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11. The electronic device according to claim 9 , wherein the processor determines that the ambiguous input is a portion of a salutation by determining that the ambiguous input is disposed adjacent to a salutatory expression.

9. An electronic device comprising: a processor apparatus including a memory having a plurality of objects and at least one message stored therein, an output apparatus; and an input apparatus having a plurality of input members, at least some of the input members having a plurality of characters assigned thereto; the processor apparatus being adapted to: generate a new message in response to receiving one of a replying or forwarding command with respect to the at least one message, provide a dictionary comprising language objects associated with the at least one message, the first dictionary being stored in the memory, detect an ambiguous input comprising actuations of a number of the input members of the plurality of input members, determine that the ambiguous input is a portion of a salutation, identify one of the language objects stored in the dictionary that corresponds with the ambiguous input, and cause the output apparatus to output at least a portion of the identified language object as a proposed disambiguation of the ambiguous input.

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13. A system for associating users with a micro-community, the system comprising: one or more processors; an object type parser stored on a memory and executable by the one or more processors, the object type parser configured to receive a search query from a first user, receive an object reference to a calendar entry based on a search result from the search query and to parse the object reference to identify account references associated with the calendar entry including an account reference for a second user in a social network; an account reference fetcher stored on the memory and executable by the one or more processors, the account reference fetcher configured to receive the object reference and to generate a list of the account references, at least one of the account references being associated with the second user in the social network; a ratings server stored on the memory and executable by the one or more processors, the ratings server configured to generate a rating for each account in the list based on relevance to the object reference; and a micro-community fetcher stored on the memory and executable by the one or more processors, the micro-community fetcher configured to receive the object reference and to determine whether the micro-community exists, the micro-community being relevant to the object reference and responsive to determining an absence of the micro-community, to determine a subset of account references from the list of the account references to associate with the micro-community based on the ratings, to generate the micro-community for the subset of account references including the first and second users associated with the calendar entry.

21. The system of claim 13 , wherein the micro-community fetcher generates the account references that are explicitly associated with the object reference.

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18. The method of claim 17 , wherein the application is a flash movie.

17. A method for adding functionality to an automated application served to a client-computing device by a first provider, the method comprising: at a second provider including a microprocessor, receiving a first request from the client-computing device for client-side script source code to add functionality to the application being served by the first provider, the first request being automatically generated without user interaction by API included in the application being served by the first provider, and including a URL with information about the functionality; based on the information in the URL, generating client-side script source code including the functionality and sending the code including the functionality to the clientcomputing device using the microprocessor; receiving a second request for client-side script source code from the clientcomputing device, the second request including a URL with information about objects identified in the application as relating to the functionality and a request for information about the objects; generating client-side script source code, based on the second request, including information about the objects encoded using a scripting language; and sending the client-side script source code including information about the objects to the client-computing device and instructions that cause the client-computer to display the information using the microprocessor.

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1. A method for communication facilitation in a location within a virtual world, the method comprising: providing in a computer a virtual world including multiple different locations in which different avatars interact through an exchange of messages; identifying jargon including acronyms for an organizational relationship characteristic of a particular one of the different locations in one of the messages the jargon being terminology common to an organizational culture specific to the particular one of the locations in the virtual world, but foreign to others of the participants not belonging to the organizational culture specific to the particular one of the locations in the virtual world; and, responding to a selection of a word in the one of the messages by determining if the selected word is jargon and if so, looking up a glossary entry for the jargon of the selected word, emphasizing the jargon of the selected word from other text in the one of the messages upon finding the glossary entry for the jargon of the selected word in the dictionary of jargon and rendering the glossary entry in the one of the messages in connection with the emphasized jargon.

5. The method of claim 1 , wherein rendering the glossary entry comprises: rendering a pop-up box with the glossary entry in connection with the one of the messages responsive to a mouse over event associated with the selected word.

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8. The method of claim 1 , the hierarchical relationship including one or more further records situated between the one or more child records and the parent record.

1. A method comprising: accessing one or more updates associated with a data record, the one or more updates stored in a database, the data record being a parent record, the one or more updates related to one or more child records associated with the parent record, the parent record being at a first level of a hierarchy of records, the child records being at a second level of the hierarchy of records; providing the one or more updates as one or more candidates for publication on an information feed associated with the data record, the information feed capable of being displayed on a display device; and selecting a number of the candidates for publication on the information feed based on one or more criteria.

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34. The method of claim 31 , wherein the number of shards into which the phrase posting list for the first phrase is divided corresponds to the number of index servers in the indexing system.

31. A method of indexing documents of a document collection in an indexing system that includes a plurality of index servers, the method comprising: determining a phrase posting list associated with a first phrase, the phrase posting list identifying documents of the document collection associated with the first phrase; dividing the phrase posting list for the first phrase into a plurality of different shards, each shard identifying a subset of the documents identified by the posting list; storing each different shard of the phrase posting list for the first phrase on a corresponding different index server; determining a phrase posting list associated with a second phrase, the phrase posting list identifying a number of documents of the document collection having at least one occurrence of the second phrase; dividing the phrase posting list for the second phrase into a plurality of different shards, each shard identifying a subset of the plurality of the documents identified by the posting list; and storing each different shard of the phrase posting list for the second phrase on a corresponding different index server, wherein shards of the phrase posting list for the first phrase and shards of the phrase posting list for the second phrase, which identify the same document, are stored on the same index server.

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5. A system on a mobile device for providing access to supplemental electronic materials associated with a document, the system comprising: a text capture component, wherein the text capture component includes a scanner programmed to capture a human-readable text sequence of a print version of a document, wherein the human-readable text sequence includes text that is perceptible to a human on the print version of the document; a processing component, wherein the processing component is programmed to process data from the text capture component to recognize the text; an identification component, wherein the identification component is programmed to determine, from the recognized text, a text string corresponding to the captured human-readable text sequence and identify the document using the text string; a content access component, wherein the content access component is programmed to: identify supplemental electronic materials associated with the document, the supplemental electronic materials being materials presentable using an audio or visual medium; determine that a request to access the supplemental electronic materials associated with the document is implicit in receiving the human-readable text sequence; receive a set of access rules for the supplemental electronic materials associated with the document; and resolve the request by enabling access to the supplemental electronic materials when the request satisfies the access rules or denying access to the supplemental electronic materials when the request does not satisfy the access rules, wherein resolving the request by enabling access to the supplemental electronic materials when the request satisfies the access rules includes permitting access to the supplemental electronic materials when the received human-readable text sequence includes an indication that the human-readable text sequence was captured from the print version of the document; and a content presentation component, wherein the content presentation component is programmed to present the supplemental electronic materials associated with the document to a user associated with the mobile device.

8. The system of claim 5 , wherein the content presentation component is programmed to present the supplemental electronic materials associated with the document to the user via a computing system in communication with the mobile device.

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19. The method of claim 15 , where the aggregator function sums values in a data set.

15. The method of claim 1 , wherein in creating the execution plan, analysis of a query includes determining whether the query includes an aggregator function.

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19. The computer-readable storage device of claim 15 , having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising tailoring wordings in the spoken dialog system associated with the dialog based on a current context and a set of business rules.

15. A computer-readable storage device having instructions stored which, when executed by a computing device configured to perform speech recognition, cause the computing device to perform operations comprising: at a turn in a dialog between a user and a spoken dialog system: nominating a set of dialog actions and a set of contextual features, wherein the computing device uses a partially observable Markov decision process in parallel with a conventional dialog state to perform the nominating; and generating an audible response in the dialog based on the set of contextual features, via a machine learning algorithm, from the set of dialog actions.

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13. The system of claim 11 , wherein the first and the second grid are of the same size.

11. A system for enhanced optical character recognition, the system comprising: a logic unit for identifying a sample character in a textual context to be optically recognized; a logic unit for comparing the sample character with a template character, wherein the sample character is scaled into a first grid and the template character is scaled into a second grid; a logic unit for identifying one or more pixels in the sample character within the first grid and one or more pixels in the template character in the second grid, wherein the one or more pixels are identified as belonging to a foreground category in the textual content, a foreground pixel having at least N gradients corresponding to edges of the foreground pixel that are juxtaposed to a neighbor pixel, wherein a contour foreground pixel has at least one gradient that is neighbored by a background pixel in the textual context; identifying one or more template contour pixels in the template character that correspond to at least one sample contour pixel in the sample character, a logic unit for mapping the at least one sample contour pixel to the corresponding template contour pixels such that one or more distances are calculated between the at least one sample contour pixel and the respective one or more template contour pixels; and a logic unit for determining that the sample contour character and the template contour character are a match based on an analysis of the one or more distances.

