or more data processing apparatus to perform operations comprising: receiving a second request for a second type of performance measure; determining that using the pre-aggregated dataset to determine a value for the second type of performance measure lowers a latency for responding to the second request relative to a latency for responding to the second request using the dataset to determine the value for the second type of performance measure; and increasing the benefit score for the pre-aggregated dataset in response to determining that using the pre-aggregated dataset to determine the value for the second type of performance measure lowers the latency for responding to the second request.

15. The system of claim 14 , wherein the instructions cause the one or more data processing apparatus to perform operations comprising: receiving a second request for a second type of performance measure; determining that using the pre-aggregated dataset to determine a value for the second type of performance measure lowers a latency for responding to the second request relative to a latency for responding to the second request using the dataset to determine the value for the second type of performance measure; and increasing the benefit score for the pre-aggregated dataset in response to determining that using the pre-aggregated dataset to determine the value for the second type of performance measure lowers the latency for responding to the second request. 16. The system of claim 15 , wherein determining that the benefit score meets the threshold value comprises determining that the increased benefit score meets the threshold value.

1. A method for sending and receiving emails using international multilingual mailboxes, comprising the steps of: 1) setting an X-alternate-address field in the header of an email message in an international multilingual mailbox to record a substitute English email address corresponding to the international multilingual mailbox; and setting an X-address-language field in the header to set a predetermined language to describe email sender's email address; 2) before sending an email generated by a sending terminal that supports international multilingual mailbox, checking whether the receiving terminal of the email supports international multilingual mailbox; 3) if the receiving terminal supports emails of international multilingual mailbox, directly sending the email with the field of X-alternate-address in the email header; extracting the X-address-language field from the header of the email by the receiving terminal, determining the corresponding predetermined language, and sending a prompt in English or in the predetermined language to the email recipient; and 4) if the receiving terminal does not support emails of international multilingual mailbox, sending the email according to the English email address in the X-alternate-address field; and receiving the email by the receiving terminal.

1. A method for sending and receiving emails using international multilingual mailboxes, comprising the steps of: 1) setting an X-alternate-address field in the header of an email message in an international multilingual mailbox to record a substitute English email address corresponding to the international multilingual mailbox; and setting an X-address-language field in the header to set a predetermined language to describe email sender's email address; 2) before sending an email generated by a sending terminal that supports international multilingual mailbox, checking whether the receiving terminal of the email supports international multilingual mailbox; 3) if the receiving terminal supports emails of international multilingual mailbox, directly sending the email with the field of X-alternate-address in the email header; extracting the X-address-language field from the header of the email by the receiving terminal, determining the corresponding predetermined language, and sending a prompt in English or in the predetermined language to the email recipient; and 4) if the receiving terminal does not support emails of international multilingual mailbox, sending the email according to the English email address in the X-alternate-address field; and receiving the email by the receiving terminal. 5. The method according to claim 1 , wherein when the email recipient replies to the email, the method further comprising: extracting the X-alternate-address field from the header to obtain reply email's receiving address, by an email server at the receiving terminal that supports emails of international multilingual mailbox.

1. A method for configuring an audio channel with a processor, the method comprising: generating a confidence metric indicative of at least one control cue in a telecommunication audio feed, wherein generating the confidence metric comprises: analyzing the at least one control cue to determine a cue type; assigning a confidence metric value for the at least one control cue based on the cue type, wherein the cue type comprises both explicit speech to perform an action and muffled voice having a lower amplitude than the average amplitude of other portions of the audio feed; comparing the confidence metric value to a predetermined threshold value associated with the cue type; updating a context history with the cue type and the confidence metric value; and configuring an input of the audio channel based on the confidence metric and the context history.

1. A method for configuring an audio channel with a processor, the method comprising: generating a confidence metric indicative of at least one control cue in a telecommunication audio feed, wherein generating the confidence metric comprises: analyzing the at least one control cue to determine a cue type; assigning a confidence metric value for the at least one control cue based on the cue type, wherein the cue type comprises both explicit speech to perform an action and muffled voice having a lower amplitude than the average amplitude of other portions of the audio feed; comparing the confidence metric value to a predetermined threshold value associated with the cue type; updating a context history with the cue type and the confidence metric value; and configuring an input of the audio channel based on the confidence metric and the context history. 13. The method of claim 1 , further comprising outputting an audio cue indicative that the processor has configured the input to the audio channel.

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

1. A method for transforming narrative content into structured output that defines where individual information resides within the output, the method comprising the steps of: receiving narrative content; scanning the narrative content using a natural language processing engine to identify at least one section and at least one clinical assertion within that section; extracting information from the narrative content, wherein the extracted information includes clinical assertions and contextual information; and identifying one or more clinical assertion elements which define a clinical assertion and assigning a clinical assertion element label to at least one clinical assertion element of the one or more clinical assertion elements based on a clinical model, wherein the label assigned to the at least one clinical assertion element is selected from a predetermined list, wherein the list is predetermined based on a clinical assertion type. 8. The method of claim 1 , wherein the at least one clinical assertion elements include section elements, and wherein a section label is assigned to a first section element of the section elements, the section label describing at least one of title, text, and code.

17. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor, cause the at least one processor to: capture behavioral data for a plurality of users with respect to a plurality of terms; obtain a rule set for stemming in a language corresponding to the plurality of terms; obtain a word to be stemmed; in response to determining that only one rule of the rule set is to be used to stem the obtained word, stemming the obtained word using only one rule; or in response to determining that more than one rule of the rule set is to be used in stemming the obtained word: determine a set of forms of the obtained word; determine an output set of forms corresponding to the set of forms, wherein each rule of the more than one rule corresponds to one of the forms in the output set of forms, determine, based at least in part upon the captured behavioral data, a relative measurement value of each form in the set of output forms, and select, based at least in part upon the relative measurement values, at least one form in the output set of forms to be used as a stem for the obtained word.

17. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor, cause the at least one processor to: capture behavioral data for a plurality of users with respect to a plurality of terms; obtain a rule set for stemming in a language corresponding to the plurality of terms; obtain a word to be stemmed; in response to determining that only one rule of the rule set is to be used to stem the obtained word, stemming the obtained word using only one rule; or in response to determining that more than one rule of the rule set is to be used in stemming the obtained word: determine a set of forms of the obtained word; determine an output set of forms corresponding to the set of forms, wherein each rule of the more than one rule corresponds to one of the forms in the output set of forms, determine, based at least in part upon the captured behavioral data, a relative measurement value of each form in the set of output forms, and select, based at least in part upon the relative measurement values, at least one form in the output set of forms to be used as a stem for the obtained word. 20. The non-transitory computer-readable storage medium of claim 17 , wherein each of the relative measure values corresponds to an indication of a frequency of use of one of the forms in the output set based in part on the captured behavioral data.

11. A method for processing an XML document, comprising: parsing an XML document and generating a stream of discrete pieces of the XML document, wherein the XML document is represented using a hierarchical data structure, and each said discrete piece of the document is represented by one or more nodes in the hierarchical data structure; accepting a discrete piece of the XML document from the stream of discrete pieces from the streaming parser at one time; keeping in memory only said discrete piece of the XML document from the stream at said time; maintaining a plurality of contexts associated with the XML document in a context data structure, wherein each context of the plurality of contexts contains a node in the hierarchical data structure and a position of the node relative to a context node; mapping each context of the plurality of contexts to the stream of discrete pieces of the XML document and performing matching against each context of the plurality of contexts on said discrete piece of the XML document from the stream; passing the particular discrete piece of the XML document to a user object for handling when the particular discrete piece of the XML document is a matched discrete piece of the XML document.

11. A method for processing an XML document, comprising: parsing an XML document and generating a stream of discrete pieces of the XML document, wherein the XML document is represented using a hierarchical data structure, and each said discrete piece of the document is represented by one or more nodes in the hierarchical data structure; accepting a discrete piece of the XML document from the stream of discrete pieces from the streaming parser at one time; keeping in memory only said discrete piece of the XML document from the stream at said time; maintaining a plurality of contexts associated with the XML document in a context data structure, wherein each context of the plurality of contexts contains a node in the hierarchical data structure and a position of the node relative to a context node; mapping each context of the plurality of contexts to the stream of discrete pieces of the XML document and performing matching against each context of the plurality of contexts on said discrete piece of the XML document from the stream; passing the particular discrete piece of the XML document to a user object for handling when the particular discrete piece of the XML document is a matched discrete piece of the XML document. 16. The method according to claim 11 , further comprising: keeping only a portion of the XML document in memory at any given time.

1. A method for coreference resolution comprising: receiving a set of document clusters, each cluster in the set of document clusters comprising a set of text documents; identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; for each of the candidate named entities, generating an event profile, the event profile comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; with a processor, computing a similarity between a pair of the candidate named entities based on their respective event profiles; and providing a decision for merging of the candidate named entities into a common real named entity, based on the computed similarity.

1. A method for coreference resolution comprising: receiving a set of document clusters, each cluster in the set of document clusters comprising a set of text documents; identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; for each of the candidate named entities, generating an event profile, the event profile comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; with a processor, computing a similarity between a pair of the candidate named entities based on their respective event profiles; and providing a decision for merging of the candidate named entities into a common real named entity, based on the computed similarity. 20. A system comprising memory which stores instructions for performing the method of claim 1 and a processor in communication with the memory for executing the instructions.

1. A computer implemented document processing method comprising: accessing a plurality of initial documents; initially processing the initial documents to provide a plurality of initial representations for respective ones of the initial documents, wherein the initial representations include a plurality of associations of the initial documents with a plurality of features which occur in respective ones of the initial documents; using the initial representations, initially identifying a plurality of associations of the initial documents with respect to one another; after the initially identifying, accessing a plurality of subsequent documents; subsequently processing the subsequent documents to provide a plurality of subsequent representations for respective ones of the subsequent documents, wherein the subsequent representations include a plurality of associations of the subsequent documents with a plurality of features which occur in respective ones of the subsequent documents; and using the initial and subsequent representations, subsequently identifying a plurality of associations of the initial documents with respect to the subsequent documents.

1. A computer implemented document processing method comprising: accessing a plurality of initial documents; initially processing the initial documents to provide a plurality of initial representations for respective ones of the initial documents, wherein the initial representations include a plurality of associations of the initial documents with a plurality of features which occur in respective ones of the initial documents; using the initial representations, initially identifying a plurality of associations of the initial documents with respect to one another; after the initially identifying, accessing a plurality of subsequent documents; subsequently processing the subsequent documents to provide a plurality of subsequent representations for respective ones of the subsequent documents, wherein the subsequent representations include a plurality of associations of the subsequent documents with a plurality of features which occur in respective ones of the subsequent documents; and using the initial and subsequent representations, subsequently identifying a plurality of associations of the initial documents with respect to the subsequent documents. 14. The method of claim 1 wherein the initially and subsequently processings individually comprise identifying the features present in respective ones of the initial documents and the subsequent documents.

1. A computer-implemented method comprising: storing unstructured data in an unstructured data store, wherein at least some of the unstructured data remains unstructured in the unstructured data store; receiving, at a query converter, a structured query in a structured query language from an application; identifying a field in data stored in the unstructured data store, based on an extraction rule that specifies where to find a subportion of text within a segment of the data; generating, by the query converter, a second query in a second query language associated with the unstructured data store, based on the structured query; causing execution of the second query against the unstructured data stored in the unstructured data store; receiving a result of execution of the second query against the unstructured data stored in the unstructured data store, the result including a value for the field; and causing an indication of the result to be provided to the application for output to a user.

1. A computer-implemented method comprising: storing unstructured data in an unstructured data store, wherein at least some of the unstructured data remains unstructured in the unstructured data store; receiving, at a query converter, a structured query in a structured query language from an application; identifying a field in data stored in the unstructured data store, based on an extraction rule that specifies where to find a subportion of text within a segment of the data; generating, by the query converter, a second query in a second query language associated with the unstructured data store, based on the structured query; causing execution of the second query against the unstructured data stored in the unstructured data store; receiving a result of execution of the second query against the unstructured data stored in the unstructured data store, the result including a value for the field; and causing an indication of the result to be provided to the application for output to a user. 9. A computer-implemented method as recited in claim 1 , further comprising: applying a schema to the data in the unstructured data store after storing data in the unstructured data store, to impose a structure on the unstructured data.

10. A system comprising a computer system comprising a processor, memory, and storage, the system being configured to: receive a text search query, the query comprising one or more query words; generate, for each query word in the query, a set of one or more anchor segments from searching metadata corresponding to a plurality of speech recognition processed audio files, the metadata including representations of one or more words detected in the audio files, wherein, for each detected word, the metadata includes a reference to each audio file in which the word was detected, a temporal location of the detected word in the audio file, and a confidence measure for the word as detected within the audio file, where each anchor segment includes a query word, an identifier for an audio file, and a temporal location of the query word within the audio file, where generating anchor segments includes, for each query word, the computer system: determining if the query word is included in a vocabulary of a learning model for a speech recognizer engine of the computer system; when the query word is in the vocabulary, searching the metadata to identify one or more high confidence anchor segments corresponding to the query word; and when the query word is not in the vocabulary: generating a search list of one or more sub-words of the query word, searching the metadata to identify one or more audio files containing at least one of the one or more sub-words to identify one or more anchor segments corresponding to one or more of the sub-words; post-process the one or more anchor segments, the post-process comprising: expanding the one or more anchor segments; sorting the one or more anchor segments; and merging overlapping ones of the one or more anchor segments; and perform speech recognition on the post-processed one or more expanded anchor segments for instances of at least one of the one or more query words using a constrained grammar.

10. A system comprising a computer system comprising a processor, memory, and storage, the system being configured to: receive a text search query, the query comprising one or more query words; generate, for each query word in the query, a set of one or more anchor segments from searching metadata corresponding to a plurality of speech recognition processed audio files, the metadata including representations of one or more words detected in the audio files, wherein, for each detected word, the metadata includes a reference to each audio file in which the word was detected, a temporal location of the detected word in the audio file, and a confidence measure for the word as detected within the audio file, where each anchor segment includes a query word, an identifier for an audio file, and a temporal location of the query word within the audio file, where generating anchor segments includes, for each query word, the computer system: determining if the query word is included in a vocabulary of a learning model for a speech recognizer engine of the computer system; when the query word is in the vocabulary, searching the metadata to identify one or more high confidence anchor segments corresponding to the query word; and when the query word is not in the vocabulary: generating a search list of one or more sub-words of the query word, searching the metadata to identify one or more audio files containing at least one of the one or more sub-words to identify one or more anchor segments corresponding to one or more of the sub-words; post-process the one or more anchor segments, the post-process comprising: expanding the one or more anchor segments; sorting the one or more anchor segments; and merging overlapping ones of the one or more anchor segments; and perform speech recognition on the post-processed one or more expanded anchor segments for instances of at least one of the one or more query words using a constrained grammar. 17. The system of claim 10 , wherein the system is further configured to expand the one or more anchor segments by: for each query word in the query: counting a first number of characters in the query before the query word and a second number of characters after the query word; multiplying the first number of characters by an average character duration to obtain a first expansion amount; and multiplying the second number of characters by the average character duration to obtain a second expansion amount; and for each anchor segment, each anchor segment being identified by an anchor word, a start time, and an end time: subtracting the first expansion amount and a first constant expansion duration from the start time; and adding the second expansion amount and a second constant expansion duration to the end time.

1. A method for automatic speech recognition, the method comprising: determining for an input signal a plurality of scores representative of certainties that the input signal is associated with corresponding states of a speech recognition model; using the speech recognition model and the determined scores to compute an average signal; computing, via a processor device executing instructions, a difference value representative of a difference between the input signal and the average signal; and processing, via the processor device, the input signal in accordance with the difference value; wherein computing the average signal comprises: identifying a given score from the plurality of scores; selecting from the plurality of scores a set of scores whose corresponding values are within a predetermined threshold from a value of the given score; and performing an averaging operation on observation mean vectors of observation densities associated with the selected plurality of scores to obtain the average signal.

1. A method for automatic speech recognition, the method comprising: determining for an input signal a plurality of scores representative of certainties that the input signal is associated with corresponding states of a speech recognition model; using the speech recognition model and the determined scores to compute an average signal; computing, via a processor device executing instructions, a difference value representative of a difference between the input signal and the average signal; and processing, via the processor device, the input signal in accordance with the difference value; wherein computing the average signal comprises: identifying a given score from the plurality of scores; selecting from the plurality of scores a set of scores whose corresponding values are within a predetermined threshold from a value of the given score; and performing an averaging operation on observation mean vectors of observation densities associated with the selected plurality of scores to obtain the average signal. 14. The method as in claim 1 further comprising: segmenting the input signal into frames; computing a respective coefficient for each of the frames; normalizing the coefficients associated with the frames; presenting the normalized coefficients to a speech recognition decoder; and computing the plurality of scores using the normalized coefficients.

9. At a computer system, the computer system including a processor and system memory, a method for providing technical assistance services for a developing software product, the developing software product being developed by a plurality of different product development groups, one or more other software developers developing other software products that are to depend on at least a portion of the developing software product, the technical assistance service allocated to a software developer to assist the software developer in developing a dependent software product, the method comprising: an act of a service allocation module receiving a service request for technical assistance services from a software developer that is developing another software product that is depend on at least a portion of the functionality of the developing software product, the service allocation module controlling the allocation of service requests to a plurality of different service providers, the developing software product having a functionality defined by the plurality of different development groups, changes to the functionality of the developing software product being determined by at least one group of the plurality of different development groups, such that changes to the functionality of the developing software product is determined independent of the one or more other software developers developing other software products that are to depend on at least a portion of the developing software product and wherein changes to the functionality of the developing software product cause changes in the technical assistance; an act of accessing request allocation criteria for the software developer, at least one request allocation criterion included in the service request, at least one request allocation criterion maintained at the service allocation module; an act of the processor identifying an optimum service provider, from among the plurality of service providers, for servicing the service request by matching the accessed request allocation criteria and service provider characteristics to provide a match in accordance with a routing algorithm; an act of sending the service request to the optimum service provider; an act of receiving an answer to the to the service request from the identified service provider, the answer is based at least in part on the service provider's expertise with respect to the at least one portion of the developing software product's functionality that the other software product is to depend on; and an act of at least notifying the software developer of the existence of the received answer.

9. At a computer system, the computer system including a processor and system memory, a method for providing technical assistance services for a developing software product, the developing software product being developed by a plurality of different product development groups, one or more other software developers developing other software products that are to depend on at least a portion of the developing software product, the technical assistance service allocated to a software developer to assist the software developer in developing a dependent software product, the method comprising: an act of a service allocation module receiving a service request for technical assistance services from a software developer that is developing another software product that is depend on at least a portion of the functionality of the developing software product, the service allocation module controlling the allocation of service requests to a plurality of different service providers, the developing software product having a functionality defined by the plurality of different development groups, changes to the functionality of the developing software product being determined by at least one group of the plurality of different development groups, such that changes to the functionality of the developing software product is determined independent of the one or more other software developers developing other software products that are to depend on at least a portion of the developing software product and wherein changes to the functionality of the developing software product cause changes in the technical assistance; an act of accessing request allocation criteria for the software developer, at least one request allocation criterion included in the service request, at least one request allocation criterion maintained at the service allocation module; an act of the processor identifying an optimum service provider, from among the plurality of service providers, for servicing the service request by matching the accessed request allocation criteria and service provider characteristics to provide a match in accordance with a routing algorithm; an act of sending the service request to the optimum service provider; an act of receiving an answer to the to the service request from the identified service provider, the answer is based at least in part on the service provider's expertise with respect to the at least one portion of the developing software product's functionality that the other software product is to depend on; and an act of at least notifying the software developer of the existence of the received answer. 13. The method as recited in claim 9 , wherein the act of identifying an optimum service provider that is to respond to the service request an act of identifying a service provider based on routing criteria included in a previously received service policy for the developing software product.

1. A non-transitory computer-readable medium having instructions stored thereon that, responsive to being executed by a client device, cause the client device to perform operations comprising: rendering an interface for a resource application of a client device that includes a display area configured to present a resource; presenting the resource in the display area; exposing an annotation portion in the interface that is configured to enable input of annotations for the presented resource in accordance with a location setting of the client device associated with a user profile, the presented resource unmodified by the annotations, wherein the user profile is one of at least two user profiles associated with a user of the client device, and wherein each of the at least two user profiles is associated with a different location of the client device; receiving an annotation input via the annotation portion; and communicating with an annotation server, separate from the client device, to store the annotation for the presented resource at predetermined times in response to the receiving the annotation.

1. A non-transitory computer-readable medium having instructions stored thereon that, responsive to being executed by a client device, cause the client device to perform operations comprising: rendering an interface for a resource application of a client device that includes a display area configured to present a resource; presenting the resource in the display area; exposing an annotation portion in the interface that is configured to enable input of annotations for the presented resource in accordance with a location setting of the client device associated with a user profile, the presented resource unmodified by the annotations, wherein the user profile is one of at least two user profiles associated with a user of the client device, and wherein each of the at least two user profiles is associated with a different location of the client device; receiving an annotation input via the annotation portion; and communicating with an annotation server, separate from the client device, to store the annotation for the presented resource at predetermined times in response to the receiving the annotation. 8. The non-transitory computer readable medium of claim 1 , having further instructions stored thereon that, responsive to being executed by the client device, cause the client device to perform operations comprising: detecting navigation of the resource application to obtain another resource; and in response to the detecting, independent of an affirmative user selection, further communicating with the annotation server to store the received annotation.

11. A method of operating a real-time validation tool embodied as software, the method comprising the steps of: extrapolating a timeline of an application as it is being built which provides interactive content that includes graphics to be rendered in a graphics plane when executing, the application comprising at least XML code, the timeline comprising an effect of the code on a system parameter over a lifetime of the application, the system parameter including pixel buffer usage; providing a user interface that is arranged for i) displaying the timeline and the pixel buffer usage and ii) displaying an editing window that displays the XML code, and iii) accepting edits to the code; and receiving edits from a user through the user interface to set one or more XPath queries in the code to true to enable evaluation of the effect on the system parameter as the application is being built.

11. A method of operating a real-time validation tool embodied as software, the method comprising the steps of: extrapolating a timeline of an application as it is being built which provides interactive content that includes graphics to be rendered in a graphics plane when executing, the application comprising at least XML code, the timeline comprising an effect of the code on a system parameter over a lifetime of the application, the system parameter including pixel buffer usage; providing a user interface that is arranged for i) displaying the timeline and the pixel buffer usage and ii) displaying an editing window that displays the XML code, and iii) accepting edits to the code; and receiving edits from a user through the user interface to set one or more XPath queries in the code to true to enable evaluation of the effect on the system parameter as the application is being built. 12. The method of claim 11 in which the system parameter comprises pixel buffer level.

1. A method by an information processing system, the method comprising: electronically communicating with at least one external information processing system; obtaining, based on electronically communicating with the at least one external information processing system, an object and a topical domain associated with the object from the at least one external information processing system, wherein the object comprises at least one term; and for at least one information source in a plurality of information sources coupled together in a pipelined sequence, electronically processing the object as follows analyzing the information source based on the at least one term and the topical domain; determining, based on the analysing, if the object is one of ambiguous and unambiguous; in response to determining that the object is ambiguous, further determining that all instances of the object are ambiguous based on the object being ambiguous, and halting the analysis of any subsequent information source in the plurality of information sources, and outputting an indication to a display coupled to an information processing system that the object is ambiguous; and in response to determining that the object fails to be ambiguous, determining if a subsequent information source exists in the plurality of information sources; in response to determining that a subsequent information source exists, passing the processing of the object to the subsequent information source; and in response to determining that a subsequent information source fails to exist, outputting an indication to the display that all instances of the object are unambiguous.

1. A method by an information processing system, the method comprising: electronically communicating with at least one external information processing system; obtaining, based on electronically communicating with the at least one external information processing system, an object and a topical domain associated with the object from the at least one external information processing system, wherein the object comprises at least one term; and for at least one information source in a plurality of information sources coupled together in a pipelined sequence, electronically processing the object as follows analyzing the information source based on the at least one term and the topical domain; determining, based on the analysing, if the object is one of ambiguous and unambiguous; in response to determining that the object is ambiguous, further determining that all instances of the object are ambiguous based on the object being ambiguous, and halting the analysis of any subsequent information source in the plurality of information sources, and outputting an indication to a display coupled to an information processing system that the object is ambiguous; and in response to determining that the object fails to be ambiguous, determining if a subsequent information source exists in the plurality of information sources; in response to determining that a subsequent information source exists, passing the processing of the object to the subsequent information source; and in response to determining that a subsequent information source fails to exist, outputting an indication to the display that all instances of the object are unambiguous. 2. The method of claim 1 , wherein analyzing the at least one information source comprises: analyzing, based on the at least one term and the topical domain, a set of n-grams generated from at least one text corpus; generating, based on the analyzing, a count of a number of times the at least one term appears in the text corpus; determining if the count is greater than a threshold, wherein determining if the object is one of ambiguous and unambiguous further comprises storing the indication that the object is ambiguous in response to determining that the count is greater than the threshold, and storing the indication that the object is unambiguous in response to determining that the count is less than the threshold.

7. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving, via an interactive voice recognition system, a user utterance and converting the user utterance to text; generating multiple intents based on the text; establishing, via the interactive voice recognition system, a confidence score for each intent in the multiple intents, wherein the confidence score for each intent is based on how much training data corresponding to the each intent was used to train a spoken language understanding module, where more training data corresponds to a higher confidence; when only a single intent in the multiple intents has a confidence score above a threshold: identifying a plurality of call types associated with the multiple intents; and applying predefined precedence rules to respond to only a single call type in the plurality of call types, the single call type associated with the single intent; and when multiple intents have confidence scores above the threshold: identifying a first intent and a second intent based on the confidence scores for the multiple intents, wherein the first intent and the second intent have highest two confidence scores in the multiple intents; and disambiguating the first intent and the second intent by presenting a disambiguation sub-dialog, via the interactive voice recognition system, wherein a user is offered a choice of which intent to process first, wherein the user is first presented with one of the first intent and the second intent having a lowest confidence score between the first intent and the second intent.

7. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving, via an interactive voice recognition system, a user utterance and converting the user utterance to text; generating multiple intents based on the text; establishing, via the interactive voice recognition system, a confidence score for each intent in the multiple intents, wherein the confidence score for each intent is based on how much training data corresponding to the each intent was used to train a spoken language understanding module, where more training data corresponds to a higher confidence; when only a single intent in the multiple intents has a confidence score above a threshold: identifying a plurality of call types associated with the multiple intents; and applying predefined precedence rules to respond to only a single call type in the plurality of call types, the single call type associated with the single intent; and when multiple intents have confidence scores above the threshold: identifying a first intent and a second intent based on the confidence scores for the multiple intents, wherein the first intent and the second intent have highest two confidence scores in the multiple intents; and disambiguating the first intent and the second intent by presenting a disambiguation sub-dialog, via the interactive voice recognition system, wherein a user is offered a choice of which intent to process first, wherein the user is first presented with one of the first intent and the second intent having a lowest confidence score between the first intent and the second intent. 8. The computer-readable storage device of claim 7 , wherein the disambiguation sub-dialog presents one of the first intent and second intent having a highest confidence score between the first intent and the second intent last.

9. A handheld electronic device comprising: a processor unit comprising a processor, an input apparatus, an output apparatus, and a memory having a routine stored therein, the processor unit being structured to: detect of a number of input member actuations corresponding with an ambiguous input; setting a first threshold, said first threshold having a value of at least two; selecting a second threshold; and only when said number of input member actuations exceeds the first threshold and a quantity of predicted language objects corresponding with said ambiguous input is less than the second threshold generate, for output, based on the quantity of predicted language objects, a number of prefix objects corresponding to said ambiguous input and a number of the predicted language objects corresponding to said ambiguous input, each predicted language object comprising a prefix object portion and a completion portion; and provide at a text input location an output comprising a prefix object and a completion portion of a first predicted language object.

9. A handheld electronic device comprising: a processor unit comprising a processor, an input apparatus, an output apparatus, and a memory having a routine stored therein, the processor unit being structured to: detect of a number of input member actuations corresponding with an ambiguous input; setting a first threshold, said first threshold having a value of at least two; selecting a second threshold; and only when said number of input member actuations exceeds the first threshold and a quantity of predicted language objects corresponding with said ambiguous input is less than the second threshold generate, for output, based on the quantity of predicted language objects, a number of prefix objects corresponding to said ambiguous input and a number of the predicted language objects corresponding to said ambiguous input, each predicted language object comprising a prefix object portion and a completion portion; and provide at a text input location an output comprising a prefix object and a completion portion of a first predicted language object. 10. The handheld electronic device of claim 9 wherein said processor unit is further structured to: provide at a variant component location an output comprising at least some of said prefix objects; detect a selection of one of said at least some of said prefix objects; and responsive to said selection, remove from said text input location the completion portion of said first predicted language object.