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9. A non-transitory computer readable storage medium storing one or more programs to be executed by a computer system, the one or more programs comprising: instructions for receiving a search query from a user; instructions for identifying a list of search results associated with the search query, wherein each search result has an initial position in the list; instructions for identifying a set of user-preferred search results that comprises search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times; instructions for identifying in the list of search results, one or more search results, each of which is associated with a respective user-preferred search result; instructions for reordering the list of search results by moving each of the identified search results from its initial position by a non-zero offset, wherein the offset is a variable that is a function of a popularity metric associated with each of the identified search results and wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and instructions for providing the reordered list of search results to the user.

9. A non-transitory computer readable storage medium storing one or more programs to be executed by a computer system, the one or more programs comprising: instructions for receiving a search query from a user; instructions for identifying a list of search results associated with the search query, wherein each search result has an initial position in the list; instructions for identifying a set of user-preferred search results that comprises search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times; instructions for identifying in the list of search results, one or more search results, each of which is associated with a respective user-preferred search result; instructions for reordering the list of search results by moving each of the identified search results from its initial position by a non-zero offset, wherein the offset is a variable that is a function of a popularity metric associated with each of the identified search results and wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and instructions for providing the reordered list of search results to the user. 11. The computer readable storage medium of claim 9 , wherein the predefined minimum number of times is a positive integer greater than 1.

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

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

1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by a user for identifying desired content items; in response to the input entered by the user, presenting a subset of content items; receiving selection actions of selected content items of the subset from the user; learning preferred descriptive terms of the user by analyzing descriptive terms associated with the selected content items and by analyzing the date, day, and time of the selection actions and the descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items, wherein similarity of the similar content items is determined by comparing the descriptive terms associated with the selected content items with a previously selected content item, and wherein the periodicity indicates an amount of time between the selection actions of the similar content items relative to a reference point; associating the periodicity with the preferred descriptive terms associated with the similar content items; associating the preferred descriptive terms with the user; determining a measurement collection having measurements associated with the preferred descriptive terms, wherein the measurements represent relative preferences of the user for the preferred descriptive terms, wherein the measurement collection includes groups of the preferred descriptive terms, wherein the relative preferences of the user for the preferred descriptive terms in a particular group are treated as equal and the groups differentiate the relative preferences of the user for the preferred descriptive terms between the groups, and wherein a preferred descriptive term is included in the particular group at least in part based on at least one of (i) smoothing relatively smaller probability weights associated with less commonly expressed preferences of the relative preferences and (ii) aging preferences of the relative preferences of relative preferences captured in a relatively more distant past, and based further on bounding a range of values of the particular group using a relevance scale factor; and in response to receiving subsequent input entered by the user, selecting and ordering a collection of content items by promoting rankings of content items of the collection of content items associated with the preferred descriptive terms of the user according to differentiation provided by the measurement collection and further based on promoting rankings of those content items of the collection of content items associated with the preferred descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent input; wherein at least one of the input and the subsequent input are entered by the user on an input constrained device.

1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by a user for identifying desired content items; in response to the input entered by the user, presenting a subset of content items; receiving selection actions of selected content items of the subset from the user; learning preferred descriptive terms of the user by analyzing descriptive terms associated with the selected content items and by analyzing the date, day, and time of the selection actions and the descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items, wherein similarity of the similar content items is determined by comparing the descriptive terms associated with the selected content items with a previously selected content item, and wherein the periodicity indicates an amount of time between the selection actions of the similar content items relative to a reference point; associating the periodicity with the preferred descriptive terms associated with the similar content items; associating the preferred descriptive terms with the user; determining a measurement collection having measurements associated with the preferred descriptive terms, wherein the measurements represent relative preferences of the user for the preferred descriptive terms, wherein the measurement collection includes groups of the preferred descriptive terms, wherein the relative preferences of the user for the preferred descriptive terms in a particular group are treated as equal and the groups differentiate the relative preferences of the user for the preferred descriptive terms between the groups, and wherein a preferred descriptive term is included in the particular group at least in part based on at least one of (i) smoothing relatively smaller probability weights associated with less commonly expressed preferences of the relative preferences and (ii) aging preferences of the relative preferences of relative preferences captured in a relatively more distant past, and based further on bounding a range of values of the particular group using a relevance scale factor; and in response to receiving subsequent input entered by the user, selecting and ordering a collection of content items by promoting rankings of content items of the collection of content items associated with the preferred descriptive terms of the user according to differentiation provided by the measurement collection and further based on promoting rankings of those content items of the collection of content items associated with the preferred descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent input; wherein at least one of the input and the subsequent input are entered by the user on an input constrained device. 20. The method of claim 1 , wherein the measurement collection is stored on a user client device and selecting and ordering the collection of content items includes selecting and ordering the content items of the collection of content items stored on the client device.

9. A computer-implemented method for filtering electronic content, the method comprising the following operations performed by at least one processor: storing, in a database, user behavior data received from a plurality of client computers and related to a plurality of modalities, wherein at least one of the plurality of modalities comprises one or more web pages of a content publisher; identifying one or more client-side events generated by one or more user interactions with the one or more web pages of the content publisher; storing user behavior data in the database, the user behavior data being generated based on the one or more identified client-side events and associated with the one or more web pages; identifying, using one or more machine learning processes, key passages of electronic content from at least the one or more web pages based on the user behavior data received from the plurality of client computers, the electronic content comprising electronic text and at least one of the machine learning processes being trained to reject invalid electronic content; ranking the identified key passages, wherein ranking the identified key passages comprises determining a ratio of user interactions with a key passage within the electronic text to total views of the electronic text; and publishing the highest ranked identified key passages from the one or more web pages to the application associated with the content publisher.

9. A computer-implemented method for filtering electronic content, the method comprising the following operations performed by at least one processor: storing, in a database, user behavior data received from a plurality of client computers and related to a plurality of modalities, wherein at least one of the plurality of modalities comprises one or more web pages of a content publisher; identifying one or more client-side events generated by one or more user interactions with the one or more web pages of the content publisher; storing user behavior data in the database, the user behavior data being generated based on the one or more identified client-side events and associated with the one or more web pages; identifying, using one or more machine learning processes, key passages of electronic content from at least the one or more web pages based on the user behavior data received from the plurality of client computers, the electronic content comprising electronic text and at least one of the machine learning processes being trained to reject invalid electronic content; ranking the identified key passages, wherein ranking the identified key passages comprises determining a ratio of user interactions with a key passage within the electronic text to total views of the electronic text; and publishing the highest ranked identified key passages from the one or more web pages to the application associated with the content publisher. 11. The method of claim 9 , wherein the plurality of modalities further includes at least one of email, mobile applications, and social media.

30. A code-portion-handling tool as claimed in claim 29 , wherein: the first data structure comprises further linked nodes representative of a language extension, the language extension being an extension to said computer-programming language, and the implementation rules define rules of substitutability to be enforced in relation to nodes of the second data structure corresponding to said one or more further nodes of the first data structure during a subsequent processing operation which utilizes said implementation in order to establish compliance with the substitutability relationships of said one or more further nodes of the first data structure represented by the first data structure; and the particular type of instance node is an instance node of a said further node of the language extension.

30. A code-portion-handling tool as claimed in claim 29 , wherein: the first data structure comprises further linked nodes representative of a language extension, the language extension being an extension to said computer-programming language, and the implementation rules define rules of substitutability to be enforced in relation to nodes of the second data structure corresponding to said one or more further nodes of the first data structure during a subsequent processing operation which utilizes said implementation in order to establish compliance with the substitutability relationships of said one or more further nodes of the first data structure represented by the first data structure; and the particular type of instance node is an instance node of a said further node of the language extension. 31. A code-portion-handling tool as claimed in claim 30 , wherein said candidate code portion includes parts that are attributable to said language extension.

6. The method of claim 4 , wherein the particular operator is a join operator that computes pairs of first tuples of a first table and second tuples of the table that have matching values.

6. The method of claim 4 , wherein the particular operator is a join operator that computes pairs of first tuples of a first table and second tuples of the table that have matching values. 7. The method of claim 6 , further comprising: determining that the dynamic scan operator is defined in an outer subtree of the join operator; and in response to determining that the dynamic scan operator is defined in an outer subtree of the join operator, pushing the partition selector operator to an outer child operator of the join operator.

13. A computer-implemented method comprising: causing to be stored, by a user agent running on an Internet-enabled device, information indicative of a current privacy setting; receiving, by the user agent, a navigation request relating to a resource associated with a web server; responsive to the navigation request, causing a HyperText Transport Protocol (HTTP) request to be generated, wherein a value associated with an HTTP header field of the HTTP request is set based on the current privacy setting; and requesting the web server to return to the user agent content associated with the resource by transmitting the HTTP request to the web server.

13. A computer-implemented method comprising: causing to be stored, by a user agent running on an Internet-enabled device, information indicative of a current privacy setting; receiving, by the user agent, a navigation request relating to a resource associated with a web server; responsive to the navigation request, causing a HyperText Transport Protocol (HTTP) request to be generated, wherein a value associated with an HTTP header field of the HTTP request is set based on the current privacy setting; and requesting the web server to return to the user agent content associated with the resource by transmitting the HTTP request to the web server. 14. The method of claim 13 , wherein the content is composed by the web server based at least in part on the value associated with the HTTP header field.

10. A non-transitory computer-readable storage medium storing one or more sequences of instructions, which, when executed by one or more processors, causes the one or more processors to carry out the steps of: storing a first value that is based at least in part on a first quantity of occurrences of a first word in a plurality of documents and a second value that is based at least in part on a second quantity of occurrences of a second word in the plurality of documents; for at least part of a document of the plurality of documents: detecting that the first word and the second word both occur in the at least part of the document; generating a random number between a first number and a second number; using the first value and the second value to determine a third value that is based at least in part on both the first quantity of occurrences of the first word in the plurality of documents and the second quantity of occurrences of the second word in the plurality of documents, wherein the third value is less than the second number and greater than the first number; comparing the third value and the random number; and in response to the detecting and based at least in part on the comparing, determining whether to send an update to a count for the first word and the second word.

10. A non-transitory computer-readable storage medium storing one or more sequences of instructions, which, when executed by one or more processors, causes the one or more processors to carry out the steps of: storing a first value that is based at least in part on a first quantity of occurrences of a first word in a plurality of documents and a second value that is based at least in part on a second quantity of occurrences of a second word in the plurality of documents; for at least part of a document of the plurality of documents: detecting that the first word and the second word both occur in the at least part of the document; generating a random number between a first number and a second number; using the first value and the second value to determine a third value that is based at least in part on both the first quantity of occurrences of the first word in the plurality of documents and the second quantity of occurrences of the second word in the plurality of documents, wherein the third value is less than the second number and greater than the first number; comparing the third value and the random number; and in response to the detecting and based at least in part on the comparing, determining whether to send an update to a count for the first word and the second word. 13. The non-transitory computer-readable storage medium as recited in claim 10 , wherein the first number is zero and the second number is 1, wherein the third value is a fractional part of a particular value that accounts for a predicted frequency of co-occurrence of the first word and the second word in the plurality of documents, and wherein the one or more sequences of instructions, when executed, cause the one or more processors to carry out determining whether to send the update to the count for the first word and the second word by determining to send the update of an integer part of the particular value to the count if the particular value is greater than or equal to 1, and if the fractional part is less than the random number.

7. The method of claim 1 , wherein the ontology further comprises: a plurality of links connecting nodes of the ontology with one another, each of the plurality of links representing a relation between nodes linked thereby.

7. The method of claim 1 , wherein the ontology further comprises: a plurality of links connecting nodes of the ontology with one another, each of the plurality of links representing a relation between nodes linked thereby. 10. The method of claim 7 , wherein at least one relation among nodes comprises an indication that one of the nodes represents at least one additional search criterion associated with a concept represented by another of the nodes.

2. The system of claim 1 , wherein each tokenizer comprises a word parser for identifying words in the received document according to grammar rules of the language associated with the parser, the identified words compared to the keywords from the keyword set associated with the respective tokenizer.

2. The system of claim 1 , wherein each tokenizer comprises a word parser for identifying words in the received document according to grammar rules of the language associated with the parser, the identified words compared to the keywords from the keyword set associated with the respective tokenizer. 3. The system of claim 2 , wherein each tokenizer further comprises a relevance filter for filtering out irrelevant words from the document prior to comparing the words to the keywords.

14. The apparatus of claim 13 , wherein the functions comprise providing the XML script to a device.

14. The apparatus of claim 13 , wherein the functions comprise providing the XML script to a device. 15. The apparatus of claim 14 , wherein the device comprises a controller that executes the XML script.

1. A learning system, comprising: a plurality of teacher stations and a plurality of student stations for holding one or more interactive learning sessions on a subject between a teacher of a plurality of teachers and at least two students, wherein the teacher and the at least two of the students interact with each other using free-style handwriting via a shared electronic white board of at least one of the plurality of teacher stations and at least two of the plurality of student stations; a database that stores at least one teacher attribute and at least one student attribute that relate to a language ability and a subject proficiency for the subject; and a server in communication with the database that: (i) serves computer generated instructional material relating to the subject to the at least two students through the at least two student stations, the computer generated instructional material for creating an interactive learning environment during the one or more interactive learning sessions, and wherein the computer generated instructional material is customized for the at least two students based on the language ability of each of the at least two students as determined by the server through each of the at least two student's respective student attributes stored in the database; and (ii) after serving the computer generated instructional material to the at least two students, selects the teacher from the plurality of teachers for the at least two students based on the language ability and the subject proficiency of each of the respective plurality of teachers teacher attributes stored in the database, wherein the teacher teaches the subject to the at least two students during the one or more interactive learning sessions in a language determined based on the language ability.

1. A learning system, comprising: a plurality of teacher stations and a plurality of student stations for holding one or more interactive learning sessions on a subject between a teacher of a plurality of teachers and at least two students, wherein the teacher and the at least two of the students interact with each other using free-style handwriting via a shared electronic white board of at least one of the plurality of teacher stations and at least two of the plurality of student stations; a database that stores at least one teacher attribute and at least one student attribute that relate to a language ability and a subject proficiency for the subject; and a server in communication with the database that: (i) serves computer generated instructional material relating to the subject to the at least two students through the at least two student stations, the computer generated instructional material for creating an interactive learning environment during the one or more interactive learning sessions, and wherein the computer generated instructional material is customized for the at least two students based on the language ability of each of the at least two students as determined by the server through each of the at least two student's respective student attributes stored in the database; and (ii) after serving the computer generated instructional material to the at least two students, selects the teacher from the plurality of teachers for the at least two students based on the language ability and the subject proficiency of each of the respective plurality of teachers teacher attributes stored in the database, wherein the teacher teaches the subject to the at least two students during the one or more interactive learning sessions in a language determined based on the language ability. 3. The learning system of claim 1 , wherein the computer generated instructional material comprises a test for assessing at least one skill gap.

1. A method of including search result based content in a web page, comprising: receiving a search criteria, wherein the search criteria specifies that a search result based content includes content from pages that match a language with which the web page is associated, and wherein the language comprises a primary language associated with the web page; receiving a display format; receiving a life cycle state; receiving an update schedule; receiving an indication that the search result based content is to be included in the web page; generating automatically for the web page a computer script or code configured to enable the search result based content to be retrieved in accordance with the search criteria, display format, life cycle state and update schedule; determining based at least in part on the update schedule to use the computer script or code to perform a search; receiving a set of search results of the search matching the search criteria and the life cycle state; including in the search result based content a content from a page that satisfies the search criteria and is associated with a secondary or default language associated with the web page, in the event a corresponding page associated with the primary language is not found; and using the set of search results to generate for the web page automatically the search result based content to be included in the web page based at least in part on the display format.

1. A method of including search result based content in a web page, comprising: receiving a search criteria, wherein the search criteria specifies that a search result based content includes content from pages that match a language with which the web page is associated, and wherein the language comprises a primary language associated with the web page; receiving a display format; receiving a life cycle state; receiving an update schedule; receiving an indication that the search result based content is to be included in the web page; generating automatically for the web page a computer script or code configured to enable the search result based content to be retrieved in accordance with the search criteria, display format, life cycle state and update schedule; determining based at least in part on the update schedule to use the computer script or code to perform a search; receiving a set of search results of the search matching the search criteria and the life cycle state; including in the search result based content a content from a page that satisfies the search criteria and is associated with a secondary or default language associated with the web page, in the event a corresponding page associated with the primary language is not found; and using the set of search results to generate for the web page automatically the search result based content to be included in the web page based at least in part on the display format. 2. A method as recited in claim 1 , wherein the search is performed in response in part to the update schedule.

19. A system for indexing digital video content maintained on a storage media item, the system comprising: a content acquisition module operative to retrieve one or more video object (“VOB”) files maintained on the storage media item; an extraction module operative to: extract caption and subtitle content from the one or more VOB files, segment the extracted caption and subtitle content into one or more segments, extract video and audio content corresponding to the one or more segments, and generate one or more descriptions of the video and audio content corresponding to the one or more segments; and an indexing component operative to generate one or more indices maintaining captions, subtitles, descriptions and corresponding video and audio content associated with the one or more segments of the one or more VOB files.

19. A system for indexing digital video content maintained on a storage media item, the system comprising: a content acquisition module operative to retrieve one or more video object (“VOB”) files maintained on the storage media item; an extraction module operative to: extract caption and subtitle content from the one or more VOB files, segment the extracted caption and subtitle content into one or more segments, extract video and audio content corresponding to the one or more segments, and generate one or more descriptions of the video and audio content corresponding to the one or more segments; and an indexing component operative to generate one or more indices maintaining captions, subtitles, descriptions and corresponding video and audio content associated with the one or more segments of the one or more VOB files. 27. The system of claim 19 wherein the extraction module is operative to extract caption and subtitle content comprising ASCII characters from a given VOB file.

1. A method for managing data organisation for computer programs, the method including the steps of: generating and storing a reference taxonomy, the reference taxonomy comprising information defining a user preference for data organisation; accessing storage associated with a computer program to obtain an application taxonomy, the application taxonomy comprising information defining the organisation of stored data items of the program; comparing the reference taxonomy with the application taxonomy to identify matching and non-matching features of the compared taxonomies; and in response to a selection of a preferred taxonomy based on a result of the comparison, storing the preferred taxonomy as a replacement of at least one of the reference taxonomy and the application taxonomy, wherein the step of storing the preferred taxonomy in response to a selection of the preferred taxonomy includes generating a modified application taxonomy which includes features of the compared reference taxonomy, and wherein the generated reference taxonomy includes nodes representing data structures and information representing relationships between data structures, and wherein the step of generating a modified application taxonomy includes repositioning data structures within the compared application taxonomy, such as that the relationships between the data structures of the modified application taxonomy and nodes of the reference taxonomy are more consistent than the relationships between data structures of the compared application taxonomy and nodes of the reference taxonomy.

1. A method for managing data organisation for computer programs, the method including the steps of: generating and storing a reference taxonomy, the reference taxonomy comprising information defining a user preference for data organisation; accessing storage associated with a computer program to obtain an application taxonomy, the application taxonomy comprising information defining the organisation of stored data items of the program; comparing the reference taxonomy with the application taxonomy to identify matching and non-matching features of the compared taxonomies; and in response to a selection of a preferred taxonomy based on a result of the comparison, storing the preferred taxonomy as a replacement of at least one of the reference taxonomy and the application taxonomy, wherein the step of storing the preferred taxonomy in response to a selection of the preferred taxonomy includes generating a modified application taxonomy which includes features of the compared reference taxonomy, and wherein the generated reference taxonomy includes nodes representing data structures and information representing relationships between data structures, and wherein the step of generating a modified application taxonomy includes repositioning data structures within the compared application taxonomy, such as that the relationships between the data structures of the modified application taxonomy and nodes of the reference taxonomy are more consistent than the relationships between data structures of the compared application taxonomy and nodes of the reference taxonomy. 6. A method according to claim 1 , wherein the step of generating a reference taxonomy includes: receiving user inputs via a graphical user interface; and interpreting user inputs to generate nodes representing data structures of a taxonomy and to generate information representing relationships between data structures.

1. A computer implemented method comprising one of selecting and receiving a problem domain, said problem domain containing problems defining behavior to-be-learned by at least one student, wherein said method includes a knowledge representation tool, wherein said knowledge representation tool enables at least one author to specify to-be-learned knowledge in sufficient detail to enable said student to solve problems in said problem domain and an interface creation tool, wherein said interface creation tool enables said author to define at least one medium through which to interact with said student, said computer implemented authoring method comprising the steps of: a) Constructing a SLT rule for solving problems in said problem domain, wherein said SLT rule consists of at least one data node and one procedure node, b) Constructing said SLT rule further consists of constructing an AST data structure and a procedure AST that operates on said AST data structure; wherein said AST data structure and said AST procedure are constructed by successive refinement of nodes, c) For each terminal node in said procedure AST, making said terminal node executable on a computer by providing said terminal node with means for specifying outputs of said terminal node, d) Assigning information, including associated media, to nodes in said SLT rule, to convey at least one of instruction, question, positive feedback and corrective feedback, e) Constructing at least one AST-based problem, each said problem being a data structure AST serving as data for said SLT rule, and f) Using said interface creation tool to assign attributes to nodes in each said AST based problem, including attributes defining at least one of location, how problem nodes are to be displayed on said interface, kinds of responses students are to provide and how student responses are to be evaluated, and g) Defining at least one method for interacting with said student, wherein said method includes at least one of mastery options, delivery options and interference methods specifying how tutoring decisions are to be made.

1. A computer implemented method comprising one of selecting and receiving a problem domain, said problem domain containing problems defining behavior to-be-learned by at least one student, wherein said method includes a knowledge representation tool, wherein said knowledge representation tool enables at least one author to specify to-be-learned knowledge in sufficient detail to enable said student to solve problems in said problem domain and an interface creation tool, wherein said interface creation tool enables said author to define at least one medium through which to interact with said student, said computer implemented authoring method comprising the steps of: a) Constructing a SLT rule for solving problems in said problem domain, wherein said SLT rule consists of at least one data node and one procedure node, b) Constructing said SLT rule further consists of constructing an AST data structure and a procedure AST that operates on said AST data structure; wherein said AST data structure and said AST procedure are constructed by successive refinement of nodes, c) For each terminal node in said procedure AST, making said terminal node executable on a computer by providing said terminal node with means for specifying outputs of said terminal node, d) Assigning information, including associated media, to nodes in said SLT rule, to convey at least one of instruction, question, positive feedback and corrective feedback, e) Constructing at least one AST-based problem, each said problem being a data structure AST serving as data for said SLT rule, and f) Using said interface creation tool to assign attributes to nodes in each said AST based problem, including attributes defining at least one of location, how problem nodes are to be displayed on said interface, kinds of responses students are to provide and how student responses are to be evaluated, and g) Defining at least one method for interacting with said student, wherein said method includes at least one of mastery options, delivery options and interference methods specifying how tutoring decisions are to be made. 16. A computer implemented method in accordance with claim 1 when said problem domain received by said author contains more than one problem domain, wherein said method comprises performing all steps in claim 1 to construct one SLT solution rule in turn for each said problem domain.

1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user.

1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user. 5. The method of claim 1 , further comprising: applying voice recognition techniques to an audio clip of a person reading aloud from the distinguished rendered document to generate the captured text.

62. The non-transitory computer-readable medium of claim 50 , wherein the first question instance further comprises a first question definition, and wherein the instructions to automatically generate a first answer comprises instructions to process the first question definition to automatically generate the first answer.

62. The non-transitory computer-readable medium of claim 50 , wherein the first question instance further comprises a first question definition, and wherein the instructions to automatically generate a first answer comprises instructions to process the first question definition to automatically generate the first answer. 64. The non-transitory computer-readable medium of claim 62 , wherein the first question definition is independent of the first text.

23. A computer-readable memory device that stores computer-executable instructions, the computer-readable memory device comprising: one or more instructions to search a collection of documents, based on a search query, to identify a set of search result documents; one or more instructions to receive a request to save a selected search result document of the plurality of search result documents; one or more instructions to save information associated with the selected search result document in response to the request to save the selected search result document; one or more instructions to identify a particular document that is similar to the selected search result document based on the saved information and, where the one or more instructions to identify the particular document that is similar to the selected search result document includes at least two of: one or more instructions to determine whether the particular document and the selected search result document have a plurality of outgoing links that point to the same documents, one or more instructions to determine whether the particular document and the selected search result document have a plurality of incoming links that come from the same documents, one or more instructions to determine whether the particular document and the selected search result document have a same format, or one or more instructions to determine whether the particular document and the selected search result document have a same layout; and one or more instructions to boost, based on saving the information associated with the selected search result document and identifying the particular document as similar to the selected search result document, a score for the selected search result document and a score for the particular document for subsequent searches involving the search query.

23. A computer-readable memory device that stores computer-executable instructions, the computer-readable memory device comprising: one or more instructions to search a collection of documents, based on a search query, to identify a set of search result documents; one or more instructions to receive a request to save a selected search result document of the plurality of search result documents; one or more instructions to save information associated with the selected search result document in response to the request to save the selected search result document; one or more instructions to identify a particular document that is similar to the selected search result document based on the saved information and, where the one or more instructions to identify the particular document that is similar to the selected search result document includes at least two of: one or more instructions to determine whether the particular document and the selected search result document have a plurality of outgoing links that point to the same documents, one or more instructions to determine whether the particular document and the selected search result document have a plurality of incoming links that come from the same documents, one or more instructions to determine whether the particular document and the selected search result document have a same format, or one or more instructions to determine whether the particular document and the selected search result document have a same layout; and one or more instructions to boost, based on saving the information associated with the selected search result document and identifying the particular document as similar to the selected search result document, a score for the selected search result document and a score for the particular document for subsequent searches involving the search query. 25. The computer-readable memory device of claim 23 , where the selected search result document is one of a plurality of search result documents that have been saved as saved search results in a data structure, and where the computer-readable memory device further comprises: one or more instructions to receive an indication to delete one of the saved search results; one or more instructions to delete the one of the saved search results in response to the received indication; and one or more instructions to adjust scores for a remaining one or more of the saved search results other than the deleted one of the saved search results.

29. The apparatus of claim 27 , wherein the computer readable instructions, when executed, further cause the apparatus to: determine an improvement for raising the search engine score of the network document by analyzing at least one of: a missing meta title, a missing meta description, a missing meta keyword, a duplicate meta title, a duplicate meta description, a duplicate meta keyword, and a broken link; and display the improvement.

29. The apparatus of claim 27 , wherein the computer readable instructions, when executed, further cause the apparatus to: determine an improvement for raising the search engine score of the network document by analyzing at least one of: a missing meta title, a missing meta description, a missing meta keyword, a duplicate meta title, a duplicate meta description, a duplicate meta keyword, and a broken link; and display the improvement. 30. The apparatus of claim 29 , wherein the computer readable instructions, when executed, further cause the apparatus to: receive a request to re-analyze the network document upon the improvement being made to the network document; and re-analyze the network document including the improvement.

9. The apparatus of claim 8 wherein the coprocessor interface software is further configured to pass data to the coprocessor to thereby enable the coprocessor to perform the query-specified data processing operation on the identified subset of unstructured data.

9. The apparatus of claim 8 wherein the coprocessor interface software is further configured to pass data to the coprocessor to thereby enable the coprocessor to perform the query-specified data processing operation on the identified subset of unstructured data. 10. The apparatus of claim 9 wherein the relational engine software comprises SQL relational engine software.

7. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to programmatically provide a user interface for forming a query by: displaying a first row of query criteria, wherein the query criteria comprises a first operand, a second operand, and a comparative operator for comparing the first operand with the second operand; displaying a second row of query criteria, the second row being logically connected to the first row by a first Boolean connector; displaying a third row of query criteria, the third row being logically connected to the second row by a second Boolean connector; displaying a fourth row of query criteria; displaying the second row and third row together in a bounded area, wherein the bounded area indicates that the second row and the third row are on a child level from the first row, and that the query criteria from the second row and third row will be evaluated together before the query criteria from the first row; in response to a user drag-and-drop operation comprising moving the fourth row within the bounded area, nesting the fourth row of query criteria with the second row and third row of query criteria; and executing a query comprising evaluating the query criteria from the second row, third row, and fourth row together before evaluating the query criteria from the first row, wherein nested query criteria are evaluated before query criteria that are not nested.

7. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to programmatically provide a user interface for forming a query by: displaying a first row of query criteria, wherein the query criteria comprises a first operand, a second operand, and a comparative operator for comparing the first operand with the second operand; displaying a second row of query criteria, the second row being logically connected to the first row by a first Boolean connector; displaying a third row of query criteria, the third row being logically connected to the second row by a second Boolean connector; displaying a fourth row of query criteria; displaying the second row and third row together in a bounded area, wherein the bounded area indicates that the second row and the third row are on a child level from the first row, and that the query criteria from the second row and third row will be evaluated together before the query criteria from the first row; in response to a user drag-and-drop operation comprising moving the fourth row within the bounded area, nesting the fourth row of query criteria with the second row and third row of query criteria; and executing a query comprising evaluating the query criteria from the second row, third row, and fourth row together before evaluating the query criteria from the first row, wherein nested query criteria are evaluated before query criteria that are not nested. 9. The computer-readable medium of claim 7 , wherein the bounded area comprises a box.

19. A processor readable non-transitive storage media that includes data and instructions, wherein the execution of the instructions enables actions for printing a document at a printing device, comprising: receiving the document at a networked device, wherein the document includes text and identifies at least one target font reference for each character; determining if a name of the target font reference is listed in a font strategy table, then employing at least one of a corresponding logic component, substitute font data, and character data to provide substitute font information and width for each character to the printing device; determining if the name of the target font reference is unlisted in the font strategy table, then updating the font strategy table to include the name of the unlisted target font reference, wherein each updated target font reference corresponds to at least one logic component, substitute font data or character data; generating a first character table for the target font reference that includes at least a glyph index and a unicode; generating a second character table for the target font reference that includes at least a width and a glyph name; and enabling the printing device to employ provided font information and width for each character to print text included in the document.

19. A processor readable non-transitive storage media that includes data and instructions, wherein the execution of the instructions enables actions for printing a document at a printing device, comprising: receiving the document at a networked device, wherein the document includes text and identifies at least one target font reference for each character; determining if a name of the target font reference is listed in a font strategy table, then employing at least one of a corresponding logic component, substitute font data, and character data to provide substitute font information and width for each character to the printing device; determining if the name of the target font reference is unlisted in the font strategy table, then updating the font strategy table to include the name of the unlisted target font reference, wherein each updated target font reference corresponds to at least one logic component, substitute font data or character data; generating a first character table for the target font reference that includes at least a glyph index and a unicode; generating a second character table for the target font reference that includes at least a width and a glyph name; and enabling the printing device to employ provided font information and width for each character to print text included in the document. 23. The media of claim 19 , wherein if the name of the target font reference is listed in the font strategy table, further determining if the font strategy table identifies a downloadable font, then providing the downloadable font information and width for each character to the printing device.

11. A non-transitory computer readable medium having computer readable instructions stored thereon for execution by a processor, the computer readable instructions capable of performing a method for compiling marketing information for a client, the method comprising: obtaining data from a plurality of social media websites, wherein each of the social media websites includes a universal resource identifier that points to a client website; extracting a plurality of insights from the obtained data, resulting in extracted insights, wherein each of the extracted insights comprises text elements that denote product approval for at least one product available for sale at the client website; collecting measurements of traffic to the client website, the traffic being referred to the client website by the plurality of social media websites; and generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the extracted insights across the plurality of social media websites to rank the extracted insights.

11. A non-transitory computer readable medium having computer readable instructions stored thereon for execution by a processor, the computer readable instructions capable of performing a method for compiling marketing information for a client, the method comprising: obtaining data from a plurality of social media websites, wherein each of the social media websites includes a universal resource identifier that points to a client website; extracting a plurality of insights from the obtained data, resulting in extracted insights, wherein each of the extracted insights comprises text elements that denote product approval for at least one product available for sale at the client website; collecting measurements of traffic to the client website, the traffic being referred to the client website by the plurality of social media websites; and generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the extracted insights across the plurality of social media websites to rank the extracted insights. 13. The non-transitory computer readable medium of claim 11 , wherein the referred traffic dynamics summary table ranks the extracted insights in accordance with an assumption that the extracted insights have contributed to a decision to buy the at least one product available for sale at the client website.

2. The system according to claim 1 , wherein the detection means includes means for formatting each intercepted electronic mail.

2. The system according to claim 1 , wherein the detection means includes means for formatting each intercepted electronic mail. 3. The system according to claim 2 , wherein the detection means further include means for copying the formatted electronic mall to the electronic mail manager database (EMM DB).

40. A non-transitory computer-readable storage medium storing instructions for transmitting an electronic document, the instructions causing one or more computer processors to perform operations comprising: receiving, at an intermediate computer that is remote from an electronic device, an email message from the electronic device, the email message having a delivery address; determining that the email message has an attached document including metadata; automatically creating a cleansed version of the attached document by removing at least a portion of the metadata from the attached document; replacing in the email message the attached document with the cleansed version of the attached document; and sending the email message with the cleansed version of the attached document from the intermediate computer to the delivery address.

40. A non-transitory computer-readable storage medium storing instructions for transmitting an electronic document, the instructions causing one or more computer processors to perform operations comprising: receiving, at an intermediate computer that is remote from an electronic device, an email message from the electronic device, the email message having a delivery address; determining that the email message has an attached document including metadata; automatically creating a cleansed version of the attached document by removing at least a portion of the metadata from the attached document; replacing in the email message the attached document with the cleansed version of the attached document; and sending the email message with the cleansed version of the attached document from the intermediate computer to the delivery address. 42. The storage medium of claim 40 , wherein the instructions cause the processor to further perform the operation of saving the cleansed version of the attached document.

15. A system according to claim 13 , wherein when the user edits the document structure of one of said documents, said edit results in a corresponding change to the model structure, leading to the refreshing of said model structure wherever said model structure appears in all of the documents.

15. A system according to claim 13 , wherein when the user edits the document structure of one of said documents, said edit results in a corresponding change to the model structure, leading to the refreshing of said model structure wherever said model structure appears in all of the documents. 16. A system according to claim 15 , further comprising means for prompting the user to select one of a plurality of possible model change interpretations of the document structure edit.

1. A computer-implemented method, comprising: capturing, by a camera in electronic communication with a computing system having one or more processors, a first image of an object comprising a text in a source language; receiving, at the computing system and from the camera, the first image; performing, by the computing system, optical character recognition (OCR) on the first image to obtain an OCR text that is a machine-encoded text representation of the text; in response to obtaining the OCR text, automatically obtaining, by the computing system and from a machine translation system, a first translated OCR text and a translation score indicative of a degree of likelihood that the first translated OCR text is an appropriate translation of the OCR text to a target language; and when the translation score is less than a translation score threshold indicative of an acceptable degree of likelihood: outputting, by the computing system, a user instruction to capture a set of second images of at least a portion of the object using the camera; in response to outputting the user instruction, capturing, by the camera, the second set of images; receiving, at the computing system and from the camera, the set of second images; performing, by the computing system, OCR on at least one of the set of second images to obtain a modified OCR text corresponding to the text; in response to obtaining the modified OCR text, obtaining, by the computing system and from the machine translation system, a second translated OCR text representing a translation of the modified OCR text from the source language to the target language; and outputting, by the computing system, the second translated OCR text.

1. A computer-implemented method, comprising: capturing, by a camera in electronic communication with a computing system having one or more processors, a first image of an object comprising a text in a source language; receiving, at the computing system and from the camera, the first image; performing, by the computing system, optical character recognition (OCR) on the first image to obtain an OCR text that is a machine-encoded text representation of the text; in response to obtaining the OCR text, automatically obtaining, by the computing system and from a machine translation system, a first translated OCR text and a translation score indicative of a degree of likelihood that the first translated OCR text is an appropriate translation of the OCR text to a target language; and when the translation score is less than a translation score threshold indicative of an acceptable degree of likelihood: outputting, by the computing system, a user instruction to capture a set of second images of at least a portion of the object using the camera; in response to outputting the user instruction, capturing, by the camera, the second set of images; receiving, at the computing system and from the camera, the set of second images; performing, by the computing system, OCR on at least one of the set of second images to obtain a modified OCR text corresponding to the text; in response to obtaining the modified OCR text, obtaining, by the computing system and from the machine translation system, a second translated OCR text representing a translation of the modified OCR text from the source language to the target language; and outputting, by the computing system, the second translated OCR text. 9. The computer-implemented method of claim 1 , wherein the camera is a device that is distinct from the one or more processors and a display of the computing system.

1. A music score reading method comprising: recognizing all signs and notes of a music score, in a sian recognizing step; estimating a drum notation in a drum part of the music score based on information obtained by said recognizing step, in a notation estimating step; and allocating actual tone generating musical instruments to the recognized signs of the drum part according to the drum notation estimated by said notation estimating step, in a musical instrument allocating step, such that the music score is converted into a readable music score data format.

1. A music score reading method comprising: recognizing all signs and notes of a music score, in a sian recognizing step; estimating a drum notation in a drum part of the music score based on information obtained by said recognizing step, in a notation estimating step; and allocating actual tone generating musical instruments to the recognized signs of the drum part according to the drum notation estimated by said notation estimating step, in a musical instrument allocating step, such that the music score is converted into a readable music score data format. 3. A music score reading method according to claim 1 wherein said notation estimating step estimates the drum notation based on information obtained by a sign recognizing function and including at least a staff position of a drum head, a kind of a drum head, a hi-hat open sign relating to a drum note, a hi-hat close sign relating to a drum note, an accent sign relating to a drum note, a stem of a drum note, a flag of a drum note, a character string for designation of a drum tone of a note, a tone length determined by the flag of the drum note, and another tone length determined by a head kind based on existence of the tone length of the drum note derived by said flag.

3. The computer program product of claim 2 , further comprising: recursively updating the transmission graph until the transmission graph meets a predetermined criterion by recomputing the frequency of transmission and probability for each one of the plurality of edges.

3. The computer program product of claim 2 , further comprising: recursively updating the transmission graph until the transmission graph meets a predetermined criterion by recomputing the frequency of transmission and probability for each one of the plurality of edges. 4. The computer program product of claim 3 , further comprising: outputting an updated transmission graph.

19. A non-transitory computer-readable medium including one or more sequences of instructions that, when executed by one or more processors, cause the processors to perform operations comprising: receiving, at a computer device and from an image capturing component, real-time image data; extracting one or more objects or a scene from the real-time image data based on results from real-time adaptive learning and one or more object/scene extraction parameters, wherein the real-time adaptive learning comprises object learning, object recognition, object segmentation, scene learning, scene recognition, scene segmentation, or a combination thereof; extracting one or more human objects from the real-time image data based on results from real-time adaptive human learning and one or more human extraction parameters, wherein the real-time adaptive human learning comprises human characteristic learning, human recognition, human segmentation, human body movement tracking, or a combination thereof; receiving augmented reality (AR) input data; and creating holographic AR image data by projecting, for each image, the extracted object or scene, the extracted human object, and the AR input data using a multi-layered mechanism based on projection parameters.

19. A non-transitory computer-readable medium including one or more sequences of instructions that, when executed by one or more processors, cause the processors to perform operations comprising: receiving, at a computer device and from an image capturing component, real-time image data; extracting one or more objects or a scene from the real-time image data based on results from real-time adaptive learning and one or more object/scene extraction parameters, wherein the real-time adaptive learning comprises object learning, object recognition, object segmentation, scene learning, scene recognition, scene segmentation, or a combination thereof; extracting one or more human objects from the real-time image data based on results from real-time adaptive human learning and one or more human extraction parameters, wherein the real-time adaptive human learning comprises human characteristic learning, human recognition, human segmentation, human body movement tracking, or a combination thereof; receiving augmented reality (AR) input data; and creating holographic AR image data by projecting, for each image, the extracted object or scene, the extracted human object, and the AR input data using a multi-layered mechanism based on projection parameters. 25. The non-transitory computer-readable medium of claim 19 , wherein each pixel of the AR input data is separated into multiple layers.

1. A method for determining a rank of a URL for a search query, the method comprising: receiving a search query by a processor; receiving a URL by the processor; sending the search query to a search engine by the processor; receiving a first result set from the search engine by the processor; receiving a second result set from the search engine by the processor; determining a first rank of the URL in the first result set; determining a second rank of the URL in the second result set; determining a third rank of the URL for the search query for the search engine based on the first and second result sets and the first and second ranks, by the processor; determining a variability of the third rank of the URL for the search engine based on the first and second result sets by the processor and the first and second ranks; and generating a report including the third rank and the variability of the third rank by the processor.

1. A method for determining a rank of a URL for a search query, the method comprising: receiving a search query by a processor; receiving a URL by the processor; sending the search query to a search engine by the processor; receiving a first result set from the search engine by the processor; receiving a second result set from the search engine by the processor; determining a first rank of the URL in the first result set; determining a second rank of the URL in the second result set; determining a third rank of the URL for the search query for the search engine based on the first and second result sets and the first and second ranks, by the processor; determining a variability of the third rank of the URL for the search engine based on the first and second result sets by the processor and the first and second ranks; and generating a report including the third rank and the variability of the third rank by the processor. 2. The method as recited in claim 1 , further comprising: sending the search query to a first data center of the search engine by the processor; sending the search query to a second data center of the search engine by the processor; receiving the first result set from the first data center by the processor; and receiving the second result set from the second data center by the processor.

23. A method for implementing an interface terminology in a longitudinal electronic medical record, the interface terminology comprising a plurality of concepts and a plurality of descriptions, a description being an alternative way to express a concept, the method comprising: linking, in a database, each concept to two or more respective descriptions via a directed graph structure; storing, in a database, an external code set comprising a plurality of external codes; mapping each concept to a respective external code via a directed graph structure; and deploying a front-end file, the front-end file comprises a link between the descriptions and the external code set; wherein each said respective concept provides a unique terminology for a user and can be added, updated, deleted, and merged; wherein said descriptions in said database include terms used by both clinicians and patients; wherein, for each concept, one of said plurality of descriptions is a preferred description for the linked concept and one of said plurality of descriptions is a preferred consumer term for the linked concept; wherein each said concept may map to more than one of said plurality of external codes; and wherein said method for implementing an interface terminology serves the ends of capturing clinician's intent, driving financial aspects including billing, and driving analytical functions; creating a longitudinal electronic medical record by: generating a first instance of a plurality of data objects during a first encounter, said plurality of data objects comprising data elements further comprising a first instance identifier and temporal identifiers; linking a data object in said first instance to a summarization reference with a pointer, where the plurality of data objects and the summarization reference are related as part of a directed graph data structure; creating an additional instance of a plurality of data objects during a later encounter, said additional instance of a plurality of data objects comprising data elements further comprising an additional instance identifier and temporal identifier; and providing continuity for said plurality of data objects of said first instance over time by tracking a relationship between said data object of said first instance and a data object of said additional instance; tagging elements within a domain within the longitudinal electronic medical record with one or more of said plurality of descriptions; and displaying the preferred descriptions and the preferred consumer term.

23. A method for implementing an interface terminology in a longitudinal electronic medical record, the interface terminology comprising a plurality of concepts and a plurality of descriptions, a description being an alternative way to express a concept, the method comprising: linking, in a database, each concept to two or more respective descriptions via a directed graph structure; storing, in a database, an external code set comprising a plurality of external codes; mapping each concept to a respective external code via a directed graph structure; and deploying a front-end file, the front-end file comprises a link between the descriptions and the external code set; wherein each said respective concept provides a unique terminology for a user and can be added, updated, deleted, and merged; wherein said descriptions in said database include terms used by both clinicians and patients; wherein, for each concept, one of said plurality of descriptions is a preferred description for the linked concept and one of said plurality of descriptions is a preferred consumer term for the linked concept; wherein each said concept may map to more than one of said plurality of external codes; and wherein said method for implementing an interface terminology serves the ends of capturing clinician's intent, driving financial aspects including billing, and driving analytical functions; creating a longitudinal electronic medical record by: generating a first instance of a plurality of data objects during a first encounter, said plurality of data objects comprising data elements further comprising a first instance identifier and temporal identifiers; linking a data object in said first instance to a summarization reference with a pointer, where the plurality of data objects and the summarization reference are related as part of a directed graph data structure; creating an additional instance of a plurality of data objects during a later encounter, said additional instance of a plurality of data objects comprising data elements further comprising an additional instance identifier and temporal identifier; and providing continuity for said plurality of data objects of said first instance over time by tracking a relationship between said data object of said first instance and a data object of said additional instance; tagging elements within a domain within the longitudinal electronic medical record with one or more of said plurality of descriptions; and displaying the preferred descriptions and the preferred consumer term. 25. The method according to claim 23 , further comprising: adding a new external code; mapping at least one concept to the new external code; and re-deploying the front-end file, the front-end file comprising a link between at least one description and the new external code; wherein the mapping step occurs without the need to re-link the at least one description to the at least one concept.

14. A method for assigning points in a high dimensional space to each word in a vocabulary of words, the method comprising: obtaining a set of training data, wherein the set of training data comprises sequences of words; training a classifier and an embedding function on the set of training data, wherein the embedding function receives a plurality of words surrounding an unknown word in a sequence of words and maps the plurality of words into a numeric representation in accordance with a set of embedding function parameters, wherein the classifier processes the numeric representation of the sequence of words to generate a respective word score for each word in a pre-determined set of words, and wherein each of the respective word scores measure a predicted likelihood that the corresponding word is the unknown word, and wherein training the embedding function comprises obtained trained values of the embedding function parameters; processing each word in the vocabulary using the embedding function in accordance with the trained values of the embedding function parameters to generate a respective numerical representation of each word in the vocabulary in the high-dimensional space; and associating each word in the vocabulary with the respective numeric representation of the word in the high-dimensional space.

14. A method for assigning points in a high dimensional space to each word in a vocabulary of words, the method comprising: obtaining a set of training data, wherein the set of training data comprises sequences of words; training a classifier and an embedding function on the set of training data, wherein the embedding function receives a plurality of words surrounding an unknown word in a sequence of words and maps the plurality of words into a numeric representation in accordance with a set of embedding function parameters, wherein the classifier processes the numeric representation of the sequence of words to generate a respective word score for each word in a pre-determined set of words, and wherein each of the respective word scores measure a predicted likelihood that the corresponding word is the unknown word, and wherein training the embedding function comprises obtained trained values of the embedding function parameters; processing each word in the vocabulary using the embedding function in accordance with the trained values of the embedding function parameters to generate a respective numerical representation of each word in the vocabulary in the high-dimensional space; and associating each word in the vocabulary with the respective numeric representation of the word in the high-dimensional space. 17. The method of claim 14 , wherein the embedding function maps each of the plurality of words to a respective floating point vector and outputs a single merged vector that is a combination of the respective floating point vectors.

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

27. A computer-implemented method comprising: enabling, using a computing device, secure information transfer between a web browser's scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, said enabling the at least one object to be returned cross-domain enabling return of a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 31. The computer-implemented method of claim 27 , further comprising: enabling bypassing security checks based, at least in part, on a determination of the information transfer occurring in a same domain.

18. A non-transitory machine-readable medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising: generating summary records that summarize full item records, the generating of the summary records being performed by the one or more processors of the machine; receiving a request from a user and indicative of a geographic region; and presenting at least part of a full item record among the full item records based on the generated summary records that summarize the full item records and based on the geographic region in response to the received request.

18. A non-transitory machine-readable medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising: generating summary records that summarize full item records, the generating of the summary records being performed by the one or more processors of the machine; receiving a request from a user and indicative of a geographic region; and presenting at least part of a full item record among the full item records based on the generated summary records that summarize the full item records and based on the geographic region in response to the received request. 20. The non-transitory machine-readable storage medium of claim 18 , wherein: the map file organizes a portion of the summary records into a group that corresponds to the geographic region indicated by the request; and the presenting of at least the part of the full item record is based on the group that corresponds to the geographic region.

12. A system of providing an interactive media presentation, the system comprising: a user electronic device associated with a user; an electronic device associated with an embodier, wherein the electronic device is in communication with the user electronic device; and a computer-readable storage medium in communication with the electronic device, wherein the computer-readable storage medium comprises one or more programming instructions that when executed, cause the electronic device to: receive, from the user electronic device, an indication that an interactive portion of a media presentation is about to begin, cause a graphical representation of a conversation atlas to be displayed to the embodier via a display device of the electronic device, wherein the conversation atlas comprises a plurality of selection elements that are each associated with an audio element for a character that is featured in the interactive portion, receive, from the user electronic device, a user response, wherein the user response comprises conversational information received from a user wherein the conversational information is directed to a character of the media presentation, in response to receiving the user response, receive, from the embodier, a selection of at least one of the plurality of selection elements of the conversation atlas, identify the audio element that corresponds to the selected selection element; and cause the identified audio element to be performed at the user electronic device, wherein the user electronic device does not display the graphical representation of the conversation atlas.

12. A system of providing an interactive media presentation, the system comprising: a user electronic device associated with a user; an electronic device associated with an embodier, wherein the electronic device is in communication with the user electronic device; and a computer-readable storage medium in communication with the electronic device, wherein the computer-readable storage medium comprises one or more programming instructions that when executed, cause the electronic device to: receive, from the user electronic device, an indication that an interactive portion of a media presentation is about to begin, cause a graphical representation of a conversation atlas to be displayed to the embodier via a display device of the electronic device, wherein the conversation atlas comprises a plurality of selection elements that are each associated with an audio element for a character that is featured in the interactive portion, receive, from the user electronic device, a user response, wherein the user response comprises conversational information received from a user wherein the conversational information is directed to a character of the media presentation, in response to receiving the user response, receive, from the embodier, a selection of at least one of the plurality of selection elements of the conversation atlas, identify the audio element that corresponds to the selected selection element; and cause the identified audio element to be performed at the user electronic device, wherein the user electronic device does not display the graphical representation of the conversation atlas. 19. The system of claim 12 , wherein the one or more programming instructions that, when executed, cause the electronic device to cause the identified audio element to be performed at the user electronic device in a voice of the character comprise one or more programming instructions that, when executed, cause the electronic device to cause one or more features of a graphical representation of the character to change based on the identified audio element.

47. A computer program product for transforming a dynamically changing electronic document comprising: means for providing a visual representation of one or more instances of a dynamically changing electronic document to a user; means for receiving feedback from interaction by the user with the visual representation, said feedback identifying one or more portions of said visual representation, said feedback being used to generate one or more virtual tags, said virtual tags identifying features of said one or more portions of said visual representation; means for constructing one or more transformation rules using said feedback and said one or more virtual tags; and means for applying said one or more transformation rules to said one or more instances of said electronic document, a second electronic document or future versions of said one or more instances of said electronic document to extract customized content identified from said one or more virtual tags and generate a virtual page of said customized content.

47. A computer program product for transforming a dynamically changing electronic document comprising: means for providing a visual representation of one or more instances of a dynamically changing electronic document to a user; means for receiving feedback from interaction by the user with the visual representation, said feedback identifying one or more portions of said visual representation, said feedback being used to generate one or more virtual tags, said virtual tags identifying features of said one or more portions of said visual representation; means for constructing one or more transformation rules using said feedback and said one or more virtual tags; and means for applying said one or more transformation rules to said one or more instances of said electronic document, a second electronic document or future versions of said one or more instances of said electronic document to extract customized content identified from said one or more virtual tags and generate a virtual page of said customized content. 65. The computer program product of claim 47 wherein said visual representation is accessed with a graphical user interface.

1. A spine implant adapted to be attached to another spine implant wherein the another spine implant includes a first fastener secured to a first portion of a first vertebra and a second fastener secured to a second portion of the first vertebra, the spine implant including: an elongated member with a first end and a second end, said first end adapted to be secured to the first fastener and the second end adapted to be secured to the second fastener; the elongated member including a platform and a first spring located between the platform and the first end and a second spring located between the platform and the second end; and a vertical rod assembly having a first rod end connected to the platform, and a second rod end configured for attachment to a second vertebra; such that, when secured between the first vertebra and second vertebra, the vertical rod assembly transmits load from the second vertebra to the platform, the platform transmits said load to the first end of the elongated member via the first spring and the second end of the elongated member via the second spring, and the first end and second end of the elongated member transmit said load to the first vertebra via the first fastener and the second fastener.

1. A spine implant adapted to be attached to another spine implant wherein the another spine implant includes a first fastener secured to a first portion of a first vertebra and a second fastener secured to a second portion of the first vertebra, the spine implant including: an elongated member with a first end and a second end, said first end adapted to be secured to the first fastener and the second end adapted to be secured to the second fastener; the elongated member including a platform and a first spring located between the platform and the first end and a second spring located between the platform and the second end; and a vertical rod assembly having a first rod end connected to the platform, and a second rod end configured for attachment to a second vertebra; such that, when secured between the first vertebra and second vertebra, the vertical rod assembly transmits load from the second vertebra to the platform, the platform transmits said load to the first end of the elongated member via the first spring and the second end of the elongated member via the second spring, and the first end and second end of the elongated member transmit said load to the first vertebra via the first fastener and the second fastener. 8. The spine implant of claim 1 including: said elongated member having a diameter with the first and the second springs defined within the diameter.

6. The system of claim 5 , wherein the input information is selected from a group of input information consisting of a string of text and at least one name-value pair and a string of text with at least one name-value pair.

6. The system of claim 5 , wherein the input information is selected from a group of input information consisting of a string of text and at least one name-value pair and a string of text with at least one name-value pair. 7. The system of claim 6 , wherein listing information is for a listing that describes an item for sale on a network-based marketplace, and wherein the input information includes a title of the listing that describes the item for sale on the network-based marketplace.

1. A computer program product tangibly embodied in a non-transitory computer readable medium, the computer program product including instructions that, when executed, cause a processor to perform operations for generating a unique name for at least one of several data elements, the operations comprising: receiving a definition of a data element for which a unique name is to be created that complies with a predefined name format, the unique name to be associated with the data element, the definition configured to aid users in understanding the data element, the definition comprising human-understandable descriptive language, the data element identifying an information category in an electronic communication; identifying a noun phrase and a verb phrase in the definition; and generating the unique name using a first noun obtained from the noun phrase and a second noun obtained from the verb phrase.

1. A computer program product tangibly embodied in a non-transitory computer readable medium, the computer program product including instructions that, when executed, cause a processor to perform operations for generating a unique name for at least one of several data elements, the operations comprising: receiving a definition of a data element for which a unique name is to be created that complies with a predefined name format, the unique name to be associated with the data element, the definition configured to aid users in understanding the data element, the definition comprising human-understandable descriptive language, the data element identifying an information category in an electronic communication; identifying a noun phrase and a verb phrase in the definition; and generating the unique name using a first noun obtained from the noun phrase and a second noun obtained from the verb phrase. 13. The computer program product of claim 1 , wherein the data element comprises a data type that can be used in defining any of the several data elements and wherein the predefined name format requires the unique name to comprise at least a qualifier term, a data term and a type term.

4. A dialogue-based learning apparatus through dialogue with users, comprising: a speech input unit for inputting speeches; a speech recognition unit for recognizing the input speech; and a behavior and dialogue controller for controlling behaviors and dialogues according to speech recognition results, wherein the behavior and dialogue controller has a topic recognition expert to memorise contents of utterances and to retrieve the topic that best matches the speech recognition results, and a mode switching expert to control mode switching, wherein the mode switching expert switches operation modes of the apparatus between a learning mode and an execution mode in accordance with a command in the recognized speech input through a user utterance, wherein in the learning mode, the topic recognition expert creates a word graph from each speech that the user utters as corresponding to a new topic, the word graph being a plurality of candidate words or sentences that are constructed by words contained in a predetermined dictionary together with associated matching probabilities with respect to the uttered speech, and the topic recognition expert registers each of words constituting the word graph together with associated occurrence frequencies as representing said new topic, the topic recognition expert registering, as representing said new topic, words and associated occurrence frequencies generated by a plurality of the word graphs when the user utters plural speeches as corresponding to the new topic, and wherein in the execution mode, the topic recognition expert performs searches from among topics that have been registered in the learning mode, and selects the maximum likelihood topic.

4. A dialogue-based learning apparatus through dialogue with users, comprising: a speech input unit for inputting speeches; a speech recognition unit for recognizing the input speech; and a behavior and dialogue controller for controlling behaviors and dialogues according to speech recognition results, wherein the behavior and dialogue controller has a topic recognition expert to memorise contents of utterances and to retrieve the topic that best matches the speech recognition results, and a mode switching expert to control mode switching, wherein the mode switching expert switches operation modes of the apparatus between a learning mode and an execution mode in accordance with a command in the recognized speech input through a user utterance, wherein in the learning mode, the topic recognition expert creates a word graph from each speech that the user utters as corresponding to a new topic, the word graph being a plurality of candidate words or sentences that are constructed by words contained in a predetermined dictionary together with associated matching probabilities with respect to the uttered speech, and the topic recognition expert registers each of words constituting the word graph together with associated occurrence frequencies as representing said new topic, the topic recognition expert registering, as representing said new topic, words and associated occurrence frequencies generated by a plurality of the word graphs when the user utters plural speeches as corresponding to the new topic, and wherein in the execution mode, the topic recognition expert performs searches from among topics that have been registered in the learning mode, and selects the maximum likelihood topic. 6. The dialogue-based learning apparatus according to claim 4 , wherein the speech recognition unit comprises a Small Vocabulary Automatic Speech Recognizer SVASR and a Large Vocabulary Automatic Speech Recognizer LVASR, wherein in the behavior and dialogue controller, a recognition result of the SVASR is forwarded to the mode switching expert, and when the mode switching expert makes a determination on mode switching, the topic recognition expert operates in the learning or execution mode that has been determined by the mode switching expert, and wherein in the learning mode, the topic recognition expert generates a word graph based on speech recognition using the LVASR.

6. The method of claim 1 further comprising: determining a subset of electronic files associated with the case file; creating a physical representation of at least one electronic file of the subset; and associating the physical representation of the at least one electronic file with the first token.

6. The method of claim 1 further comprising: determining a subset of electronic files associated with the case file; creating a physical representation of at least one electronic file of the subset; and associating the physical representation of the at least one electronic file with the first token. 7. The method of claim 6 further comprising: creating a user profile identifying one or more preferred documents; and accessing the profile to determine the subset.

1. A method of machine translation, comprising: employing at least one processor configured to execute computer-executable instructions stored in memory to perform the following act: generating a translation for a sentence by determining word alignment, order, and selection jointly, rather than independently and incrementally, from output of multiple machine translation systems.

1. A method of machine translation, comprising: employing at least one processor configured to execute computer-executable instructions stored in memory to perform the following act: generating a translation for a sentence by determining word alignment, order, and selection jointly, rather than independently and incrementally, from output of multiple machine translation systems. 5. The method of claim 1 further comprising generating the translation as a function of distortion scoring between the output of multiple machine translation systems and correspondence set order.

5. The method of claim 2 , further comprising: editing the signal language video with a sign language video editing tool; and editing the DVS voice mixed with the original video with the sign language video editing tool, wherein the sign language video editing tool comprises a sign language video database, a player for playing the original video and a sign language video mixed with the original video, and a timeline area displayed through the player.

5. The method of claim 2 , further comprising: editing the signal language video with a sign language video editing tool; and editing the DVS voice mixed with the original video with the sign language video editing tool, wherein the sign language video editing tool comprises a sign language video database, a player for playing the original video and a sign language video mixed with the original video, and a timeline area displayed through the player. 8. The method of claim 5 , wherein editing the sign language video with the sign language video editing tool comprises: identifying a translated sign language video displayed by synchronizing with the original video; and editing the sign language video by comparing the sign language video with the caption.

8. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training, wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error from the knowledge graph representation, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed.

8. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training, wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error from the knowledge graph representation, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. 17. The system of claim 8 , wherein the language patterns comprise at least one of part-of-speech, syntactic role, and sentiment associated with the text data.

11. A word game device having an objective to form or find words, comprising: a playfield that includes a plurality of playing positions, wherein a playing position is used to display a character of an alphabet, wherein an initial set of alphabet characters are assigned to playing positions to form at least one game word, and wherein at least one game word is scrambled by having at least one character shifted into a position that does not lie along the same axis common to the other characters in the word, a microprocessor with a computer-readable medium encoded with a computer program to control the operation of the device, a plurality of switches to enable a player to interact with the device, a computer program segment that is responsive to the activation of a switch, and which implements means for replacing alphabet characters assigned to playing positions, and a computer program segment to determine if a game objective has been achieved.

11. A word game device having an objective to form or find words, comprising: a playfield that includes a plurality of playing positions, wherein a playing position is used to display a character of an alphabet, wherein an initial set of alphabet characters are assigned to playing positions to form at least one game word, and wherein at least one game word is scrambled by having at least one character shifted into a position that does not lie along the same axis common to the other characters in the word, a microprocessor with a computer-readable medium encoded with a computer program to control the operation of the device, a plurality of switches to enable a player to interact with the device, a computer program segment that is responsive to the activation of a switch, and which implements means for replacing alphabet characters assigned to playing positions, and a computer program segment to determine if a game objective has been achieved. 20. A word game device as recited in claim 11 , wherein said plurality of playing positions form a two-dimensional array.

1. A computer-implemented method, comprising: receiving, by a computing system, voice input that was captured by a microphone of a mobile computing device; interpreting, by the computing system, the voice input using a speech recognition system that is configured to convert the voice input to text; identifying, by the computing system, a portion of the voice input as being ambiguous due to the portion of the voice input being able to be represented by either of two or more homophones or homonyms; identifying, by the computing system, one or more geographic locations of the mobile computing device, the mobile computing device having received one or more wireless signals from one or more external transmitting devices and from which the mobile computing device was able to determine the one or more geographic locations; applying, by the computing system, the portion of the voice input that is able to be represented by either of the two or more homophones or homonyms to one or more rules that use the one or more geographic locations of the mobile computing device to select one of the two or more homophones or homonyms as a selected homophone or homonym that represents the portion of the voice input; and outputting, by the computing system and in response to the computing system having selected the one of the two or more homophones or homonyms as the selected homophone or homonym, the selected homophone or homonym to a computer application or computer service that is associated with the voice input.

1. A computer-implemented method, comprising: receiving, by a computing system, voice input that was captured by a microphone of a mobile computing device; interpreting, by the computing system, the voice input using a speech recognition system that is configured to convert the voice input to text; identifying, by the computing system, a portion of the voice input as being ambiguous due to the portion of the voice input being able to be represented by either of two or more homophones or homonyms; identifying, by the computing system, one or more geographic locations of the mobile computing device, the mobile computing device having received one or more wireless signals from one or more external transmitting devices and from which the mobile computing device was able to determine the one or more geographic locations; applying, by the computing system, the portion of the voice input that is able to be represented by either of the two or more homophones or homonyms to one or more rules that use the one or more geographic locations of the mobile computing device to select one of the two or more homophones or homonyms as a selected homophone or homonym that represents the portion of the voice input; and outputting, by the computing system and in response to the computing system having selected the one of the two or more homophones or homonyms as the selected homophone or homonym, the selected homophone or homonym to a computer application or computer service that is associated with the voice input. 8. The computer-implemented method of claim 1 , wherein outputting the selected homophone or homonym to the computer application or service that is associated with the voice input includes the computing system sending a transcription of the voice input, including text of the selected homophone or homonym, to the mobile computing device.

8. A system comprising: one or more server devices to: identify entity identifiers, where each of the entity identifiers is associated with a document that was selected, from a plurality of documents, based on a search query including a same variation of an entity name; determine whether a total quantity of selections of the document associated with a particular entity identifier, of the entity identifiers, is greater than a total quantity of selections of each of the documents associated with other ones of the entity identifiers; and store, based on a result of the determining, the same variation of the entity name in a first memory that is used for rewriting search queries or a second memory that is used for suggesting rewritten search queries, where the same variation of the entity name is stored in the second memory when the total quantity of selections of the document associated with the particular entity identifier is greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers, and where the same variation of the entity name is stored in the first memory when the total quantity of selections of the document associated with the particular entity identifier is substantially greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers.

8. A system comprising: one or more server devices to: identify entity identifiers, where each of the entity identifiers is associated with a document that was selected, from a plurality of documents, based on a search query including a same variation of an entity name; determine whether a total quantity of selections of the document associated with a particular entity identifier, of the entity identifiers, is greater than a total quantity of selections of each of the documents associated with other ones of the entity identifiers; and store, based on a result of the determining, the same variation of the entity name in a first memory that is used for rewriting search queries or a second memory that is used for suggesting rewritten search queries, where the same variation of the entity name is stored in the second memory when the total quantity of selections of the document associated with the particular entity identifier is greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers, and where the same variation of the entity name is stored in the first memory when the total quantity of selections of the document associated with the particular entity identifier is substantially greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers. 12. The system of claim 8 , where the one or more server devices are to: rewrite a search query using one of the first memory or the second memory, where, when rewriting the search query, the one or more server devices are further to: determine whether a term, included in the search query, matches a variation of a particular entity name stored in the first memory; rewrite, using the first memory, the search query into a rewritten search query that includes an entity identifier, in the first memory, associated with the variation of the particular entity name when the term matches the variation of the particular entity name in the first memory; and perform a search based on the rewritten search query instead of performing a search based on the search query.

1. A computer-implemented method of capturing and treating content using a computer system having a processor, memory, and data storage subsystems, the computer-implemented method comprising: setting a mode of operation to a content capture mode for interpreting user input for the purpose of selecting an on-screen region of a display, and receiving a path drawn by a user, the path defining boundaries of the selected on-screen region of the display, wherein pixels comprising one or more graphical elements representing a first set of one or more textual characters are displayed in the selected on-screen region; capturing the pixels displayed within the selected on-screen region, and storing the captured pixels in an image file; switching the mode of operation to an annotation mode in response to a user command; receiving an annotation drawn by the user on the display, wherein the received annotation is implemented using a plurality of tools via a toolbar, the toolbar appearing after the selecting an on-screen region; obtaining context information for the one or more graphical elements by automatically applying text recognition to the annotation, and storing the results of the text recognition as context information via the computer system, wherein certain context information comprises preventive measures that limit an association of history with the one or more graphical elements based upon digital rights management licenses, and obtaining additional context information by extracting the first set of one or more textual characters and extracting a second set of textual characters displayed in proximity with the first set, wherein the context information and the additional context information are automatically stored in association with the image file.

1. A computer-implemented method of capturing and treating content using a computer system having a processor, memory, and data storage subsystems, the computer-implemented method comprising: setting a mode of operation to a content capture mode for interpreting user input for the purpose of selecting an on-screen region of a display, and receiving a path drawn by a user, the path defining boundaries of the selected on-screen region of the display, wherein pixels comprising one or more graphical elements representing a first set of one or more textual characters are displayed in the selected on-screen region; capturing the pixels displayed within the selected on-screen region, and storing the captured pixels in an image file; switching the mode of operation to an annotation mode in response to a user command; receiving an annotation drawn by the user on the display, wherein the received annotation is implemented using a plurality of tools via a toolbar, the toolbar appearing after the selecting an on-screen region; obtaining context information for the one or more graphical elements by automatically applying text recognition to the annotation, and storing the results of the text recognition as context information via the computer system, wherein certain context information comprises preventive measures that limit an association of history with the one or more graphical elements based upon digital rights management licenses, and obtaining additional context information by extracting the first set of one or more textual characters and extracting a second set of textual characters displayed in proximity with the first set, wherein the context information and the additional context information are automatically stored in association with the image file. 3. The computer-implemented method of claim 1 , further comprising: creating and storing a linking structure as the association between the image file and the context information.

1. A method for increasing route accuracies, the method comprising: recording a waypoint while moving along a route; recording a positional-accuracy measurement for the recorded waypoint; calculating a position accuracy prediction (PAP) parameter for the recorded waypoint based on the recorded positional-accuracy measurement wherein the PAP parameter comprises a first weight value, a first confidence value, and an-a first error distance; and comparing, with a computer processor, the recorded waypoint and the calculated PAP parameter to a corpus waypoint and an associated corpus PAP parameter stored on a computer-based system, wherein the corpus PAP parameter comprises a second weight value, a second confidence value, and a second error distance, and wherein the comparing step comprises: calculating a weight average based on the first and second weight values; computationally extending the first error distance from the PAP parameter of the recorded waypoint to provide a first probability distribution circle; computationally extending the second error distance from the PAP parameter of the corpus waypoint to provide a second probability distribution circle; and computationally generating a vector line between the recorded waypoint and the corpus waypoint; and determining, with the computer processor, an updated waypoint along the vector line between the recorded waypoint and the corpus waypoint and within an overlapping area of the first and second probability distribution circles based on the calculated weight average.

1. A method for increasing route accuracies, the method comprising: recording a waypoint while moving along a route; recording a positional-accuracy measurement for the recorded waypoint; calculating a position accuracy prediction (PAP) parameter for the recorded waypoint based on the recorded positional-accuracy measurement wherein the PAP parameter comprises a first weight value, a first confidence value, and an-a first error distance; and comparing, with a computer processor, the recorded waypoint and the calculated PAP parameter to a corpus waypoint and an associated corpus PAP parameter stored on a computer-based system, wherein the corpus PAP parameter comprises a second weight value, a second confidence value, and a second error distance, and wherein the comparing step comprises: calculating a weight average based on the first and second weight values; computationally extending the first error distance from the PAP parameter of the recorded waypoint to provide a first probability distribution circle; computationally extending the second error distance from the PAP parameter of the corpus waypoint to provide a second probability distribution circle; and computationally generating a vector line between the recorded waypoint and the corpus waypoint; and determining, with the computer processor, an updated waypoint along the vector line between the recorded waypoint and the corpus waypoint and within an overlapping area of the first and second probability distribution circles based on the calculated weight average. 3. The method of claim 1 , wherein the recorded positional-accuracy measurement for the recorded waypoint is selected from the group consisting of GPS dilution of precision effects, GPS error distances, satellite signal to noise ratios, a number of satellites utilized, satellite configurations, and combinations thereof.

1. A computer-implemented method for performing formal verification of a circuit in view of low power design specification, the method comprising: receiving, by a computer processor, a request to perform formal verification of connectivity of a circuit representing an input/output ring of a system on chip, the circuit represented by a circuit design, the circuit comprising components and connections between components; receiving, by the computer processor, low power design specification for the circuit, the low power design specification describing power states for one or more power domains of the circuit; modifying, by the computer processor, the circuit design by introducing one or more isolation cells based on the low power design specification; generating, by the computer processor, combinational constraints based on the low power design specification, the combinational constraints representing valid power states of power domains of the circuit based on the low power design specification; receiving, by the computer processor, a set of assertions representing connectivity between components of the circuit, wherein a result of evaluation of an assertion is based on whether a component is connected to another component; performing, by the computer processor, formal verification of the modified circuit design based on the set of assertions representing connectivity between components of the circuit and the combinational constraints based on low power design specification; and determining, by the computer processor, whether the circuit has valid connectivity in view of the low power design specification based on the result of the formal verification, the result of the formal verification based on values of the assertions representing connectivity between components of the circuit.

1. A computer-implemented method for performing formal verification of a circuit in view of low power design specification, the method comprising: receiving, by a computer processor, a request to perform formal verification of connectivity of a circuit representing an input/output ring of a system on chip, the circuit represented by a circuit design, the circuit comprising components and connections between components; receiving, by the computer processor, low power design specification for the circuit, the low power design specification describing power states for one or more power domains of the circuit; modifying, by the computer processor, the circuit design by introducing one or more isolation cells based on the low power design specification; generating, by the computer processor, combinational constraints based on the low power design specification, the combinational constraints representing valid power states of power domains of the circuit based on the low power design specification; receiving, by the computer processor, a set of assertions representing connectivity between components of the circuit, wherein a result of evaluation of an assertion is based on whether a component is connected to another component; performing, by the computer processor, formal verification of the modified circuit design based on the set of assertions representing connectivity between components of the circuit and the combinational constraints based on low power design specification; and determining, by the computer processor, whether the circuit has valid connectivity in view of the low power design specification based on the result of the formal verification, the result of the formal verification based on values of the assertions representing connectivity between components of the circuit. 2. The computer-implemented method of claim 1 , wherein a combinational constraint based on low power design specification comprises a logical-and of individual constraints, each individual constraint representing valid power states of a power domain specified in the low power design specification.

1. A method for controlling an application based on a handwriting input, the method comprising: displaying a first screen on a touch screen display of a terminal; determining an occurrence of a communication event associated with an application, the communication event occurring while displaying the first screen; displaying a notification indicating the communication event on the touch screen display in response to the determination while displaying the first screen; activating, in response to the determination, a handwriting recognition module to recognize a handwriting input to be associated with the application when displaying the notification; receiving the handwriting input on the touch screen display of the terminal; recognizing the handwriting input received on the touch screen display of the terminal; determining a symbol corresponding to the handwriting input; associating the symbol with a function of the application; and processing the associated symbol through the application.

1. A method for controlling an application based on a handwriting input, the method comprising: displaying a first screen on a touch screen display of a terminal; determining an occurrence of a communication event associated with an application, the communication event occurring while displaying the first screen; displaying a notification indicating the communication event on the touch screen display in response to the determination while displaying the first screen; activating, in response to the determination, a handwriting recognition module to recognize a handwriting input to be associated with the application when displaying the notification; receiving the handwriting input on the touch screen display of the terminal; recognizing the handwriting input received on the touch screen display of the terminal; determining a symbol corresponding to the handwriting input; associating the symbol with a function of the application; and processing the associated symbol through the application. 9. The method of claim 1 , further comprising: displaying a first application associated with a number if the determined symbol includes the number without including a character; and displaying a second application associated with a character if the determined symbol includes the character.

9. A computer implemented process for modifying a schema implemented on a computer programmed to execute computer code comprising instructions to: obtain an original schema corresponding to an original database, said original schema comprising a field and an original field type selection; perform rule-based structural and semantic checking comprising checking fields and relationships of said original schema for data integrity due to based on at least one of nested structure denormalization, lookup tables that can hold an unlimited number of records, inspection of taxonomy defined on a non-main table, and augmenting a particular table of said original schema; determine at least one suggested field type based on said checking, wherein said at least one suggest field type is selected from a first field type of qualifier type, wherein said first field type of said qualifier type is a lookup into the records of a qualified table of a database comprising sparse data placed in said qualified table and eliminated from a primary table of said database, a second field type of multi-lingual type, wherein said second field type of multi-lingual type is associated with a targeted audience, wherein only data that is different with respect to a second audience is entered for said targeted audience in said database, and unentered values are inherited form data entered for said second audience in said database, and a third field type of calculation type, wherein said third field type of calculation type is configured to store calculated values of said third field type in memory at runtime and not in said database; accept a field type selection from said first field type, said second field type, and said third field type, wherein said field type selection is different from said original field type selection; generate a modified schema comprising said field and said field type selection based on said original schema and said at least one suggested field type, wherein said modified schema conforms to requirements of a master data management schema; and load said modified schema into a desired database, wherein said desired database comprises data from said original database, wherein said data is optimized based on said field type selection.

9. A computer implemented process for modifying a schema implemented on a computer programmed to execute computer code comprising instructions to: obtain an original schema corresponding to an original database, said original schema comprising a field and an original field type selection; perform rule-based structural and semantic checking comprising checking fields and relationships of said original schema for data integrity due to based on at least one of nested structure denormalization, lookup tables that can hold an unlimited number of records, inspection of taxonomy defined on a non-main table, and augmenting a particular table of said original schema; determine at least one suggested field type based on said checking, wherein said at least one suggest field type is selected from a first field type of qualifier type, wherein said first field type of said qualifier type is a lookup into the records of a qualified table of a database comprising sparse data placed in said qualified table and eliminated from a primary table of said database, a second field type of multi-lingual type, wherein said second field type of multi-lingual type is associated with a targeted audience, wherein only data that is different with respect to a second audience is entered for said targeted audience in said database, and unentered values are inherited form data entered for said second audience in said database, and a third field type of calculation type, wherein said third field type of calculation type is configured to store calculated values of said third field type in memory at runtime and not in said database; accept a field type selection from said first field type, said second field type, and said third field type, wherein said field type selection is different from said original field type selection; generate a modified schema comprising said field and said field type selection based on said original schema and said at least one suggested field type, wherein said modified schema conforms to requirements of a master data management schema; and load said modified schema into a desired database, wherein said desired database comprises data from said original database, wherein said data is optimized based on said field type selection. 14. The computer implemented process of claim 9 wherein said computer readable instruction code is further configured to: import at least one field defined with extensible markup language schema definition (XSD) from an external data source.

11. A printer comprising: memory of storing a print job; and a language translation module configured to distinguish text within the print job and translate the text from a first language into a second language, wherein the language translation module is operable to distinguish by recognizing data tags inserted into the print job, the data tags identifying the current language text or by parsing all data within the print job to differentiate the current language text from fixed data in the print job.

11. A printer comprising: memory of storing a print job; and a language translation module configured to distinguish text within the print job and translate the text from a first language into a second language, wherein the language translation module is operable to distinguish by recognizing data tags inserted into the print job, the data tags identifying the current language text or by parsing all data within the print job to differentiate the current language text from fixed data in the print job. 12. A printer as recited in claim 11 , further comprising: a print engine; and a controller configured to control the print engine for printing the print job as a printed document, the printed document comprising the text in the second language.

17. The computer program product of claim 13 , wherein the method further comprises: receiving an indication for at least one of the plurality of candidate terms as to its inclusion in a predetermined category.

17. The computer program product of claim 13 , wherein the method further comprises: receiving an indication for at least one of the plurality of candidate terms as to its inclusion in a predetermined category. 18. The computer program product of claim 17 , wherein the indication is received from a user.

4. A system for content targeted web advertisements, comprising: a web server coupled to a public network providing a plurality of web pages, each web page having associated content to display to a user; and a logic unit for targeting advertisements to a web page, the logic unit configured to identify a meaning of the associated content and then automatically serve content relevant advertisements with the web page, the logic unit further configured to select the served relevant advertisements from a plurality of relevant advertisements based on a search and ranking technologies to identify one or more words and/or phrases that reflect the associated content in the web page.

4. A system for content targeted web advertisements, comprising: a web server coupled to a public network providing a plurality of web pages, each web page having associated content to display to a user; and a logic unit for targeting advertisements to a web page, the logic unit configured to identify a meaning of the associated content and then automatically serve content relevant advertisements with the web page, the logic unit further configured to select the served relevant advertisements from a plurality of relevant advertisements based on a search and ranking technologies to identify one or more words and/or phrases that reflect the associated content in the web page. 7. The system as recited in claim 4 , wherein the search and ranking technologies to: index the associated content of the plurality of web pages; rank the indexed associated content of the plurality of web pages; and compare the ranked indexed associated content data to a set of indexed advertising data.

11. A computer-based system for facilitating a response to a user query, comprising: a) a query processor configured to perform actions including: i) receiving the user query; ii) generating an operator graph based on a data model; iii) translating the operator graph into a logical operator graph representing a composable SQL query that includes a plurality of sub-queries; iv) generating the composable SQL query based on the logical operator graph, the composable SQL query being remotable to a target data source; v) sending the composable SQL query to the target data source; and b) a response management component configured to perform actions including: i) a receiving a response set from the target data source; and ii) causing the response set to be sent to a client device by selectively streaming at least a portion of the response set to the client device.

11. A computer-based system for facilitating a response to a user query, comprising: a) a query processor configured to perform actions including: i) receiving the user query; ii) generating an operator graph based on a data model; iii) translating the operator graph into a logical operator graph representing a composable SQL query that includes a plurality of sub-queries; iv) generating the composable SQL query based on the logical operator graph, the composable SQL query being remotable to a target data source; v) sending the composable SQL query to the target data source; and b) a response management component configured to perform actions including: i) a receiving a response set from the target data source; and ii) causing the response set to be sent to a client device by selectively streaming at least a portion of the response set to the client device. 13. The computer-based system of claim 11 , further comprising a post-processing component that performs a post-processing operation on the response set only if the operation is not supported by the data source.

4. The system of claim 1 , wherein said search engine has a structure that supports creation of different types of approximation vectors based on a meta data property derived from the process of transformations.

4. The system of claim 1 , wherein said search engine has a structure that supports creation of different types of approximation vectors based on a meta data property derived from the process of transformations. 12. The system of claim 4 , wherein said encoding module creates an index based on a convergence distance, CD, wherein CD=Distance(Projection(Harr M (V))−Projection(Harr (M+1) (V)) is less than a smallest similarity bound.

1. A method for generating a list of recommended applications, comprising: receiving, by an application store server and from a first client device associated with a first user, a search term; determining, by the application store server, a plurality of applications that are associated with the search term; identifying, for at least one of the plurality of applications, a second user associated with a second client device on which the at least one of the plurality of applications is installed; computing, by the application store server and for the second user, a first score, the first score reflecting at least one of a degree of activity of the second user within a social media system or a degree of popularity of the second user within the social media system, the computing including: calculating, for a first category of social media usage data associated with the social media system, an average value of the first category of the social media usage data for a group of users of the social media system; and calculating a first quotient by dividing a value of the first category of the social media usage data associated with the second user by the average value of the first category, wherein the first category of the social media usage data comprises one of a degree of activity of a user within the social media system, a degree of popularity of the user within the social media system, a count of posts by the user within the social media system, a number of followers of the user within the social media system, a number of views of the posts by the user within the social media system, or a re-share of the posts by the user within the social media system; and generating, based on the first score, the list of recommended applications.

1. A method for generating a list of recommended applications, comprising: receiving, by an application store server and from a first client device associated with a first user, a search term; determining, by the application store server, a plurality of applications that are associated with the search term; identifying, for at least one of the plurality of applications, a second user associated with a second client device on which the at least one of the plurality of applications is installed; computing, by the application store server and for the second user, a first score, the first score reflecting at least one of a degree of activity of the second user within a social media system or a degree of popularity of the second user within the social media system, the computing including: calculating, for a first category of social media usage data associated with the social media system, an average value of the first category of the social media usage data for a group of users of the social media system; and calculating a first quotient by dividing a value of the first category of the social media usage data associated with the second user by the average value of the first category, wherein the first category of the social media usage data comprises one of a degree of activity of a user within the social media system, a degree of popularity of the user within the social media system, a count of posts by the user within the social media system, a number of followers of the user within the social media system, a number of views of the posts by the user within the social media system, or a re-share of the posts by the user within the social media system; and generating, based on the first score, the list of recommended applications. 8. The method of claim 1 , wherein the degree of popularity of the second user within the social media system comprises a number of followers, on at least one social network site, of the second user.

17. The method of claim 15 , wherein the price of each advertisement is computed by multiplying a maximum price that the advertiser is willing to pay for the advertisement by the value of the advertisement for the given user, where the value of the advertisement for the user is stored in a value matrix, thereby forming a vector of prices for each of the advertisements for the given user, the vector being sorted in descending order with higher ranking advertisements being presented first.

17. The method of claim 15 , wherein the price of each advertisement is computed by multiplying a maximum price that the advertiser is willing to pay for the advertisement by the value of the advertisement for the given user, where the value of the advertisement for the user is stored in a value matrix, thereby forming a vector of prices for each of the advertisements for the given user, the vector being sorted in descending order with higher ranking advertisements being presented first. 19. The method of claim 17 , wherein the price is a fixed price that the advertiser is willing to pay for presenting the advertisement to any of the users.

13. A system comprising: a computer having a computer input device and a display device connected thereto; and a plurality of distributed processors communicatively coupled to the computer wherein the computer is configured to coordinate the activities of the distributed processors, wherein each of the distributed processors is configured to maintain a case base, wherein each of the plurality of distributed processors are configured to perform a method including the steps of: providing a parent schema, generating a plurality of distinct and domain-specific instantiations of the parent schema, replacing one or more existing Boolean features in one or more cases of a case based reasoning system with the domain-specific instantiations of the parent schema, evolving non-zero weights for the cases including the domain-specific instantiations of the parent schema; user-validating at least two of the domain-specific instantiations of the parent schema, and creating a symmetric schema by combining the user-validated domain-specific instantiations of the parent schema.

13. A system comprising: a computer having a computer input device and a display device connected thereto; and a plurality of distributed processors communicatively coupled to the computer wherein the computer is configured to coordinate the activities of the distributed processors, wherein each of the distributed processors is configured to maintain a case base, wherein each of the plurality of distributed processors are configured to perform a method including the steps of: providing a parent schema, generating a plurality of distinct and domain-specific instantiations of the parent schema, replacing one or more existing Boolean features in one or more cases of a case based reasoning system with the domain-specific instantiations of the parent schema, evolving non-zero weights for the cases including the domain-specific instantiations of the parent schema; user-validating at least two of the domain-specific instantiations of the parent schema, and creating a symmetric schema by combining the user-validated domain-specific instantiations of the parent schema. 16. The system of claim 13 , wherein the parent schema contains more than one tractable search spaces.

17. A computer program product, tangibly embodied in a non-transitory computer-readable storage medium, the computer program product including instructions operable to cause a data processing apparatus of a client user input device to perform a method comprising: storing a local primary vocabulary at the client device, wherein the local primary vocabulary pertains to any of a language, a subject matter, a functional purpose, or a content; receiving a sequence of one or more symbols from a user through entry of a sequence of keypresses by the user; transmitting at least a most recent portion of the sequence over a network after each of the keypresses; updating the locally stored primary vocabulary from a corresponding remote vocabulary of a plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, when the transmitted portion of the sequence includes one or more words that overlaps both the corresponding remote vocabulary and the locally stored primary vocabulary; receiving a new vocabulary of the plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, wherein the new vocabulary pertains to a topic, when the new vocabulary includes a plurality of words that correspond to the topic, and wherein the transmitted most recent portion of the sequence includes one or more words that overlap the vocabulary, such that the new vocabulary has associated therewith a measure of confidence above a prescribed threshold with respect to the transmitted most recent portion of the sequence, wherein the transmitted most recent portion of the sequence significantly overlaps the new vocabulary while lacking significant overlaps with the locally stored primary vocabulary and others of the plurality of remote vocabularies, wherein receiving the new vocabulary comprises receiving a notice over the network that the new vocabulary is available that pertains to the transmitted sequence, and downloading the new vocabulary over the network in response to the received notice; locally storing the received new vocabulary at the client device; receiving text entered by the user; and for the received text, using the updated locally stored primary vocabulary or the locally stored new vocabulary for any of word prediction, completion, or word correction.

17. A computer program product, tangibly embodied in a non-transitory computer-readable storage medium, the computer program product including instructions operable to cause a data processing apparatus of a client user input device to perform a method comprising: storing a local primary vocabulary at the client device, wherein the local primary vocabulary pertains to any of a language, a subject matter, a functional purpose, or a content; receiving a sequence of one or more symbols from a user through entry of a sequence of keypresses by the user; transmitting at least a most recent portion of the sequence over a network after each of the keypresses; updating the locally stored primary vocabulary from a corresponding remote vocabulary of a plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, when the transmitted portion of the sequence includes one or more words that overlaps both the corresponding remote vocabulary and the locally stored primary vocabulary; receiving a new vocabulary of the plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, wherein the new vocabulary pertains to a topic, when the new vocabulary includes a plurality of words that correspond to the topic, and wherein the transmitted most recent portion of the sequence includes one or more words that overlap the vocabulary, such that the new vocabulary has associated therewith a measure of confidence above a prescribed threshold with respect to the transmitted most recent portion of the sequence, wherein the transmitted most recent portion of the sequence significantly overlaps the new vocabulary while lacking significant overlaps with the locally stored primary vocabulary and others of the plurality of remote vocabularies, wherein receiving the new vocabulary comprises receiving a notice over the network that the new vocabulary is available that pertains to the transmitted sequence, and downloading the new vocabulary over the network in response to the received notice; locally storing the received new vocabulary at the client device; receiving text entered by the user; and for the received text, using the updated locally stored primary vocabulary or the locally stored new vocabulary for any of word prediction, completion, or word correction. 21. The computer program product of claim 17 , wherein the received new vocabulary is based on any of a different language, a subject matter, a functional purposes, or a content.

17. The method of claim 12 , wherein a user triggers the invoking of the producer, converter and distributor methods upon selecting the output format and a distribution type for the data, and wherein the producer, converter and distributor methods are selected based on the selected output type and the selected distribution type.

17. The method of claim 12 , wherein a user triggers the invoking of the producer, converter and distributor methods upon selecting the output format and a distribution type for the data, and wherein the producer, converter and distributor methods are selected based on the selected output type and the selected distribution type. 18. The method of claim 17 , wherein the user selects the output format and the distribution type after specifying a reporting object to be used in retrieving the data from the one or more repositories.

1. A computer-implemented method comprising: (A) providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; (B) receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein (B) comprises: (B) (1) receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and (B)(2) receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and (C) generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Nature-related discriminant and one Realm-related discriminant, wherein Nature-related discriminants include a discriminant for distinguishing between individual and collective meanings in the natural language and a discriminant for distinguishing between specific and indefinite meanings in the natural language, and wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language.

1. A computer-implemented method comprising: (A) providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; (B) receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein (B) comprises: (B) (1) receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and (B)(2) receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and (C) generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Nature-related discriminant and one Realm-related discriminant, wherein Nature-related discriminants include a discriminant for distinguishing between individual and collective meanings in the natural language and a discriminant for distinguishing between specific and indefinite meanings in the natural language, and wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. 5. The method of claim 1 , wherein (C) comprises generating the data structure to include a plurality of fields, wherein each of the plurality of fields represents a corresponding one of the plurality of answers.

1. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identify a customer associated with the electronic customer communication data received by the server; analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface.

1. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identify a customer associated with the electronic customer communication data received by the server; analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface. 4. The method of claim 1 , wherein the third-party server is configured to provide one or more application programming interfaces (APIs) configured to integrate mobile-to-web extension applications.

1. A method for indexing digital video content maintained on a storage media item, the method comprising: extracting caption and subtitle content from one or more video object (“VOB”) files maintained on the storage media item; segmenting the extracted caption and subtitle content into one or more segments; extracting video and audio content corresponding to the one or more segments; generating one or more descriptions of the video and audio content corresponding to the segmented caption and subtitle content; and indexing the captions, subtitles, descriptions and corresponding video and audio content associated with the one or more segments of the one or more VOB files.

1. A method for indexing digital video content maintained on a storage media item, the method comprising: extracting caption and subtitle content from one or more video object (“VOB”) files maintained on the storage media item; segmenting the extracted caption and subtitle content into one or more segments; extracting video and audio content corresponding to the one or more segments; generating one or more descriptions of the video and audio content corresponding to the segmented caption and subtitle content; and indexing the captions, subtitles, descriptions and corresponding video and audio content associated with the one or more segments of the one or more VOB files. 11. The method of claim 1 wherein segmenting the extracted caption and subtitle content comprises identifying start and stop timestamps for a given segment.

8. The context inference system according to claim 1 , wherein the inference module comprises a soft computing clustering technique.

8. The context inference system according to claim 1 , wherein the inference module comprises a soft computing clustering technique. 9. The context inference system according to claim 8 , wherein the soft computing clustering technique is a self-organizing map (SOM) technique.

1. A method using a related searches database in conjunction with a search database of an online marketplace system, the method comprising: forming the related searches database, including using the search database, forming a list of uniform resource locators (URLs) associated with internet web sites to be accessed; removing duplicate URLs from the list; if a URL on the list is similar to another URL on the list, crawling a predetermined number of potentially duplicate URLs; comparing bodies of the URL on the list and the potentially duplicate URLs; if the body of the URL on the list is similar to the body of a potentially duplicate URL, suspending crawling of the potentially duplicate URLs, storing the body of the URL on the list in the related searches database for subsequent search, indexing at least the stored body of the URL to form related search listings in the related searches database; subsequently, receiving at the online marketplace system a search request from a searcher; in the search database, identifying search listings generating a match with the search request; in the related searches database, identifying related search listings relevant to the search request; and returning a search result list to the searcher including the identified search listings and one or more of the identified related search listings.

1. A method using a related searches database in conjunction with a search database of an online marketplace system, the method comprising: forming the related searches database, including using the search database, forming a list of uniform resource locators (URLs) associated with internet web sites to be accessed; removing duplicate URLs from the list; if a URL on the list is similar to another URL on the list, crawling a predetermined number of potentially duplicate URLs; comparing bodies of the URL on the list and the potentially duplicate URLs; if the body of the URL on the list is similar to the body of a potentially duplicate URL, suspending crawling of the potentially duplicate URLs, storing the body of the URL on the list in the related searches database for subsequent search, indexing at least the stored body of the URL to form related search listings in the related searches database; subsequently, receiving at the online marketplace system a search request from a searcher; in the search database, identifying search listings generating a match with the search request; in the related searches database, identifying related search listings relevant to the search request; and returning a search result list to the searcher including the identified search listings and one or more of the identified related search listings. 3. The method of claim 1 wherein comparing bodies of the URL on the list and the potentially duplicate URLs comprises: comparing text from the URL on the list and text from one potentially duplicate URL; and determining the URL on the list is similar to the one potentially duplicate URL when the text from the URL on the list and the text from the one potentially duplicate URL have a predetermined text portion in common.

1. A method implemented by a node for providing a service in a communication network, the method comprising the steps of: receiving a request; evaluating the request, wherein the request comprises an expression, the expression being a function of a plurality of elements, each element relating to data originating from one or more context sources available in the communication network, each of the one or more context sources having an associated context source weight for a query by the service; determining one context source from the one or more context sources for which an evaluation of the expression has a lowest expression evaluation weight, based on the associated context source weights for querying by the service, interrogating first the one context source determined to have the lowest expression evaluation weight; and wherein the expression comprises one or more intermediate expressions, the method further comprising iteratively determining a weight of evaluating the one or more intermediate expressions, until all elements relate only to data originating from the one or more context sources, wherein a lowest weight intermediate expression towards each of the context sources is determined for the expression until the expression elements comprise only context sources, at which point the context source to be interrogated first has been determined.

1. A method implemented by a node for providing a service in a communication network, the method comprising the steps of: receiving a request; evaluating the request, wherein the request comprises an expression, the expression being a function of a plurality of elements, each element relating to data originating from one or more context sources available in the communication network, each of the one or more context sources having an associated context source weight for a query by the service; determining one context source from the one or more context sources for which an evaluation of the expression has a lowest expression evaluation weight, based on the associated context source weights for querying by the service, interrogating first the one context source determined to have the lowest expression evaluation weight; and wherein the expression comprises one or more intermediate expressions, the method further comprising iteratively determining a weight of evaluating the one or more intermediate expressions, until all elements relate only to data originating from the one or more context sources, wherein a lowest weight intermediate expression towards each of the context sources is determined for the expression until the expression elements comprise only context sources, at which point the context source to be interrogated first has been determined. 10. The method according to claim 1 , in which a child expression is used by multiple parent expressions, and the weight for evaluating the child expression is shared between the multiple parent expressions when the associated requests are received simultaneously.

1. A computer-implementable method for implementing correlation-based visualization of a markup language messages, said computer-implementable method comprising: receiving an inbound markup language message over a network in response to an outbound markup language message sent over the network; applying a template to at least said inbound markup language message; utilizing at least one rule to visually identify correlated elements in said inbound markup language message and said outbound markup language message in a tree structure; and outputting said tree structure.

1. A computer-implementable method for implementing correlation-based visualization of a markup language messages, said computer-implementable method comprising: receiving an inbound markup language message over a network in response to an outbound markup language message sent over the network; applying a template to at least said inbound markup language message; utilizing at least one rule to visually identify correlated elements in said inbound markup language message and said outbound markup language message in a tree structure; and outputting said tree structure. 5. The computer-implementable method according to claim 1 , wherein said template further comprises an extensible markup language (XML) formatted set of rules based on a web-service specification implemented by said inbound and outbound markup language messages.

1. A computer-implemented process of authenticating a user requesting access to protected resource using credentials that are personalized using formatting options, the process comprising: using a computing device to perform the steps of: capturing credentials from the user which are formatted using formatting options, wherein the credentials comprise one or more of formatted user name, formatted password or formatted numerical PIN, and wherein the formatting options comprise Font, Font Size, Font Color, Shading, Font Style, Font Effects, Font Underline, and character effects; comparing the captured formatted credentials against formatted credentials stored on a server that are designated by the user as valid credentials prior to requesting access; flagging the captured credentials as valid and allowing the user to have access when the comparison indicates that a match occurs; flagging the captured credentials as invalid and rejecting the request for access when the comparison indicates that a match does not occur; alerting the user via alert communication methods chosen by the user including email, text message, voice message, voice call, SMS, audible alarm, or visual clues; and logging the user request and the steps performed by the computing device.

1. A computer-implemented process of authenticating a user requesting access to protected resource using credentials that are personalized using formatting options, the process comprising: using a computing device to perform the steps of: capturing credentials from the user which are formatted using formatting options, wherein the credentials comprise one or more of formatted user name, formatted password or formatted numerical PIN, and wherein the formatting options comprise Font, Font Size, Font Color, Shading, Font Style, Font Effects, Font Underline, and character effects; comparing the captured formatted credentials against formatted credentials stored on a server that are designated by the user as valid credentials prior to requesting access; flagging the captured credentials as valid and allowing the user to have access when the comparison indicates that a match occurs; flagging the captured credentials as invalid and rejecting the request for access when the comparison indicates that a match does not occur; alerting the user via alert communication methods chosen by the user including email, text message, voice message, voice call, SMS, audible alarm, or visual clues; and logging the user request and the steps performed by the computing device. 2. The process of claim 1 , wherein the protected resource is a software application, software service, website, web service, data, hardware device, mobile app, smartphone app, physical area, physical item, bank account, trading account, credit limit, monetary balance, reward points, computer device, or communication device.

1. A method for providing a contextual description of an object, the method comprising: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt, wherein at least one of the preceding actions is performed on at least one electronic hardware component.

1. A method for providing a contextual description of an object, the method comprising: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt, wherein at least one of the preceding actions is performed on at least one electronic hardware component. 7. The method of claim 1 further comprising: identifying a third object having a third attribute related to the second and first attributes, the third object having a third object type representing one of a place, an event and a person; selecting a third pre-defined phrase template corresponding to the third object type based on at least one of the first and second object types and on the first and second attributes; and dynamically combining the third pre-defined phrase template corresponding to the third object type with the first and second pre-defined phrase templates to form the linguistic prompt related to the place, event, or person representing the first object.

8. A tangible computer-readable medium storing instructions for controlling a computing device to generate a spoken language understanding module, the instructions comprising: a. selecting at least one predicate/argument pair as an intent from a set of the most frequent predicate/argument pairs for a domain associated with a spoken dialog system in a first language; b. labeling training data using mapping rules for the first language associated with the selected at least one predicate/argument pair and that specify rules for selecting a call-type label for an utterance; c. training a call-type classification model using the labeled training data; d. re-labeling the training data using the call-type classification model; and e. iteratively processing steps (c) and (d) until training set labels converge.

8. A tangible computer-readable medium storing instructions for controlling a computing device to generate a spoken language understanding module, the instructions comprising: a. selecting at least one predicate/argument pair as an intent from a set of the most frequent predicate/argument pairs for a domain associated with a spoken dialog system in a first language; b. labeling training data using mapping rules for the first language associated with the selected at least one predicate/argument pair and that specify rules for selecting a call-type label for an utterance; c. training a call-type classification model using the labeled training data; d. re-labeling the training data using the call-type classification model; and e. iteratively processing steps (c) and (d) until training set labels converge. 13. The tangible computer-readable medium of claim 8 , wherein selecting at least one predicate/argument pair further comprises generating mapping rules and for labeling the training data.

1. A method for obtaining query results on a wireless mobile device comprising the steps of: speaking a query to said wireless mobile device; converting, in said mobile device, said query into text; transmitting said text by said mobile device using a messaging protocol over a wireless network to a search engine; performing a search based on said text with said search engine; transmitting search results using said messaging protocol over said wireless network; formatting said search results; and displaying said search results on said wireless mobile device.

1. A method for obtaining query results on a wireless mobile device comprising the steps of: speaking a query to said wireless mobile device; converting, in said mobile device, said query into text; transmitting said text by said mobile device using a messaging protocol over a wireless network to a search engine; performing a search based on said text with said search engine; transmitting search results using said messaging protocol over said wireless network; formatting said search results; and displaying said search results on said wireless mobile device. 7. The method of claim 1 wherein said search results are transmitted from said search engine to an intermediary site and formatted at said intermediary site.

1. A method of annotating with a handheld electronic book reader, the method comprising: selecting a portion of an electronic document displayed in a handheld electronic book reader in response to user input directed to the portion of the electronic document, wherein the selected portion includes a passage from the electronic document; creating a context for a defined term in the electronic document by associating the selected portion of the electronic document with a definition for the defined term, wherein the selected portion that is selected in response to user input and that is associated with the definition for the defined term in the created context includes content other than the defined term to illustrate an exemplary usage of the defined term in practice; displaying the definition of the defined term in response to user input; and displaying the context in association with displaying the definition.

1. A method of annotating with a handheld electronic book reader, the method comprising: selecting a portion of an electronic document displayed in a handheld electronic book reader in response to user input directed to the portion of the electronic document, wherein the selected portion includes a passage from the electronic document; creating a context for a defined term in the electronic document by associating the selected portion of the electronic document with a definition for the defined term, wherein the selected portion that is selected in response to user input and that is associated with the definition for the defined term in the created context includes content other than the defined term to illustrate an exemplary usage of the defined term in practice; displaying the definition of the defined term in response to user input; and displaying the context in association with displaying the definition. 4. The method of claim 1 , wherein the defined term is associated with a plurality of contexts, wherein each of the plurality of contexts includes content selected in response to user input and other than the defined term to illustrate exemplary usages of the defined term in practice, the method further comprising selectively displaying multiple contexts associated with the defined term in association with displaying the definition.

13. The system of claim 1, wherein the system is trained on a sentence-aligned training text including a plurality of sentences in the source language and a plurality of sentences in the target language, wherein each sentence in the plurality of source language sentences is a translation of a corresponding sentence in the plurality of target language sentences, and a training portion of the system comprises: a word-alignment model for determining an alignment between the words of each of the plurality of source language sentences and the corresponding target language sentence; a fertility-context event accumulator for accumulating fertility-context events from the alignments determined by said word-alignment model for at least some occurrences of the source word in a source language sentence, each fertility-context event including a number of target language words that the source language word is aligned to, the source language word, and the context of the source-language word; a sense-context event accumulator for accumulating sense-context events from the alignments determined by said word-alignment model for at least some occurrences of the source word in a source language sentence, each sense-context event including the target word, the source-language word to which the target language word is aligned, and the context of the source-language word; and wherein said fertility model and said sense model are constructed using the fertility-context events and sense-context events accumulated by said fertility-context event accumulator and said sense-context event accumulator, respectively.

13. The system of claim 1, wherein the system is trained on a sentence-aligned training text including a plurality of sentences in the source language and a plurality of sentences in the target language, wherein each sentence in the plurality of source language sentences is a translation of a corresponding sentence in the plurality of target language sentences, and a training portion of the system comprises: a word-alignment model for determining an alignment between the words of each of the plurality of source language sentences and the corresponding target language sentence; a fertility-context event accumulator for accumulating fertility-context events from the alignments determined by said word-alignment model for at least some occurrences of the source word in a source language sentence, each fertility-context event including a number of target language words that the source language word is aligned to, the source language word, and the context of the source-language word; a sense-context event accumulator for accumulating sense-context events from the alignments determined by said word-alignment model for at least some occurrences of the source word in a source language sentence, each sense-context event including the target word, the source-language word to which the target language word is aligned, and the context of the source-language word; and wherein said fertility model and said sense model are constructed using the fertility-context events and sense-context events accumulated by said fertility-context event accumulator and said sense-context event accumulator, respectively. 17. The system of claim 13, wherein the training portion of the system further comprises: a target language pre-processor operatively coupled to said word-alignment model for pre-processing the plurality of sentences in the target language.

1. A dialogue system for the examination of a laser cutting operation which is carried out on a laser machine tool to establish a proposal for improving at least one quality feature of a subsequent laser cutting operation, the dialogue system comprising: input means through which an operator can identify the quality feature that is to be improved; and a proposal module that is configured to access stored expert knowledge, and to provide at least one proposal for improving the quality feature, wherein, to provide the at least one proposal, the proposal module is further configured to read data provided from a sensor system of the laser machine tool and image data of at least one laser cut edge of a processed metal sheet together with associated metal sheet material and processing data.

1. A dialogue system for the examination of a laser cutting operation which is carried out on a laser machine tool to establish a proposal for improving at least one quality feature of a subsequent laser cutting operation, the dialogue system comprising: input means through which an operator can identify the quality feature that is to be improved; and a proposal module that is configured to access stored expert knowledge, and to provide at least one proposal for improving the quality feature, wherein, to provide the at least one proposal, the proposal module is further configured to read data provided from a sensor system of the laser machine tool and image data of at least one laser cut edge of a processed metal sheet together with associated metal sheet material and processing data. 10. The dialogue system according to claim 1 , wherein at least one decision node of the stored expert knowledge is defined such that the proposal module at the decision node makes a decision at least based on data from a control program of the laser cutting operation which is carried out.

1. An apparatus for teaching and transcription of language which comprises: a substrate upon which a plurality of language elements are arranged in a rectangular matrix of rows and columns, wherein there exists a regular reoccurrence of a language element pattern of long quality vowels, short quality vowels and triad of consonants wherein said pattern is fully contained in either a row or a column in said matrix.

1. An apparatus for teaching and transcription of language which comprises: a substrate upon which a plurality of language elements are arranged in a rectangular matrix of rows and columns, wherein there exists a regular reoccurrence of a language element pattern of long quality vowels, short quality vowels and triad of consonants wherein said pattern is fully contained in either a row or a column in said matrix. 4. The apparatus of claim 1 wherein said plurality of language elements is arranged as follows: TBL ______________________________________ a --e a b ch d ee e f g h i --e i j k l le al m ng n o --e o p qu r ar er sh si s oo oo th th t u --e u v w x oy ow x y z ______________________________________

1. A method for translating electronic messages sent from a first party to a second different party, comprising: receiving at a destination location of the second different party an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein at the destination location of the second different party, the electronic message from the first party received at the destination location is translated and; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message.

1. A method for translating electronic messages sent from a first party to a second different party, comprising: receiving at a destination location of the second different party an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein at the destination location of the second different party, the electronic message from the first party received at the destination location is translated and; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message. 19. The method of claim 1 , further comprising: prompting the user with choices for translation.

1. A computer implemented method for voice entry of information, the method comprising: detecting a characteristic of an environment in which a voice input is generated; selecting a conversion rule responsive to the characteristic of the environment; applying, using a processor and a memory, the conversion rule to the voice input; generating an entry field input, wherein the conversion rule allows the voice input to be distinct from the entry field input, and wherein the voice input obfuscates the entry field input; and providing the entry field input to an application, wherein the entry field is usable to populate a data entry field in the application.

1. A computer implemented method for voice entry of information, the method comprising: detecting a characteristic of an environment in which a voice input is generated; selecting a conversion rule responsive to the characteristic of the environment; applying, using a processor and a memory, the conversion rule to the voice input; generating an entry field input, wherein the conversion rule allows the voice input to be distinct from the entry field input, and wherein the voice input obfuscates the entry field input; and providing the entry field input to an application, wherein the entry field is usable to populate a data entry field in the application. 15. The computer implemented method of claim 1 , wherein the voice input comprises at least one word, wherein the at least one word is accepted depending on a use of the at least one word in a previous voice input.

8. A computer program product comprising a non-transitory computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: aggregate news documents from one or more news sources; group the news documents into a plurality of news collections, each of the plurality of news collections including a sub-set of the news documents having related content; determine objects described by the plurality of news collections, the objects collectively forming a set of objects; determine an overall relevance of each of the plurality of news collections by determining a number of news sources in each of the plurality of news collections reporting on a related topic; determine a level of interest in the objects described by the plurality of news collections by determining a number of other news collections mentioning the objects and a number of search queries searching for information about the objects during a predetermined timeframe; determine a significance of the objects in the plurality of news collections by determining a number of times that the objects appear in titles of the news documents of the plurality of news collections, a centrality of the objects in the news documents of the plurality of news collections, the centrality of the objects being based on where the objects are mentioned in a body of the news documents, and a pertinence of events described by the plurality of news collections involving the objects; determine a relevance of each of the plurality of news collections with respect to the objects respectively described by the plurality of news collections, the relevance being based on the overall relevance of each of the plurality of news collections, the level of interest in the objects described by the plurality of news collections, and the significance of the objects in the plurality of news collections; and determine one or more news collections from the plurality of news collections to be associated with a first object included in the set of objects based on the relevance of the one or more news collections to the first object.

8. A computer program product comprising a non-transitory computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: aggregate news documents from one or more news sources; group the news documents into a plurality of news collections, each of the plurality of news collections including a sub-set of the news documents having related content; determine objects described by the plurality of news collections, the objects collectively forming a set of objects; determine an overall relevance of each of the plurality of news collections by determining a number of news sources in each of the plurality of news collections reporting on a related topic; determine a level of interest in the objects described by the plurality of news collections by determining a number of other news collections mentioning the objects and a number of search queries searching for information about the objects during a predetermined timeframe; determine a significance of the objects in the plurality of news collections by determining a number of times that the objects appear in titles of the news documents of the plurality of news collections, a centrality of the objects in the news documents of the plurality of news collections, the centrality of the objects being based on where the objects are mentioned in a body of the news documents, and a pertinence of events described by the plurality of news collections involving the objects; determine a relevance of each of the plurality of news collections with respect to the objects respectively described by the plurality of news collections, the relevance being based on the overall relevance of each of the plurality of news collections, the level of interest in the objects described by the plurality of news collections, and the significance of the objects in the plurality of news collections; and determine one or more news collections from the plurality of news collections to be associated with a first object included in the set of objects based on the relevance of the one or more news collections to the first object. 14. The computer program product of claim 8 , wherein to determine the overall relevance of each of the plurality of news collections includes determining a level of user interest in each of the plurality of news collections, and to determine the level of interest in the objects respectively described by the plurality of news collections includes determining a trend for each of the objects on one or more social networks during the predetermined timeframe.

11. A computer system comprising: a system for searching documents written in a plurality of languages, the system comprising at least one computer, wherein the searching is implemented using a method including: receiving a first query that includes at least one keyword in a first language; generating a second query by translating the at least one keyword into a second language; applying the first query against documents including at least one document written in the first language and at least one document written in the second language with the at least one keyword in the first language; applying the second query against documents written in the second language; generating a first set of results based on the first query, wherein the first set of results includes each document written in the first language that matches the first query; and generating a second set of results that includes each document written in the second language based on the first and second queries, wherein the second set of results matches at least one of the first query or the second query.

11. A computer system comprising: a system for searching documents written in a plurality of languages, the system comprising at least one computer, wherein the searching is implemented using a method including: receiving a first query that includes at least one keyword in a first language; generating a second query by translating the at least one keyword into a second language; applying the first query against documents including at least one document written in the first language and at least one document written in the second language with the at least one keyword in the first language; applying the second query against documents written in the second language; generating a first set of results based on the first query, wherein the first set of results includes each document written in the first language that matches the first query; and generating a second set of results that includes each document written in the second language based on the first and second queries, wherein the second set of results matches at least one of the first query or the second query. 14. The system of claim 11 , the method further including determining a native language of a user.

9. The interface of claim 8 , wherein the predetermined user input triggers include user selecting one of the set of tone marks associated with the phonetic alphabet on the second key plane.

9. The interface of claim 8 , wherein the predetermined user input triggers include user selecting one of the set of tone marks associated with the phonetic alphabet on the second key plane. 10. The interface of claim 9 , wherein the predetermined user input triggers include user deleting a last-entered tone mark in a text input stream while the first key plane is being presented.

6. A method for recognizing a spoken word in the presence of a voice message generated by voice processing system, the voice processing system having a speech recognizer, comprising the steps of: (a) echo cancelling the voice message and any detected speech signal to produce a residual signal; (b) continuously storing a portion of the residual signal that has been most recently echo cancelled; (c) processing the residual signal to detect a first portion of the spoken word; (d) upon detection of the first portion of the spoken word, retaining the stored portion of the residual signal including the first portion of the spoken word that has been most recently processed at the time of such detection, ceasing the voice message, stopping echo cancelling of the voice message and any detected speech signal and initiating speech recognition of a second portion of the spoken word; (e) thereafter initiating speech recognition of the first portion of the spoken word retained upon detection of the first portion of the spoken word; and (f) combining results of the recognition effected in steps (d) and (e) to determine the spoken word.

6. A method for recognizing a spoken word in the presence of a voice message generated by voice processing system, the voice processing system having a speech recognizer, comprising the steps of: (a) echo cancelling the voice message and any detected speech signal to produce a residual signal; (b) continuously storing a portion of the residual signal that has been most recently echo cancelled; (c) processing the residual signal to detect a first portion of the spoken word; (d) upon detection of the first portion of the spoken word, retaining the stored portion of the residual signal including the first portion of the spoken word that has been most recently processed at the time of such detection, ceasing the voice message, stopping echo cancelling of the voice message and any detected speech signal and initiating speech recognition of a second portion of the spoken word; (e) thereafter initiating speech recognition of the first portion of the spoken word retained upon detection of the first portion of the spoken word; and (f) combining results of the recognition effected in steps (d) and (e) to determine the spoken word. 7. The method as described in claim 6 further including the step of detecting completion of the spoken word prior to initiating speech recognition of the retained first portion of the spoken word.

1. A computer-implemented system that facilitates associating a shape on a diagram with an associated underlying type, comprising at least one processor that executes the following computer-executable components: a component that receives a data representation diagram file that comprises at least one shape; and an association component that performs a search among a plurality of types in one or more source code files for a type that corresponds to the shape based on a respective hash value associated with an original type related with the shape such that the association component associates the type to the shape within the data representation diagram file, wherein the respective hash value is a comparison between a hash value constructed from one or more member names of the type that the shape is associated to when the data representation diagram file is saved and a hash value for one or more types in either a substantially similar file or a substantially similar namespace as the original source code file for the type.

1. A computer-implemented system that facilitates associating a shape on a diagram with an associated underlying type, comprising at least one processor that executes the following computer-executable components: a component that receives a data representation diagram file that comprises at least one shape; and an association component that performs a search among a plurality of types in one or more source code files for a type that corresponds to the shape based on a respective hash value associated with an original type related with the shape such that the association component associates the type to the shape within the data representation diagram file, wherein the respective hash value is a comparison between a hash value constructed from one or more member names of the type that the shape is associated to when the data representation diagram file is saved and a hash value for one or more types in either a substantially similar file or a substantially similar namespace as the original source code file for the type. 6. The system of claim 1 , the data representation diagram file relates to a class designer modeling tool.

17. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: extract a plurality of elements in a Structured Query Language (SQL) statement; calculate a score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements, wherein the computer readable program to calculate the score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements further causes the computing device to: determine the score of the SQL statement as a first value in response to that the correlation relation does not exist between any two of the plurality of elements, the first value being a maximum one of the respective base scores of the plurality of elements; and determine the score of the SQL statement as a second value in response to that the correlation relation exists between at least two of the plurality of elements, the second value being greater than the maximum one of the respective base scores of the plurality of elements; and determine the criticality of the SQL statement based on the score of the SQL statement.

17. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: extract a plurality of elements in a Structured Query Language (SQL) statement; calculate a score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements, wherein the computer readable program to calculate the score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements further causes the computing device to: determine the score of the SQL statement as a first value in response to that the correlation relation does not exist between any two of the plurality of elements, the first value being a maximum one of the respective base scores of the plurality of elements; and determine the score of the SQL statement as a second value in response to that the correlation relation exists between at least two of the plurality of elements, the second value being greater than the maximum one of the respective base scores of the plurality of elements; and determine the criticality of the SQL statement based on the score of the SQL statement. 18. The computer program product of claim 17 , wherein the plurality of elements include at least one of a table and a field in a database which the SQL statement is directed at, and an action to be executed by the SQL statement.

1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document.

1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. 19. The method of claim 1 , wherein at least one writing profile representation comprises at least one writing variant of an example of at least one type of written information.

1. A computer-implemented method comprising: receiving, at a server and from a mobile device, a request including a speech data representation of an utterance or feature data extracted from the speech data representation of the utterance; obtaining, by the server, a transcription of the utterance by applying a speech recognition model to the speech data representation of the utterance or the feature data extracted from the speech data representation of the utterance; identifying, by the server, a keyword based on the transcription of the utterance; and initiating a communication between the mobile device and another device based on the identified keyword.

1. A computer-implemented method comprising: receiving, at a server and from a mobile device, a request including a speech data representation of an utterance or feature data extracted from the speech data representation of the utterance; obtaining, by the server, a transcription of the utterance by applying a speech recognition model to the speech data representation of the utterance or the feature data extracted from the speech data representation of the utterance; identifying, by the server, a keyword based on the transcription of the utterance; and initiating a communication between the mobile device and another device based on the identified keyword. 7. The method of claim 1 , wherein obtaining, by the server, a transcription of the utterance by applying a speech recognition model to the speech data representation of the utterance or the feature data extracted from the speech data representation of the utterance, comprises: performing automated speech recognition of the utterance using the speech recognition model to generate the transcription of the utterance.

1. A method in a computer system for adjusting an author authority measure of a distinguished author on a topic for a current period that is preceded by earlier periods, comprising the steps of: identifying articles posted by the distinguished author on the topic during the current and earlier periods; identifying stakeholder authors that cited or posted articles on the topic during the current or earlier periods; for each identified stakeholder author, determining in the computer system whether the stakeholder author cites during the current period an identified article posted by the distinguished author; adjusting in the computing system the author authority measure of the distinguished author on the topic based at least upon whether the stakeholder author cites during the current period an identified article posted by the distinguished author and whether the distinguished author published an article during the earlier period; before adjusting the author authority measure for the current period, initializing the author authority measure for the current period based at least upon the author authority measure for the latest earlier period; and if the distinguished author has published on the topic during the current period, adjusting the author authority measure to reflect an increase in authority; wherein adjusting the author authority measure of the distinguished author on the topic based at least upon whether the stakeholder cites during the current period an identified article posted by the distinguished author for each author identified as a stakeholder includes increasing the author's authority measure if the stakeholder cites during the current period an identified article and decreasing the author's authority measure if the stakeholder does not cite during the current period the identified article.

1. A method in a computer system for adjusting an author authority measure of a distinguished author on a topic for a current period that is preceded by earlier periods, comprising the steps of: identifying articles posted by the distinguished author on the topic during the current and earlier periods; identifying stakeholder authors that cited or posted articles on the topic during the current or earlier periods; for each identified stakeholder author, determining in the computer system whether the stakeholder author cites during the current period an identified article posted by the distinguished author; adjusting in the computing system the author authority measure of the distinguished author on the topic based at least upon whether the stakeholder author cites during the current period an identified article posted by the distinguished author and whether the distinguished author published an article during the earlier period; before adjusting the author authority measure for the current period, initializing the author authority measure for the current period based at least upon the author authority measure for the latest earlier period; and if the distinguished author has published on the topic during the current period, adjusting the author authority measure to reflect an increase in authority; wherein adjusting the author authority measure of the distinguished author on the topic based at least upon whether the stakeholder cites during the current period an identified article posted by the distinguished author for each author identified as a stakeholder includes increasing the author's authority measure if the stakeholder cites during the current period an identified article and decreasing the author's authority measure if the stakeholder does not cite during the current period the identified article. 12. The method of claim 1 including limiting the author authority measure to a predefined range by applying a sigmoid function.

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

9. The method of claim 7 further comprising: dynamically providing the at least one local suggested tag and/or the at least one external suggested tag for the at least one first file to the user via the computing interface in response to the one or more inputs by repeating the acts of determining based on additional inputs provided by the user. 11. The method of claim 9 further comprising: employing machine learning to facilitate in determining the at least one local suggested tag and/or the at least one external suggested tag.

1. A system, comprising: a memory operable to store one or more classification rules; and a processor communicatively coupled to the memory and operable to: retrieve one or more data elements from a data source; identify a structured data element among the one or more data elements; parse the structured data element using one or more filter processes to produce a plurality of tokens; classify the plurality of tokens based at least in part on the one or more classification rules and an ontology, the ontology comprising a plurality of concepts and a plurality of relationships between the concepts; identify a conflict between a first classified token and a second classified token; resolve the conflict by evaluating the first and second classified tokens based at least in part on the ontology; and generate a knowledge assertion comprising the plurality of classified tokens and one or more relationships between the classified tokens.

1. A system, comprising: a memory operable to store one or more classification rules; and a processor communicatively coupled to the memory and operable to: retrieve one or more data elements from a data source; identify a structured data element among the one or more data elements; parse the structured data element using one or more filter processes to produce a plurality of tokens; classify the plurality of tokens based at least in part on the one or more classification rules and an ontology, the ontology comprising a plurality of concepts and a plurality of relationships between the concepts; identify a conflict between a first classified token and a second classified token; resolve the conflict by evaluating the first and second classified tokens based at least in part on the ontology; and generate a knowledge assertion comprising the plurality of classified tokens and one or more relationships between the classified tokens. 4. The system of claim 1 , wherein the processor is further operable to: identify an unstructured data element among the one or more data elements; parse the unstructured data element to produce a second plurality of tokens; and return the second plurality of tokens and source information for inclusion in a search index.

1. A method comprising: receiving one or more data-content-object share indications, the one or more data-content-object share indications indicating that one or more data content objects has been shared with a first user of a first client device by one or more other users at one or more other client devices, the one or more data content objects being stored in one or more data stores; in response to receiving the one or more data-content-object share indications, generating one or more share notifications, each of the one or more share indications identifying at least one of the one or more data content objects indicated by the one or more data-content-object share indications and identifying at least one of the one or more other users; receiving one or more data-content-object edit indications, the one or more data-content-object edit indications identifying one or more edits to the one or more data content objects by the one or more other users at the one or more other client devices; in response to receiving the one or more data-content-object edit indications, generating one or more edit notifications, each of the one or more edit notifications identifying the one or more data content objects identified by the data-content-object edit indications; receiving one or more messages from the one or more other users for the first user of the first client device; presenting a dashboard on the first client device, the dashboard dedicated to the first user and providing a portal to the one or more data content objects shared by the one or more other users with the first user, the dashboard including a first row or column dedicated for displaying the one or more share notifications, a second row or column different than the first row or column and dedicated for displaying the one or more edit notifications, and a third row or column different than the first row or column and different than the second row or column and dedicated for displaying the one or more messages, wherein the first row or column, the second row or column, and the third row or column are displayed simultaneously on the dashboard; and enabling the first user to remove a particular share notification from the first row or column, a particular edit notification from the second row or column, and a particular message from the third row or column.

1. A method comprising: receiving one or more data-content-object share indications, the one or more data-content-object share indications indicating that one or more data content objects has been shared with a first user of a first client device by one or more other users at one or more other client devices, the one or more data content objects being stored in one or more data stores; in response to receiving the one or more data-content-object share indications, generating one or more share notifications, each of the one or more share indications identifying at least one of the one or more data content objects indicated by the one or more data-content-object share indications and identifying at least one of the one or more other users; receiving one or more data-content-object edit indications, the one or more data-content-object edit indications identifying one or more edits to the one or more data content objects by the one or more other users at the one or more other client devices; in response to receiving the one or more data-content-object edit indications, generating one or more edit notifications, each of the one or more edit notifications identifying the one or more data content objects identified by the data-content-object edit indications; receiving one or more messages from the one or more other users for the first user of the first client device; presenting a dashboard on the first client device, the dashboard dedicated to the first user and providing a portal to the one or more data content objects shared by the one or more other users with the first user, the dashboard including a first row or column dedicated for displaying the one or more share notifications, a second row or column different than the first row or column and dedicated for displaying the one or more edit notifications, and a third row or column different than the first row or column and different than the second row or column and dedicated for displaying the one or more messages, wherein the first row or column, the second row or column, and the third row or column are displayed simultaneously on the dashboard; and enabling the first user to remove a particular share notification from the first row or column, a particular edit notification from the second row or column, and a particular message from the third row or column. 5. The method of claim 1 , wherein the dashboard includes a count section, the count section being for displaying a count of the number of notifications in each row or column.

11. An apparatus comprising: a processor; and program code configured to be executed by the processor to optimize a database query, the program code configured to analyze a database query to determine when a predicate structure in the query is a candidate for a symbol table only data structure by analyzing at least one of a query syntax, system generated predicates, and requisite statistics of the database query, analyze the predicate structure to determine when the predicate structure is already encompassed by an encoded vector index, and generate the symbol table only data structure for at least one column in a database table without generating a corresponding vector data structure from an encoded vector index when the predicate structure is a candidate and not encompassed by an encoded vector index.

11. An apparatus comprising: a processor; and program code configured to be executed by the processor to optimize a database query, the program code configured to analyze a database query to determine when a predicate structure in the query is a candidate for a symbol table only data structure by analyzing at least one of a query syntax, system generated predicates, and requisite statistics of the database query, analyze the predicate structure to determine when the predicate structure is already encompassed by an encoded vector index, and generate the symbol table only data structure for at least one column in a database table without generating a corresponding vector data structure from an encoded vector index when the predicate structure is a candidate and not encompassed by an encoded vector index. 15. The apparatus of claim 11 wherein the program code is configured to generate the symbol table only data structure when manually triggered by a user.

6. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform a method comprising: generating a XSL (Extensible Stylesheet Language) Transformations (XSLT) and Extensible Markup Language (XML) Path Language (XPath) execution tree for a source XSLT stylesheet; determining one or more optimizations for the XSLT and)(Path execution tree, the determining one or more optimizations for the XSLT and)(Path execution tree comprising profiling with sample data, identifying one or more hot-spot execution instruction nodes, and identifying one or more patterns for optimization for the one or more identified hot-spot execution instruction nodes, the identifying one or more hot-spot execution instruction nodes comprising, for each instruction in the execution tree, analyzing time and count values compared to threshold values, and selecting instructions for further analysis if predetermined conditions are fulfilled; applying the one or more optimizations to the XSLT and)(Path execution tree; verifying the one or more optimizations in the XSLT and)(Path execution tree; making the verified one or more optimizations persistent in an optimized source XSLT stylesheet; and transforming one or more source XML, documents into one or more result documents using the optimized source XSLT stylesheet.

6. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform a method comprising: generating a XSL (Extensible Stylesheet Language) Transformations (XSLT) and Extensible Markup Language (XML) Path Language (XPath) execution tree for a source XSLT stylesheet; determining one or more optimizations for the XSLT and)(Path execution tree, the determining one or more optimizations for the XSLT and)(Path execution tree comprising profiling with sample data, identifying one or more hot-spot execution instruction nodes, and identifying one or more patterns for optimization for the one or more identified hot-spot execution instruction nodes, the identifying one or more hot-spot execution instruction nodes comprising, for each instruction in the execution tree, analyzing time and count values compared to threshold values, and selecting instructions for further analysis if predetermined conditions are fulfilled; applying the one or more optimizations to the XSLT and)(Path execution tree; verifying the one or more optimizations in the XSLT and)(Path execution tree; making the verified one or more optimizations persistent in an optimized source XSLT stylesheet; and transforming one or more source XML, documents into one or more result documents using the optimized source XSLT stylesheet. 7. A program storage device of claim 6 wherein profiling with sample data comprises transforming data a non-empty set of input files with data considered representative of actual data with hit-count profiling enabled in multiple passes; and summarizing the profile data of each of the multiple passes.

9. A method for performing a search for a resource in a virtual universe using selectable and modifiable user context objects, comprising: presenting a plurality of user context objects determined for an avatar that is online in the virtual universe, wherein the presenting of the plurality of user context objects to the avatar includes deriving the plurality of user context objects from all of the following: inventory items belonging to the avatar, teleportation history of the avatar, motion history of the avatar and social tagging behavior exhibited by a user of the avatar in the real world; receiving a user context object selection from the avatar, wherein the user context object selection contains one of the plurality of user context objects determined for the avatar and any desired modifications made to the selected user context object; receiving a query from the avatar; and performing a resource search for the query in accordance with the selected user context object; and providing results from the search to a robot avatar that is configured to allow the avatar to interact anonymously and semi-autonomously within the virtual universe in response to a modification made by the avatar to the selected user context object.

9. A method for performing a search for a resource in a virtual universe using selectable and modifiable user context objects, comprising: presenting a plurality of user context objects determined for an avatar that is online in the virtual universe, wherein the presenting of the plurality of user context objects to the avatar includes deriving the plurality of user context objects from all of the following: inventory items belonging to the avatar, teleportation history of the avatar, motion history of the avatar and social tagging behavior exhibited by a user of the avatar in the real world; receiving a user context object selection from the avatar, wherein the user context object selection contains one of the plurality of user context objects determined for the avatar and any desired modifications made to the selected user context object; receiving a query from the avatar; and performing a resource search for the query in accordance with the selected user context object; and providing results from the search to a robot avatar that is configured to allow the avatar to interact anonymously and semi-autonomously within the virtual universe in response to a modification made by the avatar to the selected user context object. 13. The method according to claim 9 , further comprising using avatar selections in response to a presentation of query search results as training data to identify further user contexts, associated attributes and values for use in future queries.

11. A method of improving a readability of an automatically machine-generated summary, including: identifying each document segment generated as part of an initial summary of a given textual document; calculating a correlation degree between each of the document segments which has been identified within initial summary and each of their respective neighboring document segments that are outside of the initial summary; adding the neighboring document segments with a correlation degree above defined threshold, to the initial summary of the given textual document; and creating a final summary of the given textual document based on the initial summary and the neighboring document segments that have been added to the initial summary.

11. A method of improving a readability of an automatically machine-generated summary, including: identifying each document segment generated as part of an initial summary of a given textual document; calculating a correlation degree between each of the document segments which has been identified within initial summary and each of their respective neighboring document segments that are outside of the initial summary; adding the neighboring document segments with a correlation degree above defined threshold, to the initial summary of the given textual document; and creating a final summary of the given textual document based on the initial summary and the neighboring document segments that have been added to the initial summary. 15. The method of claim 11 , wherein if the document segment is a sentence, the correlation degree between the sentence and a neighboring sentence is determined based on the correlation degrees between words in the sentence and words in the neighboring sentence.

19. A linguistic recognition method, the method comprising: building a database; receiving a language input by a user; recognizing a character from the input language; and recognizing a word by stochastically inferring the word or a sentence based on stored common linguistic model data and individual linguistic model data from the recognized character, wherein the database comprises: the common linguistic model data configured to stochastically infer the word or the sentence from the character acquired by recognizing a language input by the user, and the individual linguistic model data configured to stochastically infer an individual use word or an individual use sentence related to the user by collecting recognition-related information through one or more client devices used by the user after storing the common linguistic data and analyzing the collected recognition-related information, and wherein the individual use word is excluded from the common linguistic model data.

19. A linguistic recognition method, the method comprising: building a database; receiving a language input by a user; recognizing a character from the input language; and recognizing a word by stochastically inferring the word or a sentence based on stored common linguistic model data and individual linguistic model data from the recognized character, wherein the database comprises: the common linguistic model data configured to stochastically infer the word or the sentence from the character acquired by recognizing a language input by the user, and the individual linguistic model data configured to stochastically infer an individual use word or an individual use sentence related to the user by collecting recognition-related information through one or more client devices used by the user after storing the common linguistic data and analyzing the collected recognition-related information, and wherein the individual use word is excluded from the common linguistic model data. 20. The method according to claim 19 , wherein the individual linguistic model data is acquired by at least one of analyzing an individual unique language pattern, analyzing user member group language pattern, and analyzing a real-time word on the World Wide Web.

9. A system for message publication feedback in a publish/subscribe messaging environment, comprising: a computer comprising a processor; and instructions which are executable, using the processor, to implement functions comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic; selecting, by the message broker from a plurality of registered message subscribers that have registered subscriptions with the message broker to receive published messages, each subscription specifying a topic and an importance level for receiving published messages having the registered topic associated therewith, at least one subscriber for which the registered topic matches the topic associated with the published message; sending the published message from the message broker to each of the at least one selected subscriber; forwarding the published message, by the message broker, to each of at least one additional message broker to which the message broker is communicably coupled in a cluster environment, each additional message broker having a plurality of registered message subscribers that have registered subscriptions therewith to receive published messages, each registered subscription specifying a topic and an importance level for receiving published messages having the registered topic associated therewith; receiving, at the message broker from each of the at least one additional message brokers, feedback regarding sending of the forwarded message by the additional message broker to selected ones of the subscribers registered therewith responsive to the registered topic matching the topic associated with the forwarded message; and consolidating the feedback received from each of the at least one additional message brokers with feedback regarding the sending of the published message from the message broker to the each of the at least one selected subscriber; and sending, from the message broker to the message publisher, the consolidated feedback.

9. A system for message publication feedback in a publish/subscribe messaging environment, comprising: a computer comprising a processor; and instructions which are executable, using the processor, to implement functions comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic; selecting, by the message broker from a plurality of registered message subscribers that have registered subscriptions with the message broker to receive published messages, each subscription specifying a topic and an importance level for receiving published messages having the registered topic associated therewith, at least one subscriber for which the registered topic matches the topic associated with the published message; sending the published message from the message broker to each of the at least one selected subscriber; forwarding the published message, by the message broker, to each of at least one additional message broker to which the message broker is communicably coupled in a cluster environment, each additional message broker having a plurality of registered message subscribers that have registered subscriptions therewith to receive published messages, each registered subscription specifying a topic and an importance level for receiving published messages having the registered topic associated therewith; receiving, at the message broker from each of the at least one additional message brokers, feedback regarding sending of the forwarded message by the additional message broker to selected ones of the subscribers registered therewith responsive to the registered topic matching the topic associated with the forwarded message; and consolidating the feedback received from each of the at least one additional message brokers with feedback regarding the sending of the published message from the message broker to the each of the at least one selected subscriber; and sending, from the message broker to the message publisher, the consolidated feedback. 10. The system according to claim 9 , wherein the feedback regarding the sending of the published message from the message broker to the each of the at least one selected subscriber comprises, for each of the at least one selected subscriber, a subscriber identifier that identifies the subscriber and the importance level specified in the registered subscription of the subscriber.

31. The method of claim 1, wherein said step of executing the executable object code further comprises: dynamically allocating an object in dynamic memory; and creating one or more data structures for said dynamically allocated object.

31. The method of claim 1, wherein said step of executing the executable object code further comprises: dynamically allocating an object in dynamic memory; and creating one or more data structures for said dynamically allocated object. 34. The method of claim 31, wherein said step of executing the executable object code further comprises: monitoring a pointer into dynamic memory being cast to a non-void type; recording said non-void type information into said one or more data structures; creating one or more additional data structures if said non-void type is an aggregate data item.