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7. The method of claim 6 , wherein identifying the at least one collaborator comprises providing the user with a name, qualifications or institution of the at least one collaborator.

6. The method of claim 1 , further comprising providing, by the system server, the selected subset of the plurality of files to a user that selects the first file.

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16. The system of claim 15 , wherein the instructions, when executed by the one or more processing units, cause the one or more processing units to: identify the new lexicon term by parsing a particular query that the users submitted to retrieve the second documents.

15. A system comprising: one or more processing units; and memory comprising instructions which, when executed by the one or more processing units, cause the one or more processing units to: access a query log reflecting queries that users have submitted to a search engine to retrieve documents; identify, in the query log, first documents that were returned by the search engine in response to users submitting lexicon terms to the search engine, the lexicon terms being identified by a lexicon as members of particular query domain; extract a document pattern from the first documents that were returned by the search engine in response to the users submitting the lexicon terms to the search engine; and use the extracted document pattern to expand the lexicon by: identifying, in the query log, second documents that include the extracted document pattern and that the query log does not indicate were retrieved by submitting the lexicon terms to the search engine; identifying, in the query log, another member of the particular query domain that the users have submitted to the search engine to retrieve the second documents; and adding the another member of the particular query domain to the lexicon as a new lexicon term.

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7. The process of claim 5 , wherein the search query is constructed using all or a part of the URL string of the document.

5. The process of claim 2 , wherein the search query is constructed using a Uniform Resource Locator (URL) corresponding to a user-supplied document or a document a user is accessing.

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1. A computer implemented method of automatically solving simultaneous parameterized equations of context qualified types for solution elements comprising: 1) other context qualified types implied by equation parameters, 2) code instances of said context qualified types and 3) type difference transformations that redesign instances of code from one design context specified by one context qualified type to a second design context specified by a second context qualified type, where said solution elements are used to automatically redesign, synchronize and integrate separate code components or precursors thereof into an integrated, synchronized solution code component, where each one of said separate code components achieves a portion of a desired computation and said integrated, synchronized solution code component achieves all portions of said desired computation, wherein an atomic context qualified type is a composition of a programming language data type and a set of qualifiers for said programming language data type, where said set of qualifiers express human oriented conceptual notions that are not expressible in terms of programming language constructs or data types, wherein a composite context qualified type is expressed as a composition of a context qualified type constructor applied to other atomic or composite context qualified types as its arguments, and where said composition includes a set of qualifiers for said composite context qualified type that express human oriented conceptual notions that are not expressible in terms of programming language constructs or data types, wherein a composite context qualified type is a specialization of said other atomic or composite context qualified types that are said arguments of said context qualified type constructor, comprising: acquiring a specification of a desired computation from a plurality of sources including but not limited to an application programmer, a data base of reusable specifications or other source, where said specification specifies intent of said desired computation without information on how said desired computation is to be implemented, acquiring a design framework based on a computation's requirements and properties, where said design framework specifies design features of a desired implementation of said desired computation, where said design framework comprises 1) skeletal code achieving some portion of said desired computation; 2) a generator method that is specialized to said design framework and that manages building of said integrated, synchronized solution code component; 3) a set of said simultaneous parameterized equations of context qualified types specific to said design framework, and that constrains relationships within said integrated, synchronized solution code component; and 4) a set of said type difference transformations that are not implicit in said type equations and which are therefore elective type difference transformations specific to said design framework, automatically solving said simultaneous parameterized equations of context qualified types for unknown context qualified types implied by equation parameters, automatically deriving each of said type difference transformations that are implied by each pair of composite context qualified types specified in said simultaneous parameterized equations of context qualified types, where said pair comprises a first context qualified type and a second context qualified type, where either said second context qualified type is a specialization of said first context qualified type, or said first context qualified type is a specialization of said second context qualified type, automatically applying said type difference transformations to known code instances of said context qualified types in said simultaneous parameterized equations of context qualified types to produce new code instances of new context qualified types, where said new context qualified types are related by one or more said type difference transformations to said context qualified types of said known code instances, and automatically assembling said integrated, synchronized solution code component that achieves all portions of said desired computation from 1) said new code instances, 2) said skeletal code, and 3) each one of said separate code components that achieves a portion of a desired computation, where said assembling is achieved using said generator method that is specialized to said design framework; and constructing a type difference transformation between a first context qualified type and a second context qualified type, where said type difference transformation is automatically generated if said second context qualified type is a specialization of said first context qualified type, where specialization means that said context qualified type is a subtype either directly or recursively of said first context qualified type, or alternatively, where said type difference transformation must be manually generated if said second context qualified type is not a specialization of said first context qualified type and said first context qualified type is not a specialization of said second context qualified type.

3. A method of claim 1 for constructing type difference transformations between two sets of context qualified types, where a first set comprises a plurality of initial context qualified types and a second set comprises a plurality of specializations of said initial composite context qualified types, where said second set is created by applying context qualified type constructors to context qualified types within said first set, where said type constructors define inherent functional relationships between said plurality of initial composite context qualified types and said plurality of specializations of said initial composite context qualified types, where said inherent functional relationships are optionally further specialized by additional qualifications, where said inherent functional relationships automatically determine, for each of said plurality of initial composite context qualified types, a plurality of bi-directional difference transformations between a code instance of one of said plurality of initial composite context qualified types and a code instance of said each of said plurality of specializations of said initial composite context qualified types, whereby a difference transformation, if it exists, effects said inherent functional relationships by automatically converting a first instance of code from one of said plurality of initial composite context qualified types to a second code instance of one of said plurality of specializations of said initial composite context qualified types or performing an inverse conversion from said second code instance to said first code instance, comprising: constructing an atomic context qualified type by adding context qualifiers to a programming language data type or by constructing a composite context qualified type by recursive application of a context qualified type constructor to a set of type based arguments and a plurality of non-programming language context qualifiers, constructing a specialization of said atomic context qualified type or said composite context qualified type via recursive application of context qualified type constructors to a plurality of type arguments that include said atomic context qualified type or said composite context qualified type and a plurality of context qualifiers, automatically creating said difference transformations based on said functional relationship, if said difference transformations can exist but have not yet been created, and introducing, based on domain specific knowledge, implied existential variables in a difference transformation, where said existential variables originate from context qualifications in a plurality of context qualified types, and where said implied existential variables are required to convert an instance of said composite context qualified type into an instance of said one or more previously defined context qualified types, or required to convert an instance of said one or more previously defined context qualified types into an instance of said composite context qualified type.

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10. A system for creating a data mart in a business intelligence server environment on a computer including one or more microprocessors, said system comprising: a plurality of data sources that maintain data within an enterprise, said plurality of data sources including at least a relational database and a multidimensional database; a business intelligence server, executing on the computer, that provides a virtual logical semantic model, wherein the virtual logical semantic model is a presentation layer to a user and is logically mapped to a plurality of physical models, each said physical model representing entities in a said data source, wherein the business intelligence server receives a specification of a list of levels and a selection of a said data source for storing aggregated data by using the virtual logical semantic model, wherein the plurality of levels spans data from at least two of said plurality of data sources, wherein said levels are identified by analyzing runtimes of queries on the two or more said data sources, wherein at least one said query reduces runtimes thereof by aggregating the data at said levels; an aggregate matrix, created with the virtual semantic model, which includes the plurality of levels, wherein the aggregate matrix is operable to perform data aggregation only at said levels by creating for each said level, in the said data source, a single aggregate table that contains columns at the each said level and at higher levels in a dimension hierarchy, and creating for each fact table a single aggregate table that includes columns corresponding to primary keys at the each said level; wherein the business intelligence server generates a multidimensional cube that contains the aggregated data in the aggregate tables, and stores the multidimensional cube in the said data source.

16. The system of claim 10 , wherein the business intelligence server invokes a Java application programming interface (API) of the said data source in order to configure metadata therein.

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27. The computer-readable medium of claim 21 , the method further comprising generating the at least one domain name suggestion manually.

21. A non-transitory computer-readable medium storing instructions which, when executed by at least one processor, performs a method, the method comprising: opening a web page on a browser in response to a user selection of a link, wherein the web page includes visible content; automatically parsing the web page; obtaining at least one keyword from the parsing; generating a first query from the at least one keyword; generating a plurality of domain name suggestions based at least on the first query; determining a plurality of domain traffic scores for the plurality of domain name suggestions; providing ranked domain name suggestions that includes one or more of the plurality of domain name suggestions ranked based on the plurality of domain traffic scores associated with the plurality of domain name suggestions; displaying the ranked domain name suggestions; receiving a user-highlighted portion of the visible content of the web page displayed during the parsing; refining the first query with one or more keywords derived from the user-highlighted portion of the visible content to generate a second query, wherein the user-highlighted portion of the visible content comprises at least one of a title of the web page, text in the web page, an image in the web page, or an advertisement in the web page; generating one or more domain name suggestions based on the second query; and providing the one or more domain name suggestions.

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8. The apparatus according to claim 1 , where the sign language video content has a lower frame rate than a main program audio video (A/V) content.

1. An apparatus for selectively supplementing main program video content with a sign language video content, comprising: a video receiver device configured to receive data representing audio and a frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content in which a plurality of locations are processed to accept substitution of the sign language video content; a user interface forming a part of the video receiver device, configured to produce a signal indicative of selection of a first location of the plurality of locations for display of the sign language video content; and a content circuit forming a part of the video receiver device; where responsive to the signal indicative of the selection, the content circuit is configured to present at the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; at least one scaler to re-scale video information, wherein the video receiver device is configured to, responsive to a signal to view the sign language video content, enable a picture-in-picture (PIP) circuit, the video receiver device also being configured to disable the video scaler when the PIP circuit is enabled, and wherein the video receiver device is configured to, responsive to a signal not to view the sign language video content, disable the picture-in-picture (PIP) circuit and enable the video scaler.

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11. A system comprising: one or more memory devices storing computer instructions; and one or more processors executing the instructions stored in the one or more memory devices in order to: receive a search query submitted by a user device; determine that the search query matches a local query for a particular geographic region corresponding to the user device, wherein the local query is a query having a geo-query count that exceeds an expected geo-query count for the particular geographic region by at least a threshold amount, the geo-query count representing a number of times the query was received in the particular geographic region, and the expected geo-query count representing a baseline number of times that the query was expected to be received in the particular geographic region based on the number of times that the query was received in a baseline geographic region that is different than the particular geographic region; and adjust result scores for local search results that are responsive to the search query.

14. The system of claim 11 , wherein the one or more processors further execute instructions to determine a presentation order for the search results using the adjusted result scores.

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8. A computer-implemented system comprising: means for extracting first information from a post to a blog; means for extracting second information, associated with the blog, from a source different than the post to the blog; means for creating a hybrid document by combining the first information and the second information; means for storing the hybrid document in a searchable index; and means for using the searchable index to determine a relevance of the post to a search query.

26. The computer-implemented system of claim 8 , where the source includes the blog, and where the means for extracting the second information includes: means for extracting at least one of a title of the blog, an author of the blog, a profile of the author of the blog, or a blogroll from the blog.

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1. A computer-implemented method of enabling access control, the method comprising: automatically defining an access control statement, for determining authorization request validity using an authorization control engine for an asset, the access control statement comprising a first portion comprising one or more of a structural expression, and a conditional expression wherein the structural expression declares fixed relationships of the asset and a second portion comprising one or more of a classification expression comprising ontology expressions; and evaluating the first portion separately but simultaneously with the classification expression in the second portion of the access control statement, wherein the second portion uses an ontology engine.

9. The computer implemented method of claim 1 , wherein the defining comprises automatically selecting ontology expressions.

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1. A method for responding to a user query, the method comprising: receiving a query submitted by a querying one of a plurality of users; searching a corpus comprising a plurality of documents to identify one or more hits, wherein each hit is a document in the corpus that is determined to be relevant to the query; building a trust network for the querying user, the trust network having as members a subset of the plurality of users including at least one user other than the querying user explicitly identified by the querying user as a friend, wherein the members of the trust network are members of a selected community of users, the selected community being selected by the querying user; providing a trust network interface operable by the plurality of users to identify others of the plurality of users as friends; receiving identifications of friends from a plurality of inputting users, including the querying user, via the trust network interface; storing a list of identified friends for each inputting user; accessing a store of annotations created by the plurality of users, each annotation being associated with a subject one of the documents in the corpus and with a creating one of the plurality of users, each annotation including user-specific metadata related to the subject document, wherein the user-specific metadata included in each annotation includes a rating of the subject document; identifying, as an annotated hit, each of the hits that is the subject document of at least one matching annotation, wherein the creating user of each matching annotation is one of the members of the trust network; obtaining an annotation rating from each matching annotation, the annotation rating being a rating of the annotation, and computing an average annotation rating based at least in part on a degree of separation of the creating user in the trust network relative to the querying user; generating a search report including a listing of the hits, wherein for each annotated hit, the search report includes information about at least one of the matching annotations, wherein an order for the listing of the hits is determined based at least in part on the average annotation ratings of the annotated hits; providing in the search report, for a given annotated hit, a control element operable by the querying user to request a display of the user-specific metadata of at least one of the matching annotations; and transmitting the search report and the user-specific metadata of at least one matching annotation to the querying user.

26. The method of claim 1 wherein the user-specific metadata includes an item of information explicitly input by the user.

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1. A computer-implemented method for assembling a tax-information data structure, comprising: receiving a plurality of income-tax documents, wherein the documents comprise tax-forms, instructions, and publications issued by an income-tax authority to be used for subsequent income-tax preparation by users; extracting, by a computer, information about taxes from the received income-tax documents, wherein the information about taxes comprises tax phrases; extracting context information related to the extracted tax information, wherein the context information comprises location information associated with the extracted tax information, and wherein the location information comprises at least one of a title or version of an income-tax document, a page number in an income-tax document, and a page index associated with an income-tax document; identifying a first set of tax phrases in the extracted tax information, wherein the identifying involves using semantic and structural heuristics; identifying a second set of tax phrases in the extracted tax information using a statistical identification technique; constructing, by the computer, the tax-information data structure, wherein the constructing involves building an association between the first and second sets of tax phrases with the extracted context information; storing, in a memory of the computer, the constructed tax-information data structure; receiving, at the computer, a tax-related query from a user, wherein the user is executing an income tax-preparation software; processing the received query using the stored tax-information data structure to generate an answer; and displaying the generated answer to the user.

6. The method of claim 1 , wherein identifying the second set of tax phrases involves: comparing phrases in a language model associated with the income-tax documents to phrases in another language model associated with a topic other than income tax; and excluding phrases that are common to the language model and the other language model.

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25. Device according to claim 18 , comprising a menu control component for controlling a user interface menu displayed on the display device, the user interface menu comprising a main menu and sub-menus which are displayed when the corresponding main menu item is selected, the main menu comprising the group designators and the sub-menus comprising the candidate words of the respective groups.

18. Context sensitive text input device, comprising: a text prediction component for determining a list of candidate words for the present input context, a candidate word being a possible textual continuation of the present context; wherein the present context comprises at least one preceding word or delimiter; a candidate grouping component for arranging the candidate words in groups, each group having a group designator; a display device for displaying the group designators and candidate words; and an input device for receiving a user input; wherein the input device is configured to receive a group selection from the user and the display device is configured to respond by displaying candidate words of the selected group, the displayed candidate word being arranged according to their respective contextual relevance; wherein the input device is further configured to receive a candidate selection from the user and to accept the selected candidate word as text input; wherein the text prediction component is further configured to update the context based on the text input and determines an updated list of candidate words for the updated context.

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12. The apparatus of claim 11 , wherein said personalization comprises an endorsement by a personal friend.

11. The apparatus of claim 1 , wherein said search results are sorted in a way that is personalized for said user.

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12. A method as recited in claim 10 wherein HTML and XML-formatted e-mails attack vulnerabilities in a Web browser.

10. A method of preventing cross-site scripting, the method comprising: parsing an HTML e-mail message to create a document object model (DOM) tree wherein the DOM tree includes a plurality of branches, the plurality of branches including at least one branch having only known elements; utilizing a model hook of an e-mail program to derive a normal element filter; applying the normal element filter to the DOM tree, the filter executing as a plug-in in a browser in a computing device; creating a modified DOM tree wherein the at least one branch having only known elements is excluded from the DOM tree and wherein the excluding of the at least one branch from the DOM tree is performed such that remaining branches of the DOM tree are still connected with one another; and applying a script analyzer filter to the modified DOM tree to create a final DOM tree having only unknown element types.

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17. The non-transitory computer-readable storage medium of claim 13 , wherein the apparatus is caused to further perform: receiving inputs of mainstream/leftfield relative rankings to the primary and secondary metagenres, said mainstream/leftfield relative rankings identifying how conventionally said offering fits in a respective metagenre.

18. The non-transitory computer-readable storage medium of claim 17 , wherein the apparatus is caused to further perform: sorting the offerings with the highest mainstrearn/leftfield relative ranking to be at the top of the recommendation list; and incorporating a number of times that at least one of the offering has been recommended as a tie breaker when two of the offerings have an identical mainstream/leftfield relative ranking.

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12. A system comprising: one or more processors; and a non-transitory computer-readable medium including one or more sequences of instructions that, when executed by one or more processors, causes: displaying, via a display interface, text using a first display size; receiving, from an input device, an input requesting an increase in the first display size; responsive to the input, determining that the increase in the display size requested is beyond a maximum display size; and responsive to the determination that the requested display size is beyond the maximum display size, providing an audio output corresponding to the text, wherein the audio output includes an audio rendition of the text displayed in a display region.

18. The system of claim 12 , wherein the providing of the audio output corresponding to the text is in accordance with a determination that an accessibility mode of an electronic device is enabled.

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1. A computer-implemented medical diagnosis system, comprising: a. a memory and a display; b. a plurality of multilingual forms stored in the memory c. the multilingual forms containing a plurality of diagnostic information in a plurality of predetermined diagnostic-information locations; d. two or more language selection buttons, e. a plurality of audio activation buttons, each audio activation button located adjacent to a diagnostic-information location, f. activation of one of said audio activation buttons causes the system to play an audio clip, wherein i. the audio clip explains the diagnostic information adjacent to the activated audio-activation-button, and ii. the audio clip explains the diagnostic information in the most recently selected output language.

12. The medical diagnosis system of claim 1 , wherein the memory stores the multilingual forms in a remote server.

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1. A non-transitory computer-readable medium storing instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining, at a client device, a credential identifier for a credential that is associated with a user; periodically, at a predetermined time period: obtaining, at the client device, a time derived from a timing device of the client device; determining, at the client device, at least one index value using the credential identifier and the time derived from the timing device of the client device; accessing, at the client device, a predetermined set of associations between index values and words; generating, at the client device, a phrase corresponding to the credential, the phrase being generated to include words that are associated with the at least one index value in the predetermined set of associations; receiving, at the client device, a user command to output the phrase; and responsive to the user command, rendering, at the client device, the phrase corresponding to the credential.

11. The non-transitory computer-readable medium of claim 1 wherein, responsive to the user command, rendering, at the client device, the phrase corresponding to the credential comprises responsive to the user command, displaying, on a screen of the client device, the phrase corresponding to the credential.

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1. A process for creating and using an electronic screen based product, said process comprising: importing untagged source documents and automatically converting the source documents into a plurality of discrete electronic screens, which collectively form the electronic screen based product; creating each of the electronic screens based upon one or more templates, wherein the one or more template are either user selected or selected by default, wherein each electronic screen is created by populating the one or more templates with text data from the source documents; analyzing text in each of the electronic screens and automatically inserting an image into the electronic screen, wherein the insertion of the image is based upon the analyzed text; automatically analyzing the electronic screens and automatically generating questions based upon the analyzed electronic screens; presenting a graphical user interface that allows a user to edit the electronic screens and add additional electronic screens to the electronic screen based product; publishing the electronic screen based product for use on a sharable content object reference model (SCORM) compliant learning management system; and communicating end user progress and performance to a database.

9. The process of claim 1 , wherein any hierarchical relationship that exists between said electronic screens can be manipulated, in terms of end user navigation, using a graphical user interface included within the process.

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5. A pattern recognition process for generating a confidence level that an unknown object which belongs to one of a plurality of models actually belongs to a selected model, the pattern recognition process for use with a constraint network, the constraint network providing a network of constraints representing one of the plurality of models, the constraint network comprising a plurality of weights, a plurality of nodes and a plurality of layers wherein each layer of nodes corresponds to a particular feature and each node is associated with a sub-range of the typical values for that feature for a selected one of the plurality of models, and wherein each weight corresponds to a value representing a relationship between the nodes of at least one feature type and the selected model, the pattern recognition process comprising the steps of: (a) receiving feature values of an unknown object, wherein each feature value has a known range; and (b) responsive to the relationship between those nodes that correspond to the feature values and the weights between those nodes, generating a value corresponding to the confidence that the object belongs to the selected model.

6. The pattern recognition process of claim 5, wherein each node corresponds to the deviation of the feature value of the unknown object from the mean value for that feature.

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7. The method of claim 4 , wherein each second node is within a threshold degree of separation from the first node.

4. The method of claim 1 , further comprising accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each edge between two nodes representing a single degree of separation between the two nodes, the plurality of nodes comprising: a first node corresponding to a first user of an online social network; a plurality of second nodes corresponding to a plurality of second users of the online social network, respectively; and a plurality of third nodes corresponding to a plurality of locations, respectively.

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18. The computer-readable storage medium of claim 17 , wherein said building the purchase index further comprises selecting the words having more than three characters to produce a set of keys.

19. The computer-readable storage medium of claim 18 , wherein said building the purchase index further comprises associating the purchased items with the keys as values of the keys, such that each of the word keys is associated with one or more of the purchased item values.

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8. The system of claim 7 , wherein said subscribe and publish communication interface is an information kit and said subscription object is an information kit subscription object, and said system further comprises: means for providing a query expression within said subscription object containing an operand other than a wildcard for uniquely differentiating said query from a query for a generic response; means for publishing said query to an information kit; and means for receiving a response containing a publication object satisfying said entire query expression.

7. The system of claim 5 , wherein said subscription component is an agent and said system further comprises: means for enabling the agent to register interest in pieces of information via expressions, wherein the agent registers interest on an information bus; means for enabling the agent to listen for information indicating occurrence of a condition for which the agent is designed to response, said condition corresponding to satisfaction of one or more criteria within an expression; means for receiving confirmation that all criteria within said expression has been satisfied; and means for completing a secondary function when said confirmation is received.

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27. The computer-readable computer memory medium of claim 25 , the method further comprising: receiving a designation of one of the plurality of search result snapshot objects; and adding a new search result snapshot object to the search result history representation by inserting a link from the designated one of the plurality of search result snapshot objects to the new search result snapshot object.

25. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed on computer processor, facilitates searches for publications, by performing a method comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history representation between a plurality of different individuals and/or entities.

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4. The method of claim 1 , said providing the Speech Hyperlink table comprising: selecting the hyperlinked terms from a text of the speech; and for each selected hyperlinked term: identifying a network address corresponding to the selected hyperlinked term and storing, in the Speech Hyperlink table, an entry comprising the selected hyperlinked term and its identified corresponding network address.

1. A method for generating a Speech Hyperlink-Time table in conjunction with a system of universal time that provides a same absolute time for every geographical location on Earth, said method comprising: creating a Speech Hyperlink table structured with columns and rows, wherein the columns of the Speech Hyperlink table consist of a column for storing hyperlinked terms, a column for storing universal times at which corresponding hyperlinked terms are recognized, and a column for storing network addresses linking corresponding hyperlinked term and a corresponding network address of a network, wherein the Speech Hyperlink table comprises a plurality of entries, wherein each entry of the plurality of entries corresponding to a row of the Speech Hyperlink table and comprises a hyperlinked term and a corresponding network address of the network, wherein said network address links the hyperlinked term to information relating to the hyperlinked term, wherein said information is on a server of the network; and while a speech is being spoken by a speaker, recognizing each hyperlinked term of the Speech Hyperlink table being spoken by the speaker, said recognizing being performed by a speech recognition system on a computing device, and for each recognized hyperlinked term: determining a universal time at which the hyperlinked term was recognized; ascertaining, from the Speech Hyperlink table, a network address that corresponds to the recognized hyperlinked term; and generating a row in the Speech Hyperlink-Time table, wherein said row comprises the universal time, the recognized hyperlinked term, and the network address that corresponds to the recognized hyperlinked term.

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32. A computer readable medium according to claim 31, wherein said means for creating comprises: means for prompting a user for one or more key words of interest; and means for saving the key words of interest as the user interest profile.

31. A computer readable medium according to claim 23, further comprising means for creating a user interest profile.

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1. A computer program product comprising machine executable instructions stored on non-transitory machine readable media, the product for at least one of tagging and browsing multimedia content, the instructions comprising instructions for: providing a tagging annotation interface adapted for allowing at least one user to manually associate at least one keyword with at least one multimedia document; providing a browsing annotation interface adapted for allowing the user to judge a relevance of at least one keyword and at least one automatically associated multimedia document; providing an annotation candidate selection component that is adapted for automatically associating at least one annotation keyword and at least one multimedia document, and manually associating the at least one selected annotation keyword with the at least one multimedia document; and a selection tool configured to select at least one of the tagging annotation interface and the browsing annotation interface according to at least one of a learning model and an input from the user; wherein the learning model is related to of word frequency and average annotation times per word; and wherein the selection tool is configured to select between the browsing annotation interface for frequent keywords and the tagging annotation interface for infrequent keywords; wherein a boundary for determining the frequent keywords and the infrequent keywords is derived from user's average tagging time per image, user's average tagging time per keyword, user's average browsing timer per image, user's average browsing time per keyword, and a total number of documents.

7. The computer program product as in claim 1 , wherein the learning model is related to visual similarity.

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14. The system as claimed in claim 13 , wherein the plurality of target systems is target processes or target devices.

13. A system for controlling or operating a plurality of target systems via spoken commands, the system comprising: the plurality of target systems; a plurality of controllers for controlling or operating the plurality of target systems via spoken commands; and a speech recognition system that stores interface information that is specific to a target system or a group of target systems of the plurality of target systems that are to be controlled or operated via the spoken commands, the speech recognition system being operable to analyze the interface information to recognize spoken commands issued for controlling or operating the target system or the group of target systems, wherein a first controller of the plurality of controllers includes a microphone for picking up audible signals in the vicinity of the first controller and a device for transmitting the audible signals to the speech recognition system, and wherein the target system or the group of target systems, which are controllable via the spoken commands, are configured to transmit the interface information specific to the target system or the group of target systems to the speech recognition system.

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2. The method of claim 1 , wherein determining if said page is inverted or non-inverted includes: generating a per text line difference value, said per text line difference value being said difference between the first count of foreground pixels in the first portion of said current line of text and the second count of foreground pixels in the second portion of said current line of text.

1. A method of processing a page in the form of an image, said page including lines of text, the method comprising: generating a histogram of foreground pixel counts corresponding to a current line of text of said page being processed, said foreground pixel counts corresponding to different rows of pixels corresponding to said current line of text; identifying a first peak and a second peak in said histogram, said first peak corresponding to a row of pixels above said second peak; determining if said page is inverted or non-inverted based on a difference between a first count of foreground pixels in a first portion of said current line of text and a second count of foreground pixels in a second portion of said current line of text, said first portion being located in said line of text above said first peak, said second portion being located in said line of text below said second peak.

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1. A computer-implemented method comprising: receiving a query comprising a search term; determining a location on a page that is responsive to the query, wherein the page has a native appearance; determining a contextual area associated with the location on the page, wherein determining a contextual area comprises: determining a plurality of lines of text associated with the location on the page, wherein determining a plurality of lines of text associated with the location on the page comprises: extracting a line of text above the line of text containing the search term; and extracting a line of text below the line of text containing the search term; identifying coordinates of a polygon including the lines of text; rendering the contextual area into an image; and in response to the query, and without requiring any additional user action, causing the image to be output in a hi-fidelity result set displaying one or more results of the query, wherein the image has an appearance the same as the native appearance of the page.

6. The method of claim 1 , wherein the page comprises a format including at least one of: hypertext markup language, extensible markup language, portable document format, Microsoft Word Document format, plain text, or rich text.

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1. A method comprising: receiving an input schema having input fields; determining a meaning of said input schema and a relationship between said input fields; creating a set theory expression representing said meaning; and, creating data structures representing semantics of said input schema.

11. A method according to claim 1 , wherein said data structures may include data table entries.

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20. The system of claim 16 , wherein generating the cross-domain ranking of the collection of complete input phrases further comprises: calculating a respective integrated ranking score R j for each complete input phrase P j of the collection of complete input phrases based on a respective formula R j = ω v ⁢ v j + ω μ ⁢ μ j ω v + ω μ , wherein v j is a respective frequency of the complete input phrase P j that has been normalized for cross-domain comparison, μ j is a respective phrase indexing power of the complete input phrase P j across the plurality of domains, ω v and ω μ are relative weights given to domain-specific frequency and cross-domain indexing power in the ranking of the collection of complete input phrases; and generating the cross-domain ranking of the collection of complete input phrases based on the respective integrated ranking scores for the collection of complete input phrases.

21. The system of claim 20 , wherein the operations further comprise: for each complete input phrase P j , normalizing the respective domain-specific frequency of said complete input phrase Pj by a maximum phrase count of a single input phrase observed in the training corpus.

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18. The method of claim 8 , wherein integrating the knowledge base with the original data comprises: establishing a semantic relationship among the knowledge base and the original data; and dynamically updating the product documentation based on the semantic relationship.

19. The method of claim 18 , further comprising: utilizing web crawlers to extract data associated with products or diagnostic services; and dynamically updating the product documentation and the knowledge base based on the data extracted.

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23. The method of claim 1 , further comprising: performing the processing step on a device in order to access the item with the device.

25. The method of claim 23 , wherein the device comprises a rendering device.

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13. An apparatus for generating a situational analysis text that is configured to transform underlying data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a situational analysis text, the apparatus comprising: a data analyzer that is stored in a memory and configured, when executed on a processor, to access input raw data from one or more monitored data channels over a network and to identify at least one data channel of the one or more monitored data channels as the primary data channel based on the detection of an alert condition, wherein the data analyzer is further configured to determine whether one or more data channels that are to be assigned as one or more related data channels, wherein the one or more related data channels are a subset of one or more monitored data channels; a data interpreter that is stored in the memory and configured, when executed on the processor, to generate, from the input raw data, language independent data structures that collect underlying data in the primary data channel and the more or more related data channels such that the underlying data is linguistically expressible, wherein at least a portion of the underlying data in the primary data channel comprises numerical data; and a natural language generation system that is stored in the memory and configured, when executed on the processor, to input the one or more generated language independent data structures to determine a scale of a graph and the content of the situational analysis text, wherein the situational analysis text generated based at least on the data in the primary data channel, wherein the situational analysis text is configured to linguistically express contextual information related to the alert condition and wherein the graph is displayable with the situational analysis text and is generated based at least on the data in the primary data channel within the determined scale and the graph is further configured to display numerical data in the primary data channel as a function of time, wherein at least a portion of the graph and at least a portion of the situational analysis text are generated in response to the identification of the alert condition.

19. The apparatus according to claim 13 , wherein a scale for the graph is determined based on the one or more related data channels and wherein the graph is further generated based on data in the one or more related data channels in an instance in which one or more data channels are determined to be related to the primary data channel.

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7. The method of claim 6 , wherein the matching entity further corresponds to an entity associated with a lowest hierarchy level associated with the grouping.

6. The method of claim 1 , further comprising: determining, from the merged table, and based at least in part from the aggregate weights, a first leading scorer of the matched fields and a second leading scorer of the matched fields, the first leading scorer associated with a record having a highest aggregate weight and the second leading scorer associated with a record having a second highest aggregate weight; determining a first condition comprising whether a first weight associated with the first leading scorer meets or exceeds a first predetermined value; determining a second condition comprising whether a difference between the first weight and a second weight associated with the second leading scorer meets or exceeds a second predetermined value; and wherein the matching entity corresponds to the first leading scorer and is based at least in part on the determining of the first condition and on the determining of the second condition.

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1. An information providing device connectible to a plurality of broadcast receiving terminals for acquiring and displaying video information of a program and electronic contents guide (ECG) information about the program and a plurality of information acquisition terminals for acquiring and displaying ECG information about the program via a communication network to provide ECG information about the program to the broadcast receiving terminals and the information acquisition terminals, comprising: an ECG information storage unit for storing the ECG information including attribute information; an emotion information acquisition unit for acquiring emotion information representing emotions of viewers about content of the program displayed by the broadcast receiving terminals via at least one of the information acquisition terminals in real-time in linkage with progression of the program; an emotion information analysis unit for analyzing at least one piece of the acquired emotion information; an ECG unit configuration unit for configuring an ECG unit by associating at least one piece of the ECG information with the program and associating at least one piece of the acquired emotion information with the program based on the attribute information of the ECG information to suit analysis results of the emotion information; and an ECG unit providing unit for providing the ECG unit to the plurality of broadcast receiving terminals and the plurality of information acquisition terminals in linkage with a progression of the program, wherein the information providing device provides the video information of a program along with the analysis of the emotion information of viewers about content of the video information of the program, which is shared among the plurality of broadcast receiving terminals, where emotion information is classified into one of evaluation categories contained in an emotion evaluation pattern defined for each of the programs, the ECG information is classified into one of evaluation categories contained in the emotion evaluation pattern based on the attribute information of the ECG information, and the ECG unit configuration unit configures the ECG unit by associating at least one piece of the ECG information with a program and an evaluation category of the ECG information based on the attribute information of the ECG information to suit analysis results of the emotion information, and wherein the ECG unit configuration unit configures the ECG unit to add supplementary information when an amount of emotion information classified into a specific evaluation category exceeds a predetermined threshold.

7. The information providing device according to claim 1 , wherein the emotion information acquisition unit acquires an evaluation category selected via the information acquisition terminal among evaluation categories contained in an emotion evaluation pattern defined for each of the programs as the emotion information.

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1. A computer system to extract contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored documents, the system comprising: one or more computer readable storage devices configured to store one or more software modules including computer executable instructions, and the compilation, wherein the electronically stored documents comprise one or more semi-structured document(s), one or more unstructured document(s), or a combination thereof, and each of the one or more electronically stored documents comprises one or more pages; a network configured to distribute information to a user workstation; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the one or more software modules in order to cause the computer system to access, from the one or more computer readable storage devices, the compilation; receive information regarding the pre-defined value, wherein the pre-defined value has a certain format, has a certain two-dimensional spatial relationship to words in a pre-selected page, and is associated with one or more keywords; for each page of the compilation, identify words and contender values on the page using optical character recognition (OCR) and post-OCR processing, and group the identified words and the identified contender values into anchor blocks based on their spatial positioning on the page, such that the page comprises a plurality of anchor blocks and each anchor block comprises one or more words, one contender value, or a combination thereof; on the page, for each of the contender values, numerically determine a first confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of a calculated two-dimensional spatial relationship between the contender value and the anchor blocks on the page with the pre-defined two-dimensional spatial relationship between the pre-defined value and the words in the pre-selected page, numerically determine a second confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of words in the anchor blocks on the page with the one or more keywords associated with the pre-defined value, and numerically determine a third confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of a format of the contender value with the certain format of the pre-defined value; over all the pages of the compilation, extract positive contender values as positively associated with the pre-defined value based at least in part on the first confidence, the second confidence, and the third confidence; store the positive contender values in the one or more computer readable storage devices; and transmit the positive contender values over the network to the user workstation in response to a search for values associated with the pre-defined value at the user workstation.

6. The system of claim 1 , wherein the determination of the first confidence is adjusted based on the number of anchor blocks on the page.

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1. A method comprising: instantiating an application on a plurality of computers including a first computer implementing a thin client, a second computer implementing a mobile client and a third computer implementing a connected client; said application comprising multiple layers including an object manager layer˜in data communication with business objects in an object the object repository comprises a plurality of business objects that are organized into projects, the projects that can be locked, checked-out or checked-in; said layers of the application comprise interfaces for passing data and commands between the layers; and instantiating the application comprises extracting attribute-value data from a meta data repository for the application.

3. The method of claim 1 wherein the multiple layers includes a data manager layer.

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2. The method of claim 1 , further comprising: responsive to determining that the first perceptual delta value at least equals the first threshold value, outputting at least the first page of the modified document as an output document.

1. Within a system comprising a processor and a memory, a method of optimizing a layout of an electronic document, the method comprising: via the processor, processing the electronic document to identify a plurality of document sections within the electronic document; recursively, combining a plurality of document sections in at least a first page of a modified document and reducing a presentation size of content within the document sections so that the combined document sections fit within the first page of the modified document; and with each recursive combination of document sections: identifying first perceptual features of content of the combined document sections based on the content as presented in an original version of the electronic document, and generating a corresponding first perceptual value derived from the first perceptual features wherein the first perceptual value is a first perceptual hash value generated by performing a first perceptual hash on the content of the combined document sections as presented in the original version of the electronic document to determine a first perceptual hash value; identifying second perceptual features of content of the combined document sections based on the content as presented in a modified version of the electronic document in which the document sections are combined into the first page, and generating a corresponding second perceptual value derived from the second perceptual features, wherein the second perceptual value is a second perceptual hash value generated by performing a second perceptual hash on the document sections as presented in the modified version of the electronic document in which the document sections are combined into the first page; generating a first perceptual delta value by comparing the first perceptual value derived from the first perceptual features to the second perceptual value derived from the second perceptual features; determining whether the first perceptual delta value at least equals a first threshold value; responsive to determining that the first perceptual delta value at least equals the first threshold value, ceasing the recursive combination of document sections into the first page; and responsive to determining that the first perceptual delta value does not at least equal the first threshold value, continuing the recursive combination of document sections in at least the first page.

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21. An apparatus, comprising: means for predicting one or more future hot terms according to a classification process, wherein said predicting is based, at least in part, on frequency change rates associated with an array of query terms; means for ranking the one or more predicted future hot terms based, at least in part, on probability values determined by the classification process; and means for creating one or more contextual shortcuts associated with the respective one or more predicted future hot terms based, at least in part, on the ranking of the one or more predicted future hot terms, wherein the one or more contextual shortcuts comprise one or more selectable links in an online document to additional online content related to the respective one or more predicted future hot terms.

22. The apparatus of claim 21 , wherein the classification process comprises a machine learning process.

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5. The method of claim 1 wherein the interface includes a graphical user interface and wherein the step of receiving input includes receiving graphical input via the interface that specifies at least a portion of the IT application.

6. The method of claim 5 wherein the interface includes a visual flow space and a programming function toolbar, the toolbar including function blocks representing IT functional modules, the method further including the steps of receiving developer input via the interface selecting functional modules from the toolbar to instantiate function instances in the flow space.

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16. A method as described in claim 15 , wherein the predetermined number of groupings is defined as a range.

15. A method of producing a keyword hierarchy, the method being implemented at a computing device and comprising: mapping, at the computing device, closeness of a plurality of keywords extracted from a plurality of items, one to another, the closeness partially defining a relevancy of one of the plurality of keywords to another of the plurality of keywords and the closeness being generated by: for each one of the plurality of keywords: creating a hash table comprising information that includes: a number of the plurality of items having the one of the plurality of keywords as a root keyword; a number of a sum of ranks of the plurality of items that have the root keyword; a first structure pointing to the plurality of keywords that are likely included in the plurality of items that have the root keyword; and a second structure storing closeness value for each of the plurality of keywords in the first structure; assigning an inertia for each one of the plurality of keywords in the first structure; walking each one of the plurality of keywords in the first structure and adjusting its inertia based at least in part on likelihood of the plurality of items having the each one of the plurality of keywords as a keyword; calculating one or more steps that the each one of the plurality of keywords is away from the root keyword in distance and adjusting the inertia of the each one of the plurality of keywords based at least in part on the one or more steps; taking the each one of the plurality of keywords that are two or three steps away from the root keyword; and adding the current inertia of the each one of the plurality of keywords to the closeness value stored in the second structure each time the each one of the plurality of keywords in the first structure points back to the root keyword; forming, at the computing device, a plurality of groupings of the keywords based on the mapped closeness, wherein the plurality of groupings include two or more of the plurality of keywords into keyword phrases; combining the plurality of groupings based at least in part on closeness of the plurality of groupings until a predetermined number of groupings remain; and outputting said keyword phrases corresponding to the plurality of groupings for display at the computing device such that each of the keyword phrases, when output, is configured to be selectable to navigate to one or more corresponding said items that have the keyword phrase.

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33. The apparatus of claim 31, wherein said at least one occluder node is positioned relative to bounding boxes to effect partial or total occlusion of objects within said bounding box.

31. An apparatus for providing simple generalized conservative visibility, comprising: a programmable machine including a display for viewing at least one object; and a processor; said processor defining at least one occluder node, wherein said at least one occluder node comprises a plane having a given width and height in object space that blocks the rendering of objects behind it in world space; said processor calculating bounding planes which form a bounding volume in which said object is occluded; said processor testing if a camera is inside an occlusion volume associated with an object, such that said object is visible to said camera, wherein an object not visible to said camera is not rendered; wherein said at least one occluder node is used by said processor to compute a conservative set of visible objects from a current view point for viewing on said display; providing an activationDistance field which specifies how far a camera must be from an occluder node for said occluder node to be active; and said processor rendering a conservative set of visible objects.

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1. A computer implemented method for enabling collaboration between advisors and clients, the method being implemented in a computer system comprising one or more processors configured to execute computer program modules, the method comprising: receiving requests to define a collaboration team that includes advisors associated with a client, wherein the requests further define different scopes of authorization for the advisors to access financial documents including financial information associated with the client; hosting, over a network, an electronic collaboration forum that enables collaboration between the advisors and the client and, responsive to receipt of the selections, selectively provides the advisors access to stored financial documents associated with the client in accordance with the scopes of authorization for the advisors defined in the requests; providing a first advisor access to a first financial document associated with the client through the electronic collaboration forum, responsive to reception of a request for the first financial document from the first advisor and to the scope of authorization for the first advisor permitting access to the first financial document; receiving a modification to the first financial document from the first advisor via the electronic collaboration forum; modifying, by the one or more processors, the first financial document accessible through the electronic collaboration forum in accordance with the received modification; and providing access to the modified first financial document via the electronic collaboration forum for (i) the client and (ii) the advisors associated with scopes of authorization that permit access to the first financial document.

3. The method of claim 1 , further comprising tracking one or more actions taken by the first advisor via the electronic collaboration forum, wherein the tracked one or more actions comprise one or both of accessing and/or modifying the first financial document.

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16. The computing device of claim 15 , wherein the computing device is further configured to perform operations comprising: presenting the result set to the user of the website.

15. A computing device configured to perform operations comprising: monitoring one or more actions taken by a user while browsing a website; automatically assigning one or more search terms to at least one of the one or more actions taken by the user based upon, at least in part, metadata associated with said one or more actions; assigning one or more complementary terms that define one or more products/services that complement the one or more actions taken by the user; in response to at least one of the actions, executing a query on a datastore based on at least a portion of the one or more search terms and at least a portion of the one or more complementary terms to generate a result set; and displaying the result set including a link to an ecommerce website that offers for sale the one or more products/services, the link embedded with a referring party identifier configured to identify a referring party to a merchant operating the ecommerce website for payment of a referral fee.

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2. A method as recited in claim 1 , further comprising repeating the obtaining, combining, and returning as each of multiple additional characters of the user data input are received.

1. A method in a search term suggestion engine of a computing device, the method comprising: receiving characters of user data as the characters are input, wherein the user data is at least part of a search term to be provided to a first application to search for the search term, wherein the first application is one of multiple applications on the computing device; receiving, from the first application, an indication of multiple suggestion sources; obtaining, from each of two or more of the multiple suggestion sources, one or more suggested search terms based on the received characters; combining the one or more suggested search terms into a combined set of suggested search terms; and returning the combined set of suggested search terms to a search user interface for presentation to a user, the returning including returning first suggested search terms received from a first one or more of the multiple suggestion sources within a threshold amount of time, waiting until second suggested search terms are received from a second one or more of the multiple suggestion sources, and returning, after returning the first suggested search terms, the second suggested search terms to the search user interface.

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1. In a computing environment, a method implemented by computing system having a processor, the method comprising: receiving a canonical enveloped message from a computer implemented application, wherein the canonical enveloped message comprises payload data and is associated with a context store that stores context information of the canonical enveloped message in a form that is independent of one or more protocols employed by the canonical enveloped message; at a protocol pipeline comprising a plurality of protocol components processing the canonical enveloped message including using two or more of the protocol components to process the canonical enveloped message, and by at least adding, removing or modifying context entries in the context store, wherein each portion of the context information is stored in the context store as a context entry that comprises at least a name element to identify the portion, a value element representing the value of the identified portion, and optionally a metadata element that defines any additional information about the identified portion, such that context information for a plurality of protocol components is aggregated using a common format in the context store; converting the canonical enveloped message to a raw message that does not include the context store; and sending at least a portion of the raw message on a computer implemented communication medium.

3. The method of claim 1 , wherein at least one context entry in the context store comprises a context entry metadata element defining restrictions on the use of the at least one context entry.

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9. The method according to claim 5 , wherein an ontology definition for the ontology is established such that an object or datatype property of an ontology class can be marked as grounded.

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

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5. The apparatus according to claim 4 , wherein the processor is further programmed to estimate an attribute of the keyword, wherein the giving of the question relating to the keyword to the user converts a first character string indicating the keyword into a second character string indicating the attribute, and wherein the generated synthesized speech obtained by synthesizing speech of the keyword synthesizes speech of the second character string.

4. The apparatus according to claim 1 , wherein the processor is further programmed to give a question relating to a keyword to the user; and calculate a correct answer rate based on an answer to the question from the user, to generate a learning history including information associated with the question and the correct answer rate, wherein the score indicating the degree of emphasis of the keyword calculates the score which becomes lower as the correct answer rate increases, in accordance with the learning history.

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30. The computer readable medium as defined in claim 29 , wherein each said data entry field on the electronic form is an editing control selected from the group consisting of one or more of: a plain text box; a drop-down list box; a list box; a check box; a rich text box; an expression box; an option button; a button; a section with controls; a section; an optional section; an optional section with controls; a repeating section with controls; a repeating section; controls in a layout table; controls; a repeating table; a bulleted list; a numbered list; a plain list; a hyperlink; a date picker; an inline picture; a linked picture; an optional sequence; a choice; and a recursion.

29. The computer readable medium as defined in claim 27 , wherein: the electronic form has one or more data entry fields each corresponding to one said markup language node of the structured markup language document.

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1. A method comprising: in a processing system, receiving a rule set as a single package; generating a dependency graph for the rule set, the dependency graph including a plurality of ranked nodes, the nodes including entity nodes, attribute nodes, condition nodes, and rule nodes, where a first attribute node points to a first condition node when a first attribute associated with the first attribute node is used in a conditional expression associated with the first condition node, a first condition node points to a first rule node when a first condition associated with the first condition node is used in a first rule associated with the first rule node, and where the first rule node points to a second rule node when the first rule overrides a second rule associated with the second rule node; and generating a sequence of processing logic for optimal processing of inputted facts according to a rank order of the nodes in the dependency graph.

2. The method of claim 1 in which processing comprises single pass execution when there are no logical loops.

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12. The apparatus of claim 8 , the processing circuitry to determine that the communication message is a text message create a text title with denoted text from the text message when the text message has text denoted for the text title, and create a text title with a portion of the text message when the text message does not have text denoted for the text title.

8. An apparatus, comprising: a housing comprising a front face and a back side; a primary display; a secondary display comprising a prism arranged to create an illusion that a text title is floating in a middle of the prism and the prism is rounded toward the front face of the housing to enable a user to read a side display screen when the apparatus is lying flat on the back side, the primary and secondary displays comprising separate displays; and processing circuitry coupled with the primary display and the secondary display, the processing circuitry to: receive a communication message, determine whether the communication message is a voice message, an e-mail message or a text message, use one or more words from the voice message as text for the text title when the communication message is a voice message, use one or more words from the e-mail message as text for the text title when the communication message is an e-mail message, use one or more words from the text message as text for the text title when the communication message is a text message, and display the text title associated with the communication message on the secondary display.

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30. The method of claim 23 wherein the copying step is only performed where a condition relating to the first and second nodes is satisfied.

23. A method in a computer system, the method performed in a lexical knowledge base derived from one or more dictionaries, the lexical knowledge base comprising a network of nodes each representing a word occurrence in the dictionaries, the lexical knowledge base containing text segment subgraphs each comprising a plurality of nodes and derived from dictionary text segments, the method characterizing the sense of an occurrence of a polysemous word represented as a node of the lexical knowledge base and comprising the steps of: (a) selecting a pair of words having a high level of semantic coherency; (b) identifying in the lexical knowledge base a plurality of text segment subgraphs between the words of the pair; (c) identifying within the identified plurality of text segment subgraphs a first node having no word sense characterization and representing a first occurrence of a first word; (d) identifying within the identified plurality of text segment subgraphs a second node having a word sense characterization and representing a second occurrence of the second word; and (e) copying the word sense characterization of the second node to the first node.

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47. The one or more computer-readable storage media of claim 42 , wherein identifying text comprises identifying words or phrases.

42. One or more computer-readable storage media encoded with instructions that, when executed, cause a processor to perform acts comprising: receiving, via a network connection, a threshold parameter indicating a predetermined threshold similarity of subject matter and an input document associated with a new item available for purchase, the input document to be indexed into a search index file; comparing a subject matter of the input document to a subject matter of an existing document that relates to an item available for purchase and is already indexed into the search index file, wherein the structure of the input document includes at least two fields, the at least two fields each including content, and the predetermined threshold similarity of subject matter exists at least when a percentage of fields in a structure of the input document correspond to fields in a structure of the existing document; determining, based at least on the comparison, that the input document and the existing document meet the predetermined threshold similarity of subject matter; responsive to determining that the input document and the existing document meet the predetermined threshold similarity of subject matter, identifying text in the input document that is dissimilar to text in the existing document; designating any dissimilar text between the input document and the existing document as candidate synonyms; merging the candidate synonyms into the search index file, wherein the merging associates the dissimilar text as synonyms in the search index file; and indexing the input document into the search index file.

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2. The device of claim 1 , wherein the converting comprises converting the image pattern to a first text comprising the detected first telephone number, and wherein the operations further comprise: converting the audio component of the media content to a second text; detecting the second telephone number in the second text; and comparing the first text with the second text to determine whether the first telephone number matches the second telephone number.

3. The device of claim 2 , wherein the operations further comprise buffering a portion of the audio component to generate a buffered portion, and wherein the converting the audio component comprises converting the buffered portion.

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16. A computer system for extracting topic words from electronic documents based on at least one seed word comprising: a. a programmable computer processor; b. a memory readable by the processor; and c. software stored in the memory for execution by the processor, the software comprising: i. a keyword identification module for identifying keywords in each document that are indicative of the topic of the document; ii. an evaluation module for evaluating the relevance of each of the documents to the at least one seed word; iii. a key topic document identification module for identifying at least one key topic document that is relevant to the at least one seed word; iv. a selection module for selecting a subset of the documents, referred to as topic documents, by an iterative process starting with the at least one key topic document and then selecting other documents if their keywords are sufficiently similar to the keywords contained in the previously selected topic documents; and v. an extraction module for extracting a set of topic words from the topic documents.

19. The system of claim 16 wherein in the step of identifying keywords, the keyword identification module excludes words contained in a pre-defined dictionary from consideration.

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2. The method of claim 1 , further comprising: in response to determining that the candidate partition of the next highest rank set of predicted input characters is unallocated, allocating the next highest rank set of predicted input characters to the candidate partition.

8. The method of claim 2 , wherein the partitions occupy substantially all of the virtual keyboard.

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10. The context aware method of claim 6 , wherein the first A-box corresponds to information that defines a relationship between an instance and a class.

6. A context aware method comprising: extracting, from a semantic model, a terminological-box (T-box) comprising information that defines a relationship between classes; generating a reasoning rule based on the T-box; generating a first assertion box (A-box) based on sensing information, wherein the sensing information relates to information sensed to recognize a user state; and inferring a user context based on the reasoning rule and the first A-box.

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2. The method according to claim 1 , wherein said at least one executable code snippet comprises a primary executable code snippet and a secondary executable code snippet, and wherein the method further comprises: executing the primary executable code snippet; and in response to the primary executable code snippet failing to correct said semantic errors identified for said node chosen, automatically executing the secondary executable code snippet.

1. A method for correcting semantic errors in code in an integrated development environment, said method comprising: inputting, using a code editor, code being developed in an integrated development environment; identifying, in a syntax tree constructed for said code inputted, one or more nodes containing semantic errors pertaining to use of a third-party library; choosing a node of said one or more nodes identified in said syntax tree constructed containing said semantic errors; displaying multiple suggestions for correcting said semantic errors identified for said node chosen, wherein each of said multiple suggestions include one or more executable code snippets associated with one or more collaboration records located for said node chosen, and wherein said one or more executable code snippets are submitted by peer developers to correct said semantic errors identified for said node chosen; displaying an executable code snippet configuration interface for configuring said one or more executable code snippets, wherein the executable code snippet configuration interface comprises: an input parameter active field for identifying input parameters that are required, by said node chosen, to be used with said one or more executable code snippets; an output parameter active field for identifying output parameters that are required, by said node chosen, to be used with said one or more executable code snippets; an input/output parameter active field for identifying input/output parameters that are required, by said node chosen, to be used with said one or more executable code snippets; and a return value active field for identifying a return value that is required, by said node chosen, to be returned by said one or more executable code snippets; selecting at least one executable code snippet from said one or more executable code snippets displayed for correcting said semantic errors identified for said node chosen; and executing said code inputted in said integrated development environment, wherein said at least one executable code snippet has been previously collected by said integrated development environment, and wherein said at least one executable code snippet selected is automatically invoked to correct said semantic errors identified for said node chosen.

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1. A language processing device comprising: a first analysis unit that performs a predetermined analysis on a natural language sentence including a polysemic word and other words to output a plurality of analysis results for the natural language sentence in accordance with a plurality of meanings possessed by the polysemic word; a second analysis unit that performs a particular analysis on the plurality of analysis results outputted by said first analysis unit to adopt one analysis result from the plurality of analysis results; a storage unit that stores determination information, for each combination of one meaning of said polysemic word with information related to the other words, the determination information indicating whether or not each combination is adopted; an adoption information generation unit that generates adoption information for each combination of the meaning of the polysemic word within each analysis result outputted by said first analysis unit with the information related to the other words, the adoption information indicating whether or not each combination is adopted by said second analysis unit; and a rule generation unit that, when a first said combination that is indicated to be “not adopted” in the adoption information corresponds to the determination information that indicates the first combination is “adopted”, the rule generation unit changes the adoption information for the first combination to “adopted” and subsequently generates a deletion rule for deleting one or more unnecessary analysis results from the plurality of analysis results, the deletion rule being based on the updated adoption information.

2. The language processing device according to claim 1 , wherein each said combination of the meaning of the polysemic word with information related to the other words includes one of the following: a surface string, a word class, a conjugation, and a combination thereof of the polysemic word with words therearound.

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152. The system of claim 149 , wherein the unit of time is not an integer.

149. The system of claim 148 , wherein the term of experience is rounded down to a unit of time.

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13. A computer readable medium having stored thereon one or more sequences of instructions for causing one or more microprocessors to perform the steps for delivery of content from a corpus of data, the steps comprising: receiving a search query; generating a search query result set by searching a corpus of data for items that satisfy the search query; identifying a trigger query, said trigger query associated with a content presentation action; generating a trigger query result set by searching the corpus of data for items that satisfy the trigger query; determining a level of intersection between the search query result set and the trigger query result; and presenting content as specified by the content presentation action when said level of intersection is greater than a predetermined threshold.

16. The medium according to claim 13 , wherein said level of intersection is determined by dividing the number of items in the intersection of the search query results and the trigger query results sets by the number of items in the trigger query result set.

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53. The server apparatus of claim 52 , wherein the at least one computer program is further configured to select advertising content related to the location.

52. Server apparatus, comprising: a processor; a communications interface in data communication with the processor; and a storage device in data communication with the processor, said storage device comprising a storage medium, said storage medium comprising at least one computer program with a plurality of instructions, said at least one computer program being configured to: receive a digital representation derived from speech input relating to an organization or entity which a user wishes to locate, the digital representation being received via the communications interface; based at least in part on the digital representation, identify a location associated with the organization or entity; and enable generation of a graphical or visual representation of the location on a remotely disposed computerized device in order to aid the user in finding the organization or entity, the remotely disposed computerized device having a touch-screen input and display device and a wireless interface enabling communication with the server apparatus via at least one network, the remotely disposed computerized device being disposed within a transport apparatus configured for movement between different locations, the graphical or visual representation of the location configured to be displayed upon the touch-screen input and display device; wherein the at least one computer program is further configured to receive and utilize digital representations of speech in an iterative or hierarchical fashion to allow the user of the computerized device to progress through a menu structure comprising multiple possible matching organizations or entities.

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45. The computer-readable medium of claim 43 , wherein unrolling includes minimizing in-transitions for each state of the automaton.

43. A computer-readable medium that is not a transitory propagating signal, the computer-readable medium including instructions, which when executed by the computer, cause the computer to perform operations comprising: converting a quantification into an automaton, wherein converting includes unrolling the quantification to control an in-degree of the automaton; and converting the automaton into machine code corresponding to a target device.

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8. The method of claim 7 , wherein the file comprises a spreadsheet file.

7. The method of claim 6 , wherein the e-mail message includes a file comprising the translated string.

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1. A non-transitory computer-accessible memory medium that stores program instructions executable by a computer system to perform: providing a graphical program development environment comprising a graphical specification and constraint language that allows specification of a model of computation and explicit declaration of constraints; and creating a graphical program in the graphical specification and constraint language in response to user input, wherein the graphical program comprises: a specified model of computation; a plurality of interconnected functional blocks that visually indicate functionality of the graphical program in accordance with the specified model of computation; and graphically indicated specifications or constraints for at least one of the functional blocks in the graphical program; wherein the specifications or constraints comprise: initiation interval (II), comprising a minimum number of cycles between firings of the at least one functional block; input pattern (IP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the beginning of firing of the at least one functional block, wherein each true value in the sequence denotes consumption of a token at an input terminal of the at least one functional block; and output pattern (OP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the end of firing of the at least one functional block, wherein each true value in the sequence denotes production of a token at an output terminal of the at least one functional block; and automatically generating an output program based on the graphical program, wherein the output program implements the functionality of the graphical program in accordance with the specified model of computation, and further implements the specifications or constraints; wherein the output program is useable to configure a programmable hardware element to perform the functionality subject to the specifications or constraints.

11. The non-transitory computer-accessible memory medium of claim 1 , wherein the specifications or constraints for the at least one functional block are with respect to one or more of: throughput of terminals on the at least one functional block; or latency between inputs and corresponding outputs of the at least one functional block.

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3. The dynamic English graphic playing method of claim 1 , further comprising an executing Step, wherein when the execution Step is defined as Step (B), prior to performing Step (B), a sentence recognition Step (A) is performed, Step (A) comprising Step (A-1) of converting an input sentence into a space and a separate language element, and Step (A-2) of recognizing the converted space and separate language element, comparing the recognized space and separate language element against a data storage unit, separating the compared space and separate language element into a meaningful language element region and a space region surrounding the meaningful language element region, and storing the meaningful language element region and space region, and after the execution of Step B, a sentence reference position moving Step (C) is performed, Step (C) comprising Step (C-) of deleting recognition information on a preceding sentence, and stopping a dynamic graphic conversion, and Step (C-2) of moving reference points of a recognition region and a screen display region such that Step (A) is repetitively performed on a next sentence or a sentence on a next line.

5. The dynamic English graphic playing method of claim 3 , further comprising converting an image represented on a computer-based display device to a file format capable of being stored in a state of storage at a certain time or in a certain represented state.

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11. The method of claim 8 , wherein the selected one or more second terms include multiple consecutive words that occur after the one or more first terms that refer to the particular entity.

8. A computer-implemented method comprising: receiving a particular sequence of terms that occurs in a document, wherein the document includes multiple sequences of terms outside of the particular sequence; determining that the particular sequence of terms includes one or more first terms that refer to a particular entity; selecting one or more second terms from the particular sequence of terms that includes the one or more first terms that refer to the particular entity; generating, for each of the selected one or more second terms that are from the particular sequence of terms that includes the one or more first terms that refer to the particular entity, a name-context pair that includes (i) the one or more first terms that refer to the particular entity, and (ii) the selected one or more second terms; determining, for each distinct name-context pair, a context consistency measure that is an estimate of a probability that the selected one or more second terms of the respective name-context pair will appear in another sequence of terms based on the occurrence in the other sequence of terms of the one or more first terms that refer to the particular entity of the respective name-context pair; and storing context-entity name data that associates one or more of the distinct name-context pairs with the corresponding context consistency measure in a memory.

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14. The computing device of claim 8 , wherein instructions to at least one of: read the design of the electronic circuit at the first level, represent the instances of the elements of the electronic circuit in the data structure, parse the design of the electronic circuit to automatically generate the list of regular expressions, prune the connectivity descriptors of the electronic circuit and optimize the at least one of the design verification and the design simulation of the electronic circuit at the second level are provided through at least one of: a module executing on the processor, packaging thereof with at least one of an operating system and an application executing on the computing device, and a driver component.

8. A computing device comprising: a memory; and a processor communicatively coupled to a memory, the processor being configured to execute instructions to: read a design of an electronic circuit at a first level higher than a second level at which at least one of design verification and design simulation of the electronic circuit is to be conducted, represent instances of elements of the electronic circuit in a data structure, parse, at the first level, the design of the electronic circuit to automatically generate a list of regular expressions related to text-matching strings with the elements of the electronic circuit based on removing undesired instances related to the elements of the electronic circuit from the data structure, prune, at the second level, connectivity descriptors of the electronic circuit based on the automatically generated list of regular expressions at the first level, and optimize the at least one of the design verification and the design simulation of the electronic circuit at the second level based on the pruned connectivity descriptors thereof.

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10. A spoken dialog system comprising a processor and a memory encoded with computer-executable instructions that, when executed by the processor, perform a method for multiple value confirmation and correction, comprising: responsive to collecting a set of values from a user, inviting the user to interrupt a spoken confirmation of the set of values, previously collected from the user, upon hearing an incorrect value, to correct the incorrect value; presenting the spoken confirmation of the set of previously collected values to the user wherein the spoken confirmation includes a sequence of prompts spoken by the spoken dialog system, the sequence of prompts comprising spoken confirmation values of the set of previously collected values as understood by the spoken dialog system and a pause after each of the spoken confirmation values, each pause except the last immediately followed by a next spoken confirmation value in the sequence of prompts; detecting a user interruption of a spoken confirmation value or a pause in the sequence of prompts, wherein the user interruption comprises an indication that the spoken confirmation value is incorrect; halting the sequence of prompts being spoken by the spoken dialog system in response to detecting the user interruption; collecting a corrected value from the user in response to detecting the user interruption; and providing a new spoken confirmation to the user, wherein the new spoken confirmation includes the corrected value.

11. The spoken dialog system of claim 10 , wherein detecting a user interruption comprises using one or more correction grammars to allow for stating a value correction in multiple ways.

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20. The system of claim 1 , wherein said source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors comprises: a sensor identity (ID) acquisition module configured to acquire one or more identities of the one or more sensors used to sense the at least one physical characteristic of the authoring user.

25. The system of claim 20 , wherein said sensor identity (ID) acquisition module configured to acquire one or more identities of the one or more sensors used to sense the at least one physical characteristic of the authoring user comprises: a sensor identity (ID) acquisition module configured to acquire an identity of a facial expression sensor device or a skin characteristic sensor device used to sense the at least one physical characteristic of the authoring user.

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16. The computer program product of claim 14 , further including a sixth executable portion for merging some of the listing of possible time zones by grouping those of the listing of possible time zones having shared daylight saving transition rules over the predetermined period of time.

14. A computer program product for establishing an applicable local time zone of a web browser in a computing environment, the computer program product comprising a computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising: a first executable portion for querying a plurality of time zone offsets over a predetermined period of time to obtain a listing of possible time zones; a second executable portion for selecting ones of the listing of possible time zones matching a polled absolute coordinated universal time (UTC) offset; a third executable portion for assigning a plurality of numerical weights to the selected ones of the listing of possible time zones according to a weighting process based on the matching polled absolute UTC offset, a matching daylight savings observance type, a matching Hyper-Text Transfer Protocol (HTTP) accept-language header, and a human population size; a fourth executable portion for combining each of the assigned plurality of numerical weights to generate a combined numerical weight for the selected ones of the listing of possible time zones; a fifth executable portion for sorting the listing of possible time zones based on the combined numerical weight; and a sixth executable portion for selecting one of the listing of sorted possible time zones having a highest combined numerical weight of the plurality of assigned numerical weights to format a time stamped output.

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24. The system of claim 18 , wherein the processor is configured to index documents with inheritance metadata.

18. A system for indexing and searching entity-relationship data, comprising: a processor configured to: receive indication of a database of entity-relationship data which includes identifiers of entities and indications of relationships between the entities, indicating which entities are related to each other; represent the entities of the indicated database as respective documents, each document containing content and metadata of a respective entity; represent the entities of the provided database as respective categories; represent each relationship instance, which indicates a relationship between a plurality of entities, in the database, as a category set that contains categories of all participating entities in the relationship; and index the entity-relationship data of a populated logical document model as an inverted index.

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31. The method of claim 23 wherein the textual information comprises a pattern of symbols responsive to a characteristic of the audio information.

23. The method of claim 1 further comprising: providing to the first party textual information corresponding to audio information from the second party.

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15. A non-transitory computer readable medium comprising instructions that, when executed by a processor, perform a method, the method comprising: obtaining a context managed entity from a client system, wherein the context managed entity corresponds to software executing on a computer system; querying a managed entity repository to obtain a plurality of managed entities linked to the context managed entity, wherein the plurality of managed entities comprises a software managed entity, a first hardware managed entity, and a second hardware managed entity; generating a node in a topology model object for each of the plurality of managed entities; generating a plurality of link objects in the topology model object for a plurality of relationships between the plurality of managed entities, wherein the plurality of link objects comprises a containment link object; rendering a topology graph comprising each node and each link object in the topology model object by arranging the nodes into tiers; and expanding the containment link object in the topology graph to show a containment link between the first hardware managed entity nesting as a hardware component within the second hardware managed entity.

17. The non-transitory computer readable medium of claim 15 , wherein the model engine is further configured to: exclude at least one managed entity from the plurality of managed entities based on a view type received from the client system.

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1. A computer-implemented method comprising: identifying, in a plurality of digital videos, a plurality of candidate volumes representing spatio-temporal segments of the digital videos, wherein each of the candidate volumes corresponds to a contiguous sequence of spatial portions of video frames of one of the digital videos, has a starting time and an ending time, and potentially represents a discrete object or action within the video frames, wherein identifying the candidate volumes in the digital videos comprises: stabilizing the digital videos using a video stabilization algorithm and identifying, as a stable segment, a contiguous sequence of frames in one of the digital videos in which a degree of background motion is below a threshold, using a measure of background motion produced by the video stabilization algorithm; determining, for each of the identified candidate volumes, features characterizing the candidate volume, wherein the features are determined from visual properties of the spatial portions of the video frames contained in the candidate volumes; and assigning a verified label to each volume of a plurality of the identified candidate volumes using the determined features, the verified label indicating a particular object or action represented by the volume to which the verified label is assigned.

11. The computer-implemented method of claim 1 , further comprising: receiving a textual search query; determining a match degree to which volumes of a digital video have a verified label matching the search query; and including the digital video in a search result set of videos matching the search query, based at least in part on the match degree.

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15. The method of claim 14 , wherein outputting the second candidate sub-word unit comprises displaying the second candidate sub-word unit.

14. The method of claim 13 , further comprising: producing a second candidate sub-word unit upon triggering the sub-word unit recognition by the handwriting recognition engine; and outputting the second candidate sub-word unit.

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6. The monitoring apparatus of claim 4 , wherein the monitoring apparatus is configured to communicate with the image output device using Hypertext Transfer Protocol (HTTP) and Simple Network Management Protocol (SNMP).

4. A monitoring apparatus for extracting a desired status value related to a remotely monitored image output device, automatically without human intervention, wherein the monitoring apparatus is configured to communicate with the image output device using plural application-layer communication protocols, the monitor apparatus comprising: a processing circuit configured to access a memory associated with the monitoring apparatus to determine, based on a vendor type of the image output device, a communication protocol of the plural application-layer communication protocols, to use to extract the desired status value from the image output device, the memory storing, for each of the plural application-layer communication protocols, information of at least one vendor, the accessing step determining which of the plural application-layer communication protocols can should be used to obtain the desired status value based on the information of at least one vendor stored in the memory and the vendor information of the image output device; access the image output device without human intervention using the determined communication protocol to obtain device information of the monitored image output device that is stored on the image output device; extract the desired status value from the obtained device information; and store the extracted desired status value.

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9. The method of claim 1 , wherein a value derived from the user-interface text to translate is used to search in the translation mechanism.

1. A method to translate displayed user-interface text of a computer application, comprising: intercepting, by a processor coupled to a memory and a screen, a command to display user-interface text on the screen in a first language, the command comprising the user-interface text to display in the first language; extracting user-interface text to translate from the command; querying a translation mechanism by use of the extracted user-interface text; receiving translated user-interface text in a second language from the translation mechanism; and displaying the translated user-interface text in the second language.

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3. A method according to claim 1 , wherein said delivering step comprises delivering said key word signal in Braille form to said first body part of said handicapped person.

1. A method for communicating visual images to a handicapped person, said method comprising the steps of: providing at least one device for physically transmitting information to said handicapped person; providing information about said visual images to said handicapped person using said at least one device; and said information providing step comprising delivering a physical signal representative of a key word describing a portion of a visual image to a first part of a body of said handicapped person using said at least one device and further comprising transmitting at least one physical input describing a dynamic element associated with said key word to a second part of the body of said handicapped person; and wherein Dividing the fingers of a hand of said handicapped person into a first group consisting of a pointer finger and a middle finger and into a second group consisting of a ring finger and a pinky and said transmitting step comprises transmitting information about a bad character to one of said fingers of said first group and transmitting information about a good character to one of said fingers of said second group.

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17. The non-transitory computer program product according to claim 15 , wherein the process further comprises: generating a plurality of examples of a range profile for one or more of said objects of interest from their respective HMMs and using a simulation technique to generate the classification results for a particular set of HMMs so as to predict the potential performance of the classifier.

15. The non-transitory computer program product according to claim 13 , wherein the probabilistic model for the object comprises a set of one or more Hidden Markov Models (HMM), each HMM defining, for a different orientation of the object, probabilities for the possible sequences of distances between the features of the respective object of interest selected from the non-sensor based sources of information.

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16. The computer program product of claim 15 , wherein the computer-usable medium comprises: computer usable program code that executes the simulation engine in cooperation with the high level modeling system to implement a simulation of the circuit design specified by the simulation model; computer usable program code that allocates the block of memory for use by the simulation engine; and computer usable program code that stores state information for the simulation within the block of memory.

17. The computer program product of claim 16 , wherein the computer-usable medium further comprises computer-usable program code that writes contents of the block of memory to a file stored in persistent memory, wherein the file is reloaded at a later time to recall the state of the simulation.

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13. The baggage system of claim 3 , wherein the input attributes include: a location and identification of a baggage item; and a baggage handler identification associated with the baggage item.

3. The baggage system of claim 2 , where the server is further configured to: receive plurality of input attributes of the present event; performing pre-processing on the plurality of input attributes to generate an input data set; generating the output value from the trained model based upon the input data set; and predict an outcome associated with the present event based upon the output value.

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16. The non-transitory computer readable medium of claim 15 , the operations further comprising: outputting the electronic message in the first preferred language for display in a transcript window associated with the second user.

15. A non-transitory computer readable medium storing computer program instructions, which, when executed on a processor, cause the processor to perform operations comprising: receiving a preferred language identification for each of a plurality of message accounts associated with a first user; associating each preferred language identification with a respective one of the plurality of message accounts, each of the plurality of message accounts having a different preferred language identification; determining that a source language of an electronic message sent via a particular one of the plurality of message accounts from the first user to a second user is different from a first preferred language associated with the particular message account; and translating the electronic message to the first preferred language.

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1. A computer system for making available digital documents of different types and content, and responsive to a request for one of the documents received from another computer according to a communication protocol, the computer system comprising: means for receiving an indication of a requested document; means for accessing a definition of additional content for a type of the requested document; means for generating an additional content component according to the definition of additional content for the type of the requested document; means for selecting at least a portion of the content of the requested document; means for combining the additional content component with the content of the selected portion of the requested document to obtain an output document; and means for packaging and transmitting the output document to the other computer according to the communication protocol.

7. The computer system of claim 1, further comprising: means for transforming the portion of the requested document according to an identity of the other computer.

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104. A method to enable improved analysis and use of sociological data, the method comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; and further correcting for email corruption based problems by identifying emails based on hashes of header information; creating frequency occurrence table based on content of emails; and comparing frequency occurrence table, and identifying emails as identical, corrupted, or compared as a result of hash collision.

105. The method of claim 104 , further comprising: enabling a user to select a preferred copy of an email for future use.

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6. The system of claim 1 , wherein the relevant content and the base content are served to a user based on the at least one association, if the user requests the base content.

1. A system configured to associate base content with relevant content, the system comprising: A processor; a parsing module configured to parse the base content to form parsed base content; a unit-dictionary module coupled with the parsing module and including a plurality of query units; a query processing engine coupled with the unit-dictionary module and configured to receive and remove query units from the plurality of query units in the unit-dictionary module; a unit-extraction module coupled with the unit-dictionary module and configured to selectively extract at least one query unit of the plurality of query units from the parsed base content, wherein the parsed base content includes the extracted at least one query unit; a unit-ranking module coupled with the unit-extraction module and configured to rank the extracted query units based on a relevance score and a revenue-generation amount for the extracted query units to identify relevant content, wherein the relevance score is based at least partially on a location of the extracted query unit within the base content; and a unit-matching module coupled with the unit-ranking module and configured to generate at least one association between the base content and the relevant content based on a similarity between the extracted query units and a query unit associated with the relevant content, wherein the relevant content includes at least one advertisement.

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14. The computer program product of claim 12 , wherein the extracted features of the input question are further identified by the computer readable program causing the computing device to: identify one or more tenses associated with the terms added to the extracted features; and add the one or more tenses associated with the terms to the extracted features.

12. The computer program product of claim 8 , wherein the extracted features of the input question are identified by the computer readable program causing the computing device to: identify a utility of each term in the input question; eliminate zero or more terms within the input question that comprise a utility less than a predetermined value; and add the remaining terms in the input question to the extracted features.

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4. The method according to claim 2 , comprising: in the input unit, receiving the query condition regarding structure of the documents to be retrieved; in the first storage unit, storing structure storage-type location information regarding storage location of every structure of each document to be retrieved; and in the processing unit, referring to the structure storage-type location information and performing the first retrieval on the document to be retrieved if the document is determined to include a structure specified in the query condition which is stored on the first storage unit, and referring to the structure storage-type location information and performing the second retrieval on the document to be retrieved if the document is determined to include the structure specified in the query condition which is not stored on the first storage unit, or if the document is determined to include no structure that meets the query condition.

5. The method according to claim 4 , comprising: in the first storage unit, storing cross-document structure priority information defining cross-document priority of the structure of the documents; and in the processing unit, extracting data from each document to be retrieved based on the cross-document structure priority information, and storing the extracted data onto the first storage unit as a partial document, wherein information indicating existence on the first storage unit is used for structures of the documents to be retrieved which are stored on the first storage unit information indicating partial existence on the first storage unit is used for structures of the documents to be retrieved which are partially stored on the first storage unit, and information indicating no existence on the first storage unit is used for structures of the document to be retrieved which are not stored on the first storage unit, and thereby updates the cross-document structure priority information.

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1. A method for creating a concept-object database by an electronic computer, the method comprising: producing an initial set of semantic objects, each semantic object including a reference to encoded information and an initial list of one or more tags; binding hyperlinks to semantic objects and processing the hyperlink-bound semantic objects in order to produce a set of first-level concept objects; and binding additional hyperlinks to first-level concept objects and further processing the additional-hyperlink-bound first-level concept objects to produce a set of concept objects stored in a concept-object database by searching electronically encoded information, such as web pages within the world-wide web, to identify hyperlinks within the electronically encoded information to identify hyperlinks contained in the electronically encoded information, each identified hyperlink encoded in a hyperlink-based object; and for each semantic object, binding, to the semantic object, hyperlinks that reference the encoded information referenced by the semantic object to create a hyperlink context for each semantic object, determining whether a hyperlink-bound semantic object can be promoted to a first-level concept object, and when hyperlink-bound semantic object can be promoted to a first-level concept object, processing the hyperlink-bound semantic object to produce a corresponding first-level concept object associated with emergent terms.

6. The method of claim 1 wherein a hyperlink-based object that encodes a hyperlink includes: a first-reference that references electronically encoded information; anchor-text that describes the referenced electronically encoded information; and a second reference that references the encoded information containing the hyperlink.

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1. A method for importing data from a document to a repository, comprising: creating a map file corresponding to a document type of the document, wherein the map file maps the document type of the document to a plurality of information fields stored in the repository for the document type; storing the map file in a directory and providing a location of the directory to the repository; selecting data from the document; creating a macro for the document, wherein the macro is dynamically inserted into the document from which data is imported when the document is loaded from the repository, and wherein the macro is configured to: access the map file at the directory location stored in the repository, determine the plurality of information fields corresponding to the document type of the document from which data is imported from the map file, and dynamically create a context menu, in response to the selection of data, comprising the plurality of information fields, wherein the context menu is a user interface that is created using the map file, wherein the macro is specific to a document application in which the document is loaded; mapping the selected data to one of the plurality of fields in the repository by selecting the one of the plurality of information fields displayed in the context menu; inserting a comment into the document by a user importing the data, wherein the comment indicates that the selected data is imported into the repository; and importing the selected data from the document to the selected information field in the repository using the map file, wherein the selected data is copied to the map file, which acts as an intermediary storage file between the document and the repository, until the stored selected data is loaded from the map file into the repository at a later time.

2. The method of claim 1 , further comprising: loading the document from a repository application comprising the repository.

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35. The apparatus of claim 33 , wherein (C) comprises deriving, from the likelihood and the measure of relevance, a timescale adjustment factor that adjusts a playback rate of the audio stream.

33. The apparatus of claim 31 , further comprising: a text-to-speech engine to play the emphasis-adjusted audio stream.

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4. A method according to claim 2 comprising calling a deleted data values check routine to check for any records using data including data values deleted from the at least one candidate taxonomy.

2. A method according to claim 1 , wherein the interface of the metadata repository exposes at least one check routine, the method including calling the or each check routine to cause the repository service to check for a specific inconsistency between the at least one candidate taxonomy and the data stored in the repository.

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32. A non-transitory computer readable medium for processing a voice input provided in response to a prompt, the computer readable medium storing instructions for: automatically providing a sequence of prompts in response to a user invoking a voice mode, wherein each prompt is associated with a respective time period of a plurality of time periods; receiving a voice input while a prompt of the sequence of prompts is being provided; identifying a characteristic time associated with the received voice input; identifying a time period of the plurality of time periods that includes the characteristic time; and applying the received voice input to a respective prompt of the sequence of prompts associated with the identified time period.

39. The computer readable medium of claim 32 , wherein the applying comprises providing one or more variables needed to perform an operation associated with the prompt corresponding to the identified time period.

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7. A method of providing variability rules for component model and architecture design, the method comprising: setting, via a processor, variability of component model elements to produce variability-set component model elements; determining a category of implicit variability rules with respect to the variability-set component model elements and component model elements associated with the variability-set component model elements; applying the implicit variability rules, which are given to the category, to the component model elements associated with the variability-set component model elements; and managing a list of variability elements in the component model and setting condition information for each variability, wherein at least one of the variability-set component model elements is designated as at least one from among optional, alternative, selective, and mandatory, and wherein the variability of the mandatory at least one of the variability-set component model elements is not automatically changed even when the implicit variability rules are applied.

10. The method of claim 7 , wherein the option is independently given to the component model elements and selected according to conditions.

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8. The apparatus according to claim 2 , wherein each of the documents included in the document set is a structured document that is separated into document elements each of which corresponds to one of intention representations, and the extracting of the feature words comprises extracting the feature word from the document elements.

2. The apparatus according to claim 1 , wherein the extracting of the feature words comprises extracting words subjected to intention representation by using more than one type of intention representation and selecting words from the extracted words based on a predefined criteria, as the feature words.

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13. The system of claim 12 , wherein at least a portion of the database stored in an electronically readable medium is implemented in a server system remote from the user.

12. A system for searching for and presenting content items as an arrangement of conceptual clusters to facilitate further search and navigation on a display- constrained device, the system comprising: a database stored in an electronically readable storage, medium for cataloging a relatively large set of content items, at least some of the content items having metadata to specify explicit concepts associated with the content items, and at least some of the metadata including phrases having more than one metadata term; an electronically readable medium containing instructions for causing a computer system to: input logic for receive from a user incremental input to incrementally identify more than one search term for desired content items; select from the relatively large set of content items: a first set of content items, wherein all search terms match metadata terms of a single one of the metadata phrases of each content item of said first set; a second set of content items, wherein a first subset of the search terms matches at least one metadata term of at least a first metadata phrase of each content item of said second set; and a third set of content items, wherein a second subset of the search terms matches at least one metadata term of at least a second metadata phrase of each content item of said third set, the first metadata phrase differing from the second metadata phrase; for group the content items the second and third sets have in common to form an intersection set for user-implied concepts inferred from the explicit concepts associated with the metadata of the content items of the intersection set; organize the content items of the first set and the intersection set into conceptual cluster sets: the content items of the first set being organized into explicit conceptual cluster sets based on the metadata phrases having metadata terms matching the search terms so that content items having a same metadata phrase matching the search terms are clustered together; and the content items of the intersection set being organized into user-implied conceptual clusters based on at least the first and second metadata phrases the content items of the intersection set have in common so that content items having same first and second metadata phrases matching the search terms are clustered together; and present on the display-constrained device the content items organized into the explicit conceptual cluster sets and the user-implied conceptual cluster sets: each explicit conceptual cluster set identified based on the metadata phrase common to the content items of said explicit conceptual cluster set having metadata terms matching the search terms; and each user-implied conceptual cluster set identified based on the first and second metadata phases the content items of said user-implied conceptual cluster set have in common.

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1. A method comprising: receiving, at a computing device, a query template comprising a request for web pages from a data set that resides in a cloud comprising a cluster of computing devices; optimizing, via the computing device, the query template to segment the query template into an offline phase and an online phase, the offline phase comprising a query segment with no parameters, the online phase comprising a query segment with parameters; executing, via the computing device, the offline phase in accordance with the cluster of computing devices of the cloud to build one or more indexes; executing, via the computing device, the online phase in accordance with a client computer, wherein the building of the index is based on a space constraint associated with the client computer; sending, via the computing device, the one or more indexes based on the space constraint to the client computer; providing a versioning of a query template to help a user backtrack to correct a mistake; receiving a request to correct the mistake; and returning to a previous version of the query template.

5. The method of claim 1 , further comprising supporting long-term user sessions that span periods of disconnected operation while the user waits for the outcome of offline processing steps.