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19. A computer implemented method for generating a Boolean query comprising: a. getting training data, by a processor, wherein the training data comprises a plurality of training documents and wherein each of the plurality of training documents comprises at least one training token; b. clustering the plurality of training documents, by the processor, into a plurality of clusters based on the at least one training token of the plurality of training documents, wherein each cluster comprises at least one training document; c. generating, by the processor, the Boolean query for a cluster of the plurality of clusters based on an occurrence of the at least one training token in the at least one training document of the plurality of training documents; d. getting production data, wherein the production data comprises a plurality of production documents and wherein each of the plurality of production documents comprises at least one production token; and e. executing, by the processor, the Boolean query on the plurality of production documents in the production data.

26. The method of claim 19 , wherein the plurality of training documents and/or the plurality of production documents comprises one item selected from the group comprising: a document, an email, a content of a website, a content of a blog, a transcript of a voice call, an identifiable item from a video, an identifiable item from a picture, a transcript of a conversation, a document containing different languages, and a transcript of an audio portion of a video.

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19. The method in claim 4 further comprises a training phase having the steps of: detecting whether each one of a plurality of predetermined features exists in each message of a training set of m messages belonging to the first class so as to yield a feature matrix containing feature data for all of the training messages, wherein the plurality of predetermined features defines a predefined n-element feature space and each of the training messages has been previously classified as belonging to the first class; reducing the feature matrix in size to yield a reduced feature matrix having said N features (where n, N and m are integers with n>N); and applying the reduced feature matrix and the known classifications of each of said training messages to the classifier and training the classifier to recognize the N features in the m-message training set.

20. The method in claim 19 wherein said indication is a predefined color coding of all or a portion of the incoming message.

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12. The system of claim 9 , wherein selecting either the global set of search results or the location-specific set of search results further comprises only selecting the global set of search results if a top ranked result of the global set of search results is different from a top ranked result of the location-specific set of search results.

9. The system of claim 1 , wherein selecting either the global set of search results or the location-specific set of search results as a primary set of search results comprises selecting the global set of search results if the clustering score for the global set of search results indicates that a predetermined percentage of entities associated with search results in the global set of search results are physically located within a predetermined distance of each other.

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17. The computer-implemented method of claim 13 , wherein the fresh indices are continually updated with information from relevant classified queries in reaction to a popularity of a query.

13. A computer-implemented method of identifying and clustering queries that are increasing in popularity using a computing system having memory, processor, and data storage subsystems, the computer-implemented method comprising: receiving a search query request from a user input device; identifying a spike in incoming query stream activity comprising the search query request; temporally correlating the spike in the incoming query stream activity with relevant content from a plurality of historical indices as a result of searching said historical indices; correlating the spike in the incoming query stream activity with relevant content from a plurality of fresh indices as a result of searching said fresh indices, wherein the fresh indices contain information and results from recently crawled content sources; analyzing results from searching the historical indices and the fresh indices to determine if the search query request should be clustered with an existing group of search query results; prioritizing results of the search query request according to an age and size of identified cyclic clustered results; and communicating the prioritized results of the search query request to a user output device.

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15. A method for displaying usage history of a calculator, the calculator having a user interface, the method comprising: receiving a first mathematical expression in an expression entry area on the calculator: displaying a result in a first window on the calculator, wherein the result displayed in the first window comprises a result for the first mathematical expression; displaying, in a second window on the calculator, a usage history comprising the first mathematical expression, a second mathematical expression, and results, wherein the results displayed in the second window comprise the result for the first mathematical expression and a result for the second mathematical expression, wherein the usage history is displayed in a hierarchical tree such that a result for a given mathematical expression is displayed on a different hierarchical level than the given mathematical expression; and displaying organizational tabs for the second window, wherein each organizational tab is operable to display a given category of data associated with the usage history, wherein the hierarchical tree is expandable and collapsible, and wherein the hierarchical tree can be expanded and collapsed while the result is displayed in the first window.

20. The method of claim 15 wherein the given category of data associated with the usage history comprises one or more of the following: results, variables, functions, and expressions.

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3. The method of claim 1 , the relevant metadata based at least in part on one or more schemas.

1. A method for translating a relational database query into a multidimensional expression language (MDX) database query comprising: parsing a relational database query into one or more relational database query tokens; filtering zero or more of the one or more relational database query tokens based at least in part on business logic to create a set of filtered relational database query tokens, the filtering comprising: removing a relational database query token, from the one or more relational database query tokens, responsive to determining that the relational database query token corresponds to a field not supported by a multidimensional database and is associated with a return of a dataset that exceeds a threshold; identifying relevant metadata, from a metadata store, associated with metadata associated with the set of filtered relational database query tokens, the relevant metadata comprising current multidimensional metadata and trend related multidimensional metadata; translating at least some relational database query tokens of the set of filtered relational database query tokens into one or more work item query language (WIQL) tokens; retrieving a first group of one or more MDX tokens based at least in part on the relevant metadata; retrieving a second group of one or more MDX tokens based at least in part on the one or more WIQL tokens; arranging at least some of the one or more MDX tokens of the first group and at least some of the one or more MDX tokens of the second group based at least in part on the metadata associated with the set of filtered relational database query tokens; and generating one or more MDX database queries for trend related information and current information based at least in part on at least some of the arranged MDX tokens, at least some of the parsing, the filtering, the identifying, the translating, the retrieving a first group, the retrieving a second group, the arranging, and the generating implemented at least in part via a processing unit.

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12. The method of claim 1 : wherein the media content item comprises metadata associated with the delimited segment; and wherein evaluating is based, at least in part, on evaluating at least a portion of the metadata associated with the delimited segment.

1. A method for analyzing a media content item, the method comprising: receiving, by a media analyzer, the media content item; evaluating, by the media analyzer, at least a portion of the media content item; delimiting, by the media analyzer, a segment of the media content item; based, at least in part, on the evaluating, associating, by the media analyzer, a sentiment-state keyword with the delimited segment; and storing, by the media analyzer, a map of the delimited segment, the map comprising the associated sentiment-state keyword and a delimitation of the segment; wherein the delimited segment comprises an element selected from the group consisting of: audio content and video content; wherein the associating is based, at least in part, on an evaluation of an element selected from the group consisting of: audio content of the delimited segment and video content of the delimited segment; wherein associating comprises associating a confidence value with the sentiment-state keyword associated with the segment; and wherein storing comprises storing the keyword confidence value in the map of the delimited segment.

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1. A method for providing automatic diagnosis and decision support in whole-body imaging, comprising: using whole-body imaging to obtain a first set of image data of a patient; detecting a plurality of anatomical landmarks in the first set of image data using a classification-based method; fitting a statistical whole-body atlas using the first set of image data and the plurality of anatomical landmarks, wherein the statistical whole-body atlas encodes anatomical or functional variations of the whole-body or body parts and includes statistics on global and local shape deformations, and statistics on joint articulations; and using the statistics in the statistical whole-body atlas to characterize pathological findings in terms of a diagnosis, wherein the statistical whole-body atlas comprises at least one of mathematical distributional appearance models or spatial relational models of organs or structures in one or more whole-body imaging modalities, wherein the mathematical distributional appearance models or spatial relational models are learned based on annotated training data.

2. The method of claim 1 , wherein the first set of image data is obtained using one or more imaging modalities.

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18. The computer system of claim 1 , wherein the content script manager is configured to evaluate the page using a combination of page analysis logic, a whitelist, or a blacklist.

1. A computer system comprising: at least one processor configured to execute instructions stored on a non-transitory computer-readable medium to execute a browser application to provide a browser interface; a rendering engine configured to cause the at least one processor to execute, within an execution environment, a page script of a page to be rendered within the browser interface, the page script configured to interact with a page model to render the page within the browser interface; an extension manager configured to cause the at least one processor to execute an extension file which modifies a functionality of the browser application in association with the rendering of the page, including detecting a content script associated with the extension file which, during execution, interacts with the page model; and a content script manager configured to cause the at least one processor to evaluate the page prior to allowing execution of the content script associated with the extension file by the rendering engine, wherein the content script manager is configured to prevent the content script from accessing the execution environment when the page fails the evaluation; and wherein the content script manager is configured to allow the content script to access the execution environment when the page passes the evaluation.

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8. The method as recited in claim 4 , wherein the an act of evaluating the query expression to obtain a property value for the property comprises an act of evaluating the query expression to obtain a further data provider, and wherein the further data provider virtualizes the property value from the data provider.

9. The method as recited in claim 8 , wherein the act of evaluating the query expression to obtain a further data provider comprises an act of evaluating a further data construction statement contained in the data provider to create the further data provider.

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12. The method of claim 11 wherein generating the at least one title text region includes at least one of: determining a geometric distance from the title text region to a first text region in the extracted article; and determining a keyword distance from the title text region to the first text region in the extracted article.

14. The method of claim 12 wherein the keyword distance includes: extracting a stem of at least one word in the title text region; extracting a stem of at least one word in at least one of the body text regions; and matching the stem from the title text region with the stem of the at least one body text region.

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6. The method of claim 5 , wherein the links are presented in ranked order based on the determined value for the web page corresponding to the link.

5. The method of claim 1 , further comprising: determining, by one or more computing devices, a value for each of the web pages based at least in part on the number of relevant interactions with the web page by one or more second users.

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14. The apparatus of claim 13 , wherein the subtitle loading buffer is configured to load the text subtitle stream including the style segment which includes a data field indicating a number of the set of the at least one user control style defined in the style segment for each of the least one region style.

15. The apparatus of claim 14 , wherein the subtitle loading buffer is configured to load the text subtitle stream including the style segment which defines the at least one set of user control style, the number of the at least one set of user control style defined for each of the at least one region style is less than or equal to 25.

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34. The non-transitory computer-readable memory of claim 27 , wherein speech samples are scored by a human, and a statistical model is built using the features and human scores; wherein the assessment score is based on the scoring model and one or more of the calculated features.

35. The non-transitory computer-readable memory of claim 34 , wherein the statistical model is built using multiple regression.

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12. The method of claim 11 further comprising: removing unparseable text from the legal document; chunking the received legal document; and splitting the legal document into sentences by using the chunks.

11. A method for extracting text in a legal document for preparation of headnotes, the method comprising: detecting one or more predetermined features in each sentence of the legal document, wherein the one or more predetermined features are based on grammatical constituents of text in the legal document; computing occurrence of the detected one or more predetermined features in each sentence of the legal document; assigning a score to each predetermined feature detected in each sentence by referring to feature graphs corresponding to each predetermined feature, wherein the feature graphs are retrieved from a repository; combining the assigned score in each sentence to obtain a final headnote score for each sentence; comparing the final headnote score with a predetermined threshold; tagging text in each sentence as headnote and non headnote based on the comparison; and rendering the legal document with text tagged as headnote on a user interface.

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32. The system of claim 29 , further comprising: an additional service generator that generates additional services related to a result of the searching.

33. The system of claim 32 , wherein the additional service is a contents context awareness service including at least one of guide services, selling services, advertising services, education services, consulting services, recommendation services, auction services and administrative services.

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18. The method of claim 17 wherein the pair of input words comprises two different words.

17. A method in a computer system for determining the level of similarity of a pair of input words, the method comprising: identifying a plurality of semantic relation type path patterns, each comprising an ordered series of semantic relation types, whose occurrence between arbitrary pairs of words indicate that the arbitrary pairs of words have similar meanings; and if path patterns occurring between the input words include semantic relation type path patterns among the identified plurality, indicating that the input words are similar in meaning.

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2. The method of claim 1 , wherein the secondary object model is XML.

1. A method for integrating a secondary object model into a programming environment containing a primary object model, the method comprising: differentiating, by a compiler, between a desired access to the primary object model and a desired access to the secondary object model based on an access differentiating syntax that incorporates a notation of the secondary object model and at least one operator of the secondary object model into a syntax of the primary object model, the secondary object model incorporated into the programming environment such that member access to an object may be made according to either the primary or secondary object model; and dynamically computing a desired member name for accessing the object according to the secondary object model by referencing a namespace to identify a member according to the secondary object model.

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4. The method of claim 1 further comprising: providing a third quantum of execution on a second meta-virtual processor to a third scheduler-context of the first scheduler during the first quantum of execution; and providing a fourth quantum of execution on the second meta-virtual processor to a fourth scheduler-context of the second scheduler subsequent to the first quantum of execution on the second meta-virtual processor.

1. A method comprising: providing a first quantum of execution on a first meta-virtual processor to a first scheduler-context of a first scheduler in a meta-scheduler created by a process executing on a computer system; and providing a second quantum of execution on the first meta-virtual processor to a second scheduler-context of a second scheduler in the meta-scheduler subsequent to the first quantum of execution on the first meta-virtual processor, the first and second quantum being expressed in terms of a number of tasks to be executed, the first scheduler including a first plurality of virtual processors, the second scheduler including a second plurality of virtual processors, the first scheduler excluding the second plurality of virtual processors, the second scheduler excluding the first plurality of virtual processors, the first meta-virtual processor being one of a plurality of meta-virtual processors, the plurality of meta-virtual processors, the first plurality of virtual processors, and the second plurality of virtual processors having a same cardinality.

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1. A computer implemented method comprising: receiving, at an Internet search system, a search query; receiving multiple search results, each of the search results identifying an Internet resource indexed by the search system that satisfies the query; determining that the search query matches a name of a user that submitted the search query; providing, in response to the search query, a ranking of one or more of the search results and a personal knowledge panel comprising one or more items of user-provided information about the user, wherein the personal knowledge panel includes multiple input fields for updating the user-provided information of the knowledge panel; receiving updated user information that was provided using the input fields of the personal knowledge panel; and associating the updated user information with an account of the user.

2. The method of claim 1 , wherein the personal knowledge panel allows the user to modify the one or more items of user-provided information without the navigating away from a search results page that includes a presentation of the one or more search results.

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15. A computer-readable medium comprising instructions to cause a computing system to process a relational database query, said instructions comprising: a first set of instructions, executable on a processor, configured to generate a relational model of a multidimensional data source using one or more of a schema for the multidimensional data source and metadata for the multidimensional data source, the relational model comprises: a relational-to-multidimensional mapping between a virtual relational table for a relational database application corresponding to the multidimensional data source and the multidimensional data source, and the schema and metadata accessed from the multidimensional data source for the virtual relational table; a second set of instructions, executable on a processor, configured to form the relational database query from the relational database application against the relational model of the multidimensional data source using a graphical user interface, wherein the graphical user interface: displays a presentation layer representation of the virtual relational table for the relational application corresponding to the multidimensional data source, enables pointer-driven selection for query of one or more tables and columns of data stored in the multidimensional data source and represented by the displayed presentation layer representation, and enables selection of a detail filter to apply against the relational model; a third set of instructions, executable on a processor, configured to receive the relational database query, the received relational database query being drawn against the relational model of the multidimensional data source, wherein the relational database query specifies a detail filter against the relational model having selected predicates; a fourth set of instructions, executable on the processor, configured to use the relational-to-multidimensional mapping to translate the received relational database query into a multidimensional database query, wherein the multidimensional query specifies, for each of the selected predicates that can be applied against the relational model of the multidimensional data source before a crossjoin operation is performed, applying the selected predicate against the relational model of the multidimensional data source before the cross join operation is performed; a fifth set of instructions, executable on the processor, configured to submit the multidimensional database query for execution against the relational model of the multidimensional data source, wherein the multidimensional data source comprises three or more dimensions; and a sixth set of instructions, executable on the processor, configured to display a result of the multidimensional database query against the modeled multidimensional data source.

16. The computer-readable medium of claim 15 further comprising: a seventh set of instructions, executable on the processor, configured to receive, in response to submitting the multidimensional database query, a multidimensional database query result; and an eighth set of instructions, executable on the processor, configured to use a relational-to-multidimensional mapping to translate the received multidimensional database query result into a relational database query result.

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22. The method of claim 21 wherein the step of applying the selected business rule further includes the step of comparing the generated list of keywords with a master key word list to generate a priority value.

21. The method according to claim 20 wherein analyzing the content of the call includes generating a list of key words based on the content of the incoming call and generating a priority value based on the list of key words.

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56. A method of extracting a second sequence, comprising the steps of: receiving a first sequence (S′); retrieving a dual SSM Sequence Model (SSM) Matrix generated from the first sequence and a second sequence (D(S″, S′)); extracting the second sequence (S″) from the dual SSM Matrix (D(S″, S′)) and a first histogram vector (h′) of the first sequence (S′).

75. The method of claim 56 , adapted for analysis of biological sequences, wherein the step of receiving a first sequence (S′) comprises the step of receiving a DNA sequence, and wherein the step of retrieving comprises the step of retrieving a dual SSM Matrix generated from the DNA sequence and an additional property that is associated with the DNA sequence (D(S″, S′)), and wherein the step of extracting comprises the step of extracting the additional property that matches the DNA sequence from the step of receiving.

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1. A method performed by one or more devices, the method comprising: identifying, by at least one of the one or more devices, a group of search result documents that are responsive to a search query; determining, by at least one of the one or more devices, a measure of staleness of a search result document in the group of search result documents; determining, by at least one of the one or more devices, whether a stale document is preferred for the search query, where determining whether a stale document is preferred for the search query includes: determining, based on selections of older documents over newer documents, whether a first document was previously selected over a second document in a set of search results relating to the search query or a similar search query, where the first document is ranked lower than the second document, and where the first document is older than the second document; identifying the search query as a search query for which a stale document is preferred when the first document was previously selected over the second document in the set of search results relating to the search query or the similar search query; generating, by at least one of the one or more devices, a score for the search result document based on: the measure of staleness of the search result document, and whether a stale document is preferred for the search query; and ranking, by at least one of the one or more devices, the search result document with regard to at least one other search result document, of the group of search result documents, based on the generated score.

4. The method of claim 1 , where the measure of staleness of the search result document is based on anchor growth associated with the search result document.

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10. The method of claim 1 further comprising, iterating the method for one or more additional semantic identities requested by the agent.

1. A machine-implemented method, comprising: assigning interests of an agent, the interests are associated with one or more categories, the agent represents a primary identity for a principal and a principal is a resource, the primary identity is a true persona of the agent; associating the one or more categories with the agent; generating a semantic identity for the agent that is associated with the one or more categories; subsequently using the semantic identity, by the agent to perform network transactions as the semantic identity, and the semantic identity and the primary identity are formulated from identifiers and secrets to provide a statement of roles and permissions that a particular identity has in relation to particular resources that are accessed in the network transactions; mining the network with the semantic identity and presenting the mining process to network onlookers as coming from the semantic identity and not the agent, the network is mined within a defined semantic space that is representative of the one or more categories; and maintaining anonymity of the primary identity during the mining of the network, the semantic identity uses a password for the semantic identity to assure services of the network that identification is for the semantic identity and not the agent.

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1. A computer-implemented method, the method comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client.

5. The method of claim 1 wherein the output is a prediction.

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23. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; and in the social graph, updating a value of the first edge between the first and second nodes, wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises: extracting a user identifier from a cookie received with the first activity data; and if a match for the user identifier is not found in the social graph, performing a probabilistic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browser types; browser versions; or user navigational, geo-temporal, and behavioral patterns.

24. The method of claim 23 wherein a personally identifiable information of the sender includes an e-mail address of the sender.

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15. The system of claim 14 , wherein the instructions cause the one or more data processing apparatus to perform operations comprising: receiving a second content item request that specifies a second phrase of one or more words; determining that two keywords in a same content distribution campaign are both eligible to be selected as a controlling keyword for the second content item request; identifying a tiebreaker rule based on data associated with the two keywords; identifying, from the two keywords, a second controlling keyword based on the tiebreaker rule; and providing, in response to the second request, data associated with the second controlling keyword.

18. The computer readable medium of claim 15 , wherein identifying a second controlling keyword based on the tiebreaker rule comprises: determining that a first keyword from the two keywords has a less specific match with the phrase than a second keyword from the two keywords; determining that a first quality score for the first keyword exceeds a second quality score for the second keyword; and selecting, in response to the determination, the first keyword as the second controlling keyword.

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1. A method for entering information in an electronic equipment for composition of a message, the method comprising: receiving one or more symbols from an input device to create a message to be transmitted to and read by a recipient, wherein the symbols correspond to one or more alphanumeric characters; requesting local dictionary information related to the received one or more symbols from a local predictive text dictionary application resident in the electronic equipment; requesting remote dictionary information related to the received one or more symbols from a predictive text dictionary application stored on an associated remote server, wherein the request for remote dictionary information is transmitted automatically upon expiration of a predetermined period of time in response to the received one or more symbols from the input device; receiving the requested local dictionary information and the remote dictionary information, wherein the received local dictionary information and the remote dictionary information includes predictive text that begins with the symbols received from the input device; and outputting the predictive text in a user-sensible format, wherein the predictive text from the local dictionary information is output in priority before the predictive text received from the remote dictionary information.

2. The method according to claim 1 , wherein the received symbols are used to identify remote dictionary information including at least one of a word, phrase or expression stored in the remote predictive text dictionary application.

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21. The computing system of claim 17 , wherein the logic is to determine the valid content boundary within the image by: for each line of a plurality of lines of the image of the text, determining whether the line includes content that is separated by white space from other content within the line by more than a threshold; where the line includes content that is separated by white space from other content within the line by more than the threshold, setting a portion of the valid content boundary corresponding to the line so that the content that is separated by white space from the other content within the line is outside the valid content boundary.

17. A computing system comprising: a processor; a computer-readable data storage medium to store first data representing an image of text and a marking other than the text, and second data representing the text and the marking in non-image form, the marking represented within the second data as if the marking were part of the text; and logic executable by the processor to determine a valid content boundary within the image, the valid content boundary dividing a portion of the image corresponding to the text from and excluding another portion of the image corresponding to the marking, and for each character of a plurality of characters within the second data, to remove the character from the second data where the logic has determined that a location of an image portion within the first data corresponding to the character falls outside the valid content boundary.

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1. A method for document discovery, comprising: receiving a scan of a physical copy of a document comprising a non-text object; determining a first tag for the non-text object by comparing the non-text object with a plurality of templates comprising a plurality of tags, wherein the first tag defines a portion of the non-text object in an original file and specifies a type of the non-text object and a formatting attribute of the non-text object; generating, based on the first tag, non-text object metadata comprising composition information comprising the type and the formatting attribute for the non-text object; searching a plurality of electronic documents stored in a data repository with a search query comprising the non-text object metadata, wherein each of the plurality of electronic documents comprises searchable metadata; comparing the non-text object metadata with the searchable metadata; and providing a location of the original file to a user when the non-text object metadata in the search query matches the searchable metadata of the original file.

4. The method of claim 1 , further comprising: determining whether the user has authorization to access the original file, wherein the location is provided only when the user is determined to have authorization to access the original file.

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7. The method of claim 1 , wherein the input parameters comprise Normalized Auto-correlation Coefficient Function at pitch information.

1. A method of noise-robust speech classification, comprising: inputting classification parameters to a speech classifier from external components; generating, in the speech classifier, internal classification parameters from at least one of the input classification parameters; setting a Normalized Auto-correlation Coefficient Function threshold, wherein setting the Normalized Auto-correlation Coefficient Function threshold comprises: increasing a first voicing threshold for classifying a current frame as unvoiced when a signal-to-noise ratio (SNR) fails to exceed a first SNR threshold, wherein the first voicing threshold is not adjusted if the SNR is above the first SNR threshold, and increasing an energy threshold for classifying the current frame as unvoiced when the noise estimate exceeds a noise estimate threshold, wherein the energy threshold is not adjusted if the noise estimate is below the noise estimate threshold; and determining a speech mode classification based on a the first voicing threshold and the energy threshold.

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19. The apparatus of claim 18 , wherein the font-related properties comprise font identification, a font style, a font size, and a font color.

18. The apparatus of claim 16 , wherein the inline style information is configured to change one of region presentation properties specified by the linked region style for the text string, and the region presentation properties comprises font-related properties.

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1. A method for generating a plurality of application programming interfaces (APIs) in a codeless manner, said method comprising: generating, by one or more processors of an electronic system, a set of data graphs that identifies relationships between data objects included in a description of a database schema of a database; generating, by the one or more processors, the plurality of APIs based on the set of data graphs; publishing, by the one or more processors, the plurality of APIs to a user for selecting an API of the plurality of APIs; and generating, by the one or more processors, a JavaScript object notation based model (JSON-based model) associated with the selected API, wherein the selected API is added to an application that uses the selected API for exchanging data with the database using the JSON-based model; wherein during execution of the application, the JSON-based model is instantiated into a JS object based on the JSON-based model's behavioral description in the JS file and the JSON-based model's property description in the JSON file.

4. The method of claim 1 , wherein the description of the database schema comprises a set of data objects in the database.

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1. A method for machine learning based classification of vascular branches to distinguish falsely detected branches from true branches, comprising: sampling a plurality of overlapping fixed size branch segments from one or more branches of a detected centerline tree of a target vessel extracted from a medical image of a patient; extracting a plurality of 1D profiles along each of the plurality of overlapping fixed size branch segments; calculating a probability score for each of the plurality of overlapping fixed size branch segments based on the plurality of 1D profiles using a trained deep neural network classifier; assigning a final probability score to each of a plurality of centerline points in the one or more branches of the detected centerline tree of the target vessel based on the probability scores of the overlapping fixed size branch segments containing that centerline point; and pruning the one or more branches of the detected centerline tree of the target vessel based on the final probability scores of the plurality of centerline points in the one or more branches of the detected centerline tree of the target vessel to remove falsely detected branches from true branches in the one or more branches of the detected centerline tree of the target vessel.

3. The method of claim 1 , wherein extracting a plurality of 1D profiles along each of the plurality of overlapping fixed size branch segments comprises: extracting, for each of the plurality of overlapping fixed length branch segments, 1D profiles of vessel scale, image intensity, centerline curvature, tubularity measure, image intensity and gradient statistics along and inside a cross-sectional circular boundary, and distance to a most proximal point in the branch of the detected centerline tree.

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25. The method of claim 1 , wherein the at least one feature further comprises whether the search query appears in any of: a display host, an algorithmically generated keyword or summary, or a combination thereof.

1. A method of generating a search result list in response to a search query from a searcher using a computer network, the method executed with a computer having a processor, the method comprising: (a) maintaining a first database including a first plurality of search listings comprising sponsored search listings having a sponsored content; (b) maintaining a second database including documents having a general web content; (c) receiving, by the processor, a search query from the searcher; (d) identifying, by the processor, from the first database a first set of search listings comprising sponsored search listings having documents generating a match with the search query, and from the second database a second set of search listings comprising general web listings having documents generating a match with the same search query as used to identify the sponsored first set of search listings; (e) determining, by the processor, a confidence score for each listing from the first set of search listings, wherein the confidence score is determined in accordance with a relevance of each listing when compared to the listings of the second set of search listings after execution of step (d); (f) ranking, by the processor, the sponsored first set of search listings in accordance, at least in part, with the confidence score for each search listing thereof, wherein the processor associates the sponsored first set of search listings with at least one feature different than the relevance of each search listing when compared to the listings of the second set of search listings, and the processor further orders the sponsored first set of search listings in accordance with the at least one feature, the at least one feature comprising any of a number of clicks, a click-through rate, and a conversion rate derived from historical click-through and conversion data from user activity on the sponsored first set of search listings; (g) computing a plurality of demotion terms related to a plurality of the top-ranked sponsored first set of search listings, wherein the demotion terms capture non-ideal characteristics thereof; (h) updating the confidence score of each of the top-ranked sponsored first set of search listings based on the plurality of demotion terms; and (i) re-ranking the top-ranked sponsored first set of search listings according to the updated confidence scores.

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5. The computer-executable method of claim 1 , wherein analyzing the text to determine whether the text requires at least one diacritical mark comprises scanning the text to determine whether each character of the plurality of characters comprises the at least one diacritical mark.

1. A computer-executable method of diacritizing a text, the method comprising: storing a Hidden Markov Model in computer memory for establishing a probability for associating a given diacritical mark with a given character of the text; inputting a sequence of individual characters of the text into a computer processor, the computer processor programmed for: analyzing the text to determine whether the text requires at least one diacritical mark, the text including a plurality of characters associated with an Arabic language; converting each character to an ASCII code; feeding each ASCII code in sequence to the Hidden Markov Model; applying an expectation-maximization process to each ASCII code starting at one end of the sequence; transitioning from one diacritical mark to another diacritical mark from a set of diacritical marks for each ASCII code; recording a probability for each diacritical mark when associated with each current ASCII code; changing a state of the Hidden Markov Model based on each probability over regularly spaced periods of time; wherein the Hidden Markov Model transitions from state q i at time t to a state q i at time t+1, where t=1, 2, 3, . . . M; and i, j=1, 2, . . . , N, and where M represents a number of the transitions and N represents a number of the states; wherein a transition probability a ij , representing a probability that diacritical mark q i appears directly after diacritical mark q i , equals an expected number of transitions from state q i to state q i divided by an expected number of transitions from state q i , finalizing a diacritical mark having the highest probability for the current ASCII code; processing each character in the sequence of the text, wherein the Hidden Markov Model bases the probability at least in part on the probability of a diacritical mark applied on one or more preceding characters of the sequence and on a context of the text for determining the probability of a diacritical mark on a given character; generating a sequence of the diacritical marks corresponding to the sequence of characters; matching the sequence of diacritical marks with the text to obtain the diacritized text; and displaying the diacritized text on an output device.

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8. The method of claim 1 wherein, in step F, if said speech recognition analysis determines that said spoken response is a request for the identity of the entity responsible for the calling system, the method further comprises initiating a prerecorded response indicating the identity of the calling party, repeating said prerecorded greeting which asks for the target person, and repeating step C through step E.

1. A method of determining the status of an answered telephone during the course of an outbound telephone call comprising: A. placing, with an automated calling system, a telephone call to a location having a telephone number at which a target person is listed; B. after said telephone call being answered, as determined by an initial spoken response, or other audio or telecommunication signals, initiating a prerecorded greeting which asks for the target person; C. receiving a spoken response from an answering person or other audio signal and determining if said spoken response or other audio signal is being provided by an answering machine; D. upon determining that the spoken response or other audio signal is not provide by an answering machine, performing a speaker-independent speech recognition analysis on said spoken response, wherein performing said speaker-independent speech recognition analysis includes initiating a speaker-independent speech recognition application with said target person, wherein the speaker-independent speech recognition application is an interactive speech application configured and arranged to provide a series of acoustic prompts to the answering person by telephonic interaction, to determine the meaning of said spoken response; and E. providing at least one of the following conditional responses based on the meaning of the subsequent spoken response as determined by the speaker-independent speech recognition analysis in accordance with a set of speaker-independent speech recognition enabled states of conversation including (1) the answering person indicates that he or she is the target person, (2) the answering person indicates that he or she is not the target person, (3) the answering person indicates that the target person is not present at the location, (4) the answering person indicates a hold request, (5) the answering person requests the identity of the caller, (6) the answering person indicates that the telephone number is not the correct number for the target person, and (7) the speaker-independent speech recognition analysis cannot determine the meaning of the spoken response from the answering person: a. if said speech recognition analysis determines that said spoken response is a request for the identity of the entity responsible for the calling system, initiating a prerecorded response indicating the identity of the calling party, repeating said prerecorded greeting which asks for the target person, and repeating step C through step E; and b. if said speech recognition analysis cannot determine a status of said spoken response, repeating said prerecorded greeting which asks for the target person, and repeating step C through step E; and F. responding appropriately to the results of the speech recognition analysis.

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3. The method of claim 1 wherein substituting comprises, with respect to an automatic Texture-Coordinate Generation operation using a glTexGen command in OpenGL, calculating a texture coordinate element, storing generated texture coordinate data, and passing to an OpenGL|ES implementation glEnableClientState and glTexCoordPointer commands which contain the stored texture coordinate data.

5. The method of claim 3 wherein the OpenGL|ES implementation supports vertex array.

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23. The one or more non-transitory computer-readable media as recited in claim 20 , wherein the personalized page further comprises a tag portion to display a tag associated with the recommended elements.

20. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors to execute modules comprising: a recommendation creator stored in the memory and executable by the one or more processors to store interactions with a user, the interactions including interactions with elements in an electronic catalog, and to recommend additional elements associated with the elements in the electronic catalog based at least in part on the interactions with the user; a community association engine stored in the memory and executable by the one or more processors to select a subset of discussion forums associated with at least one of the recommended elements, individual ones of the discussion forums including dialog created by a plurality of users that includes opinions that are associated with the at least one of the recommended elements, wherein the community association engine selects the subset of discussion forums by: generating a score for individual discussion forums of the subset of discussion forums; calculating a normalization score for the individual discussion forums by applying a weight to the score of the individual discussion forums, the weight to adjust the score based on a relative frequency of the recommended elements; and selecting one or more of the individual discussion forums having an associated normalization score above a threshold score; and a personalization manager stored in the memory and executable by the one or more processors to present a personalized page including the one or more of the individual discussion forums selected.

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11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search query; identifying a plurality of search results that satisfy the search query; determining that at least one search result of the plurality of search results identifies a music web page having an entry in a database of identified music web pages, wherein the database indicates, for each web page of a plurality of web pages entry, that the web page is a music web page from which music content can be accessed; in response to determining that at least one search result identifies a web page that is a music web page having an entry in the database of identified music web pages, determining, from the database of identified music web pages, that the database associates the music web page with music data provided within the music web page, wherein the music data identifies one or more other music web pages; in response to determining that the database associates the music web page with music data provided within the music web page, generating a presentation for the plurality of search results, including generating a particular search result in the presentation having a link to the web page that is a music web page and having one or more secondary music search result links representing one or more other music web pages associated with the music web page in the database of identified music web pages; and providing the presentation of search results including the particular search result having the one or more secondary music search result links for the one or more other music web pages associated with the music web page in the database of identified music web pages that were determined to be presented in response to the search query.

15. The system of claim 11 , wherein the music content is an audio resource or a video resource.

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23. The computer-readable medium of claim 22 wherein the motion estimation unit is arranged to: wherein the search range is determined by using a syntax counter that counts the number of 0s and number of 1s used to code a single bit of a syntax after the syntax has been binarized; the instructions cause the computing device to: generate the look-up table by associating one or more potential candidate probabilities with each update probability value of a plurality of the update probability values, wherein the update probability values form an index for the look-up table; wherein the search range is set by associating the previous probability and the first candidate probability with respective update probability values indexing the look-up table; the instructions cause the computing device to: generate the look up table by establishing a range of update probabilities as an index of the look-up table by using initial previous probabilities and corresponding initial first candidate probabilities; generate the look-up table by selecting the candidate probabilities for each update probability indexing the look-up table by selecting the probabilities from an initial range of probabilities for placement on the look-up table, wherein the selected candidate probabilities assigned to an update probability (1) each have different probability update costs relative to each other, and (2) have a probability value closest to the update candidate value that is an initial first candidate probability; limit the searching to a maximum of three candidate probabilities in addition to the first candidate probability and for each single bit of a syntax; select candidate probabilities based on, at least in part, comparing a new probability based value to a previous probability based value; select candidate probabilities, at least in part, depending on the results of one of: (1) determining the difference between the new probability based value and a candidate probability from the look up table selected by using the new probability based value as an index number to look up the candidate probability, and (2) determining the difference between (a) a change value based on, at least in part, the difference between the new probability and the previous probability, and (b) a candidate probability from the look up table selected by using the change value as an index number to look up the candidate probability; adjust an initial value of a probability candidate from the look up table depending on a comparison between the initial value and the previous probability based value, and setting the value of the probability candidate by using the difference in a calculation; and perform an early exit comprising using the first candidate probability for updating when a second probability candidate being the first probability candidate selected from the look-up table has a bit-costlarger than or equal to the bit-cost of the first probability candidate; wherein the bit-cost comprises the bit cost to perform the update or the bit-cost to indicate an update is to be performed or both, and in the bitstream.

22. At least one non-transitory computer-readable medium having stored thereon instructions that when executed cause a computing device to: receive image data comprising a syntax having a sequence of symbols to be entropy coded; and update a previous probability from a previous frame relative to a current frame being entropy encoded that a symbol will occur in one of the sequences comprising: set a search range among a set of possible update probabilities comprising: set a first candidate probability as one end of the search range by using a count of a syntax counter and without regard to bit-cost to update the previous probability, and set another end of the search range as the previous probability; select one of the candidate probabilities on a look-up table and within the search range to update the previous probability for coding of the symbol, and selecting based on, at least in part, the bit-cost associated with updating the previous probability with at least one of the candidate probabilities; and update the previous probability by using the selected candidate probability.

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19. The continuous speech recognition system of claim 18 , further comprising: a database to store each word from the output module with an assigned robust confidence level parameter and a start and stop time code from that word; an intelligence engine configured to assign a higher weight to recognized words with a robust confidence level above a threshold than recognized words below the threshold, and use the weight for the recognized words when queries are made with the user interface; a special N-gram repository coupled to the run-time correction module, where the special N-gram repository acts as a repository to store all special N-grams, sequences of linguistic items xyz, that have significantly different counts/occurrences in the corpus of domain specific text analyzed than would be expected compared to a background training data from the general-corpus statistical language model indicative of text phrases in general use, where the special N-grams (xyz) are three or more linguistic items in that sequence and are stored along with the actual counts of the number of times that N-gram appeared in the corpus of domain specific text analyzed, and the special N-gram repository when queried with a linguistic sequence of xyz returns whether the N-gram xyz is included in the repository database and the observed counts associated with that special N-gram (xyz); the domain specific count database coupled to the run-time correction module, where the count database returns the linguistic sequences of xy, the N-gram (xyz), and the observed counts of both C(xy) and C(xyz) in the corpus of domain-specific text analyzed when requested by the run-time correction module, but is not itself modified either during a training time or at run time; and a statistical language correction module that uses the established criterion based on the statistical test to determine whether a difference in the observed counts in the domain specific count database of sequences of linguistic items x, y and each of the possible linguistic items z are in fact significantly different from an estimated amount of counts of that same linguistic sequence xyz derived from the general use statistical language model, wherein the units of the linguistic items xyz are words, word phrases, or a combination of both.

18. A continuous speech recognition system over a network, comprising: a continuous speech recognition engine that includes front-end filters and sound data parsers configured to convert a supplied audio file of a continuous voice communication, as opposed to a paused voice command communication, into a time coded sequence of sound feature frames for speech recognition, a speech recognition decoder module having an input to receive the time coded sequence of sound feature frames from the front-end filters as an input, where the speech recognition decoder module applies a speech recognition process to the sound feature frames and determines at least a best guess at each recognizable word that corresponds to the sound feature frames, a user interface of the continuous speech recognition system has an input to receive the supplied audio files from a client machine over the wide area network and supply the supplied audio files to the front end filters, a general-corpus statistical language model that provides probability estimates of how linguistically likely a sequence of linguistic items are to occur in that sequence based on an amount of times the sequence of linguistic items occurs in text and phrases in general use, wherein the speech recognition decoder module requests a run-time correction module for one or more corrected probability estimates P′(z|xy) of how likely a linguistic item z follows a given sequence of linguistic items x followed by y; where x, y, and z are three variable linguistic items supplied from the decoder module, and the decoder module has an input to receive back the one or more domain correct probability estimates from the run-time correction module for one or more possible linguistic items z that follow the given sequence of linguistic items x followed by y, a first input in a run-time correction module configured to receive requests from the decoder module to return the one or more domain correct probability estimates for the one or more possible linguistic items z that could follow the given sequence of linguistic items x followed by y, wherein the run-time correction module is trained to linguistics of a specific domain, and is located in between the speech recognition decoder module and the statistical language model in order to adapt the probability estimates supplied by the general-corpus statistical language model to the specific domain when those probability estimates from the general-corpus statistical language model significantly disagree by at least an established criterion based on a statistical test with the linguistic probabilities in that domain, a second input in the run-time correction module configured to receive from the statistical language model one or more probability estimates P(z|xy) of how likely are each of the possible linguistic items z that could follow the given sequence of linguistic items x followed by y, an output in the run-time correction module to return to the decoder module one or more domain corrected probability estimates P′(z|xy) of how likely are each of the possible linguistic items z that could follow the given sequence of linguistic items x followed by y; an output module of the speech recognition system configured to provide a representation of what uttered sounds and words were inputted into the speech recognition system based on the domain corrected probability estimates; and a server to host the continuous speech recognition engine.

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26. The method of claim 20 , further comprising causing display of advertising for at least one organization or entity which is geographically proximate to the organization or entity at the location.

27. The method of claim 26 , wherein the digitized representation of speech is generated based on a speech input of a user when the user is riding within a moving transport apparatus.

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7. A computer program product for determining digital content sensitivity comprising a non-transitory computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to identify a plurality of tags from a first set of tagged documents in a first repository; computer usable program code configured to identify a plurality of tags from a second set of tagged documents in a second repository, wherein access to documents in the second repository is more restrictive than access to documents in the first repository; computer usable program code configured to, for each of a plurality of tags in at least one of the first set and the second set: determine a ratio of tag instances in the second repository to tag instances in the first repository; determine whether the ratio exceeds a previously determined threshold; when the threshold is less than the previously determined ratio, change an indicator of at least of one tagged document associated with the tag that indicates that the tagged document is not likely to contain sensitive content; and when the threshold exceeds the previously determined ratio, notify a user via a user interface of a computing device, wherein the notifying confirms that the tagged document associated with the tag contains sensitive information, and responsive to a positive response by the user input via the user interface, change the indicator of at least one tagged document associated with the tag that indicates that the tagged document is likely to contain sensitive content.

10. The computer program product of claim 7 , further comprising: computer usable program code configured to, for each tagged document having a changed indicator: execute a content analysis program that analyzes whether the tagged document contains sensitive information; utilize results from content analysis program to determine whether the tagged document is to be indicated as containing sensitive information or indicated as not containing sensitive information, wherein use of the tags to initially change the indicator reduces processing overhead compared with executing the content analysis program against all tagged documents in the first repository and the second repository.

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4. The non-transitory computer-readable storage medium of claim 1 , wherein the method performed when the computer-program code is executed on the suitably programmed system further comprises: transmitting, by the suitably programmed system, to the first user terminal a first indication of the first contextual object for display by the first user terminal in association with the value of the data measure; and transmitting, by the suitably programmed system, to the first user terminal a second indication of the first contextual object for display by the first user terminal in place of the first indication, the second indication denoting that contents of the first contextual object have changed relative to the contents of the first contextual object when the first indication is displayed.

1. A non-transitory computer-readable storage medium having a computer program stored thereon for causing a suitably programmed system to process by one or more computer processors computer-program code by performing a method when the computer-program code is executed on the suitably programmed system, the method facilitating collaboration, the method comprising: processing, by the suitably programmed system, a first request from a first user terminal of a plurality of user terminals to associate a first contextual object with a data measure mapped to a multi-dimensional data model, the first contextual object comprising information received by the first user terminal from a first user of the first user terminal, the multi-dimensional data model configured for access by online analytical processing (OLAP) applications; determining, by the suitably programmed system, coordinates of a plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; storing, by the suitably programmed system, in an electronic data storage the first contextual object in association with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; receiving, by the suitably programmed system, a second request from a second user terminal of the plurality of user terminals, the second request dynamically generated based on a value of the data measure being displayed by the second user terminal to a second user of the second user terminal, the second request indicating the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure, the second request configured to identify contextual objects associated with the coordinates; determining, by the suitably programmed system, an existence of contextual objects that are associated with the coordinates indicated in the second request; retrieving, by the suitably programmed system, the first contextual object from the electronic data storage using the coordinates of the plurality of data dimensions of the multi-dimensional data model; transmitting, by the suitably programmed system, to the second user terminal an indication of the first contextual object for display by the second user terminal in juxtaposition with the value of the data measure; and transmitting, by the suitably programmed system, to the second user terminal the first contextual object.

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29. A non-transitory computer-readable medium embodying a program of instructions for generating a certified electronic document when executed by a computer, the program of instructions operable to cause the computer to perform steps comprising: receiving, from a single computer, first identification information associated with a first signatory user; receiving, from the single computer, second identification information associated with a second signatory user; receiving from the single computer, third identification information associated with a notary user; identifying, on a display, at least one unexecuted electronic document that requires execution by the first and second signatory users; receiving a first user command from the single computer identifying the assent of the first signatory user to the execution of the at least one unexecuted electronic document; receiving a second user command from the single computer identifying the assent of the second signatory user to the execution of the at least one unexecuted electronic document; receiving a third user command from the single computer identifying the presence of a notary user with the first signatory user; and in response to receiving the first user command and the second user command, electronically executing the at least one unexecuted document by applying official electronic notarization indicia associated with the notary user to the at least one unexecuted document to create at least one electronically executed document, the official electronic notarization indicia certifying the presence of the notary user at the execution of the at least one executed and certified electronic document by the first user and identifying the notary user as a registered and valid notary meeting at least one jurisdictional requirement.

32. The non-transitory computer-readable medium of claim 29 , wherein: receiving the first user command comprises identifying that the first user used an input device associated with the first computer to click on a first signature box within the at least one unexecuted electronic document; and receiving the second user command comprises identifying that the second user used the input device associated with the first computer to click on a second signature box within the at least one unexecuted electronic document.

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14. The computer program product of claim 13 , wherein: the positions of the array respectively correspond to positions in a set of consecutive storage positions of a memory device.

13. A computer program product executable in a non-transitory computer readable storage medium for using Superword-Level Parallelism (SLP) in processing a plurality of statements, wherein the statements are associated with an array having a number of array positions, and each statement includes one or more expressions, the computer program product comprising: instructions for gathering isomorphic and non-isomorphic expressions for each of the statements into a merge stream of mixed isomorphic and non-isomorphic expressions, the merge stream being furnished with a location for each gathered isomorphic expression and each gathered non-isomorphic expression, wherein the location for a given expression is associated with one of the positions of the array; instructions for selectively identifying one or more sets of expressions in the merge stream that are aggregatable by a SLP packing operation, and applying SLP packing operation to the identified one or more sets of expressions in order to merge the identified one or more sets of expressions into one or more isomorphic sub-streams; instructions for selectively combining the expressions of the one or more isomorphic sub-streams, and other non-isomorphic expressions of the merge stream, into a number of input vectors that are substantially equal in length to one another; instructions for generating a location vector containing the respective locations for all of the isomorphic and non-isomorphic expressions in the merge stream; instructions for generating an output stream comprising the expressions of the number of input vectors, wherein the expressions are arranged in the output stream in an order that is determined by the respective locations contained in the location vector; and instructions for preserving at least one location vector or a set of location vectors at each step during processing.

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1. A computer-implemented apparatus that enhances search result listings, comprising: a processor operatively coupled to a computer readable medium having stored thereon the following computer executable components: an attribute value ranking component comprising a search engine search result list sorted by search results rank, and further sorted by attribute value as a primary sort and rank as a secondary sort, wherein an attribute value rank is calculated for each of the attribute values; grouped search results comprising the search result list resorted by the calculated attribute value ranks, and further resorted by the attribute values, and still further resorted by the search results rank; a search result display component that provides search result groupings based on the group-by ranking for interaction with a user; and computer-readable storage medium comprising data structures and code for causing a computer to execute the attribute value ranking and search result display components, wherein the object oriented search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page.

3. The computer-implemented apparatus of claim 1 , wherein the display component provides a user selectable set of attributes that are available for group-by ranking of the object oriented search result list.

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32. The computer-readable medium of claim 31 , wherein receiving the first representation of the access token from the IdP further comprises: generating an original token; modifying the original token to obtain a modified token; and providing the modified token to the IdP to obtain an access token for accessing the RP.

33. The computer-readable medium of claim 32 , wherein the first representation of the access token includes a signed modified token by the IdP and second representation of the access token includes a signed original token by the IdP.

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3. The syntax-based document analysis system of claim 1 , where the document type specific syntax definition further comprises: a second structure category component for the document structure; a third structure category component for the document structure; and a fourth structure category component for the document structure.

1. A syntax-based document analysis system comprising: a memory comprising: a document type specific syntax definition for syntactically correct document structure, the syntax definition comprising a first structure category component for the document structure; document type specific document structure identifiers; an electronic document including a document structure instance; a first editable electronic spoken language glossary comprising permissible constituents associated with the first structure category component; executable instructions that define a syntax-based document analysis module, the syntax-based document analysis module operative to: analyze the electronic document to determine a document type of the electronic document; retrieve a document specific parameter set for the document type; obtain the document type specific document structure identifiers from the document specific parameter set; identify the document structure instance in the electronic document by locating at least one of the document type specific document structure identifiers that were obtained from the document type; determine whether the document structure instance includes any of the permissible constituents in the first electronic spoken language glossary consistent with the document type specific syntax definition; and, perform a document analysis operation based on whether the document structure instance includes any of the permissible constituents in the first electronic spoken language glossary consistent with the document type specific syntax definition; and, a processor operative to execute the executable instructions.

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5. A method for outputting formatted information comprising the steps of: providing an input data text file comprising a plurality of name/value pairs; providing a computer program including a formatting source code for producing an output in a first format; providing a recipe text file built using a grammar providing a plurality of lines each representing a rule on how to parse text within said recipe text file, and comprising a plurality of formatting descriptions, at least some of said formatting descriptions indicating a name link to one or more of said plurality of name/value pairs; converting said recipe text file into a sequence of executable objects; receiving a first request from said computer program for rendering said output; and executing said sequence of executable objects, in response to said first request, to render one or more of said plurality of name/value pairs into said output in a second format in accordance with said plurality of formatting descriptions, without modifying said formatting source code; modifying said recipe text file to form a modified recipe text file comprising one or more modified formatting descriptions, at least some of said modified formatting descriptions indicating a modified name link to one or more of said plurality of name/value pairs; converting said modified recipe text file into a modified sequence of executable objects; receiving a subsequent request for rendering said output; and in response to said subsequent request, executing said modified sequence of executable objects to render one or more of said plurality of name/value pairs into said output in a modified format in accordance with said plurality of modified formatting descriptions, without modifying said formatting source code.

8. The method of claim 5 , wherein said step of executing the modified sequence of executable objects produces a report.

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3. The method according to claim 2 , further comprising associating, by the node, each of the extracted features with a set of weighted feature attributes.

4. The method according to claim 3 , further comprising determining, by the node, relatedness of each of the extracted features based on one or more weighted feature attributes.

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1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: selecting a question submitted to a question answering (QA) system, wherein the question pertains to a domain specific corpus ingested by the QA system; analyzing data pertaining to a plurality of answers generated by the QA system, wherein the analysis results in a stability characteristic pertaining to each of the plurality of answers, and wherein the analyzing comprises: analyzing one or more characteristics of answer change pertaining to each of the plurality of answers, wherein the analysis results in a plurality of change frequencies pertaining to each of the plurality of answers; and computing, for each of the plurality of answers, a stability score related to the stability characteristic, by combining the plurality of change frequencies; adjusting a confidence value associated with each of the plurality of answers based on the respective answer's stability characteristic; providing one or more of the plurality of answers to a first requestor based on the adjusted confidence values; storing, in a data store accessible by the QA system, a plurality of inference chains that include a change timeframe and the stability score corresponding to each of the answers; receiving a subsequent question submitted to the QA system, wherein the subsequent question is substantially similar to the question and results in one or more of the plurality of answers being retrieved by the QA system; retrieving one or more stored inference chains from the data store, wherein the retrieved inference chains pertain to the one or more answers retrieved by the QA system; and providing the one or more answers retrieved by the QA system and data pertaining to the retrieved inference chains to a second requestor.

2. The method of claim 1 further comprising: determining one or more key characteristics pertaining to each of the plurality of answers; identifying a set of answers that has changed over time, wherein the set of answers includes one or more answers from the plurality of answers; and identifying one or more reasons that the set of the answers changed by searching the domain specific corpus.

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20. The system of claim 15 wherein the query engine is further configured to: determine a score associated with each of the plurality of e-mails in response to a weighted average for a sender identifier related to an e-mail message and one or more recipient identifiers related to the e-mail message, the weighted average quantifying text contributed by the sender of the e-mail message; and generate the set of results based on at least one score associated with at least one e-mail.

15. A system for searching for e-mails, the system comprising: a set of one or more processors; and a set of one or more storage devices, each storage device communicatively coupled to at least one processor in the set of one or more processors and configured to store computer-executable instructions, the set of one or more storage devices storing a set of computer-executable instructions representing: a crawler configured to receive a plurality of e-mails; an indexer configured to store index information associated with the plurality of e-mails in a first database and a full-text index in a second database; and a query engine configured to: receive information indicative of one or more search terms, determine a query plan based on the one or more search terms that specifies an interleaving between querying the first database and querying the second database, the interleaving defining how results of a first database query against one database in the first or second databases influence a second database query against the other database in the first or second database, perform a search in response to the query plan to determine information related to the one or more e-mails, and generate a set of results based on the information related to the one or more e-mails.

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11. The non-transitory computer-readable medium of claim 8 , wherein said generating said derived XML schema includes: making a second determination that among instances of a certain element contained in said collection of XML documents that at least a threshold portion of said instances conform to one or more value constraints; and in response to said second determination, causing said derived XML schema to define said one or more value constraints for said element.

14. The non-transitory computer-readable medium of claim 11 , wherein said one or more value constraints are based on a string pattern.

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2. The method of claim 1 wherein grouping text segments as coarse grained text fragments in dependence upon the logical operators further comprises: grouping text segments as coarse grained text fragments in dependence upon formatting codes embedded within the text passage and punctuation.

1. A method of natural language processing (‘NLP’), the method comprising: receiving, by an NLP module, the NLP module including automated computing machinery configured for NLP, text specifying predetermined evidence; receiving, by the NLP module, a text passage to process, the text passage including conditions and logical operators, the text passage comprising criteria for evidence; decomposing, by the NLP module, the text passage into coarse grained text fragments, including grouping text segments as coarse grained text fragments in dependence upon the logical operators; analyzing, by the NLP module, each coarse grained text fragment to identify conditions within the coarse grained text fragment; evaluating, by the NLP module, each identified condition in accordance with the predetermined evidence and predefined condition evaluation rules; evaluating, by the NLP module, each coarse grained text fragment in dependence upon the identified condition evaluations and the logical operators of the coarse grained text fragment including: evaluating each OR logical operator as the higher value of each evaluated condition of the OR logical operator; evaluating each AND logical operator as the lower value of each evaluated condition of the AND logical operator; and calculating a fragment score for each coarse grained text fragment as the average of the evaluations of the OR logical operators and the AND logical operators of the coarse grained text fragment; and calculating, by the NLP module in dependence upon the evaluations of each coarse grained text fragment, a truth value indicating a degree to which the evidence meets the criteria of the text passage.

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31. The method of claim 25 , wherein the concept is a first concept, further comprising: refining the first concept based on a relationship to a second concept before using a processor to perform the multi-dimensional analysis.

32. The method of claim 31 , wherein the set of data objects is a first set of data objects, and the second concept is present in a second set of data objects different from the first set of data objects.

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8. The pivotal bone anchor assembly of claim 1 , wherein the shank capture structure mates with a retainer having a partially spherical-shaped outer surface that conforms with a profile of the partially spherical-shaped lower surface of the shank capture structure and engages the partially spherical-shaped internal surface of the cavity.

9. The pivotal bone anchor assembly of claim 8 , wherein a bottom surface of the insert engages the retainer.

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16. The method of claim 1 further comprising: classifying a candidate visual pattern into the first child class by processing an image that depicts the candidate visual pattern with a classifier module assigned to the parent class, the classifier module including the modified weight vector.

1. A method comprising: classifying a reference set of visual patterns that belong to a parent class into mutually exclusive child classes that include first and second child classes, a visual pattern from the reference set being classified into the first child class instead of the second child class; modifying a weight vector that corresponds to the parent class, the modified weight vector altering a first probability that the visual pattern belongs to the first child class and a second probability that the visual pattern belongs to the second child class; based on the altered first and second probabilities, removing mutual exclusivity from the first and second child classes by adding the visual pattern to the second child class; and using a processor, generating a hierarchy of classes of visual patterns, the hierarchy including the parent class and the mutually nonexclusive first and second child classes that each include the visual pattern.

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30. A computer-implemented system, comprising: one or more processors; one or more non-transitory computer readable storage media; computer readable instructions stored on the one or more non-transitory computer readable storage media which, when executed by the one or more processors, implement a first cluster configured to perform operations comprising: receiving, at a first cluster, a search query, the first cluster being a first data intake and query system; transmitting, through a firewall of either the first cluster or a cloud-based cluster, a request for information identifying a plurality of indexers of the cloud-based cluster, the cloud-based cluster being a second data intake and query system; in response to the request, obtaining, from the cloud-based cluster, the information identifying the plurality of indexers, wherein the first cluster and the cloud-based cluster each include at least one master node that is knowledgeable about active indexers within its respective cluster, and the information identifies the plurality of indexers based on the at least one master node of the cloud-based cluster identifying the active indexers; distributing the search query to the plurality of indexers of the cloud-based cluster and one or more indexers of the first cluster, said distributing using the obtained information identifying the plurality of indexers and being through the firewall; and receiving, at the first cluster, a response to the distributed search query from at least one of the plurality of indexers of the cloud-based cluster wherein each response from a respective indexer is produced by the respective indexer based on an evaluation, by the respective indexer, of the distributed search query.

40. The system as described in claim 30 , wherein the system further comprises: one or more additional processors; one or more additional computer readable storage media; computer readable instructions stored on the one or more additional computer readable storage media which, when executed by the one or more processors, implement the cloud-based cluster.

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1. A computer implemented method for generating a qualified set of data, the method comprising: receiving, by at least one processor, an input set of data; determining, by the at least one processor analyzing the input set of data, a domain that characterizes a subject matter of the input set of data; computing, by extracting a common feature from the input set of data by the at least one processor, a probability that a specific user created a first portion of the input set of data; identifying, by the at least one processor, the first portion of the input set of data based, at least in part, on the first portion of the input set of data having the common feature; generating, by the at least one processor, based, at least in part, on the domain, on the probability and on the first portion of the input set of data having the common feature, a user identifier associated with the first portion of the input set of data; storing, by the at least one processor, the user identifier in a data repository; computing, by the at least one processor, based at least in part on the domain and the user identifier, a credibility measure; computing, by the at least one processor, based at least in part on the credibility measure, a quality factor associated with the first portion of the input set of data; generating, by the at least one processor, based at least in part on the quality factor exceeding a quality factor threshold, the qualified set of data comprising data, among the first portion of the input data, that exceeds the quality threshold; and outputting, by the at least one processor, the qualified set of data.

6. The method of claim 1 , wherein the analyzing the input set of data includes using at least one of a web crawler technique, a pattern recognition technique, and a natural language processing technique.

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1. A television receiver remote controller, comprising in combination: a first storage device storing electronic program guide (EPG) data as an EPG database that relates content to television channels containing said content, the first storage device forming a part of a television receiver device; the remote controller being contained in a remote controller housing, the housing containing: a second storage device; a data interface that receives the EPG database from the first storage device forming a part of the television receiver device and stores the EPG database on the second storage device; a speech interface that receives speech input from a user and produces speech signals therefrom; a natural language speech processor engine that receives the speech signals and translates the speech signals to a query of the EPG database stored on the second storage device; and a processor that receives results of the query from the natural language speech processor, and either conveys the results of the query to a user utilizing a user interface or sends navigation commands to the receiver.

11. The receiver remote controller according to claim 1 , wherein the television receiver device comprises one of a cable set-top box, satellite set-top box, IPTV set-top box, broadcast TV adapter, and broadcast television receiver.

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1. A method for shifting and recharging an emotional state of a user with word sequencing presented on a data processing apparatus with a display and an input, the method comprising the steps of: receiving, from the user through the input of the data processing apparatus, a selection of a first word sequence set defined by a mood recharging characteristic value, the first word sequence set including a plurality of words each with at least one corresponding definition; generating on the display with a first predefined typeface a first one of the plurality of words in the selected first word sequence set; generating on the display with a second predefined typeface, while the first one of the plurality of words remains generated on the display, a first one of the at least one corresponding definition of the first one of the plurality of words in the selected first word sequence set for a time duration corresponding to a predefined cadence rate value; and prompting the user with a question related to the mood recharging characteristic value and associated with the first word sequence set.

19. The method of claim 1 , further comprising: transmitting to a remote server, a word sequence set purchase request including a payment authorization; receiving a second word sequence set from the remote server; and storing the second word sequence on the data processing apparatus.

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10. The system of claim 9 , wherein the primary speech database has been further modified by identifying boundaries of the primary speech segments.

11. The system of claim 10 , wherein phone boundaries of the primary speech segments are identified using a zero-crossing calculation.

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4. The method of claim 1, wherein the step of aurally providing information of matches resulting from the search further comprises the steps of: displaying one or more matches resulting from the search, wherein the matches comprise orthographic information; receiving an indication of a possible selection of a first match from the one or more matches; in response to the received indication of a possible selection of the first match, causing information about the first march to be electronically spoken.

5. The method of claim 4 wherein the one or more sets of orthographic information and the matches are displayed with associated pictures.

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5. A computer-implemented method comprising: as implemented by one or more computing devices configured with specific computer-executable instructions, outputting a portion of an audio content item synchronously with a portion of a textual content item; generating, within the portion of the textual content item, an output indicator indicating a location within the portion of the textual content item that corresponds to a current output position within the portion of the audio content item; receiving first data from an input device; determining the first data corresponds to a predefined gesture to cause display of a rotational navigation control element on a display device; displaying the rotational navigation control element using the display device; receiving second data from the input device, the second data representing a rotational input associated with the rotational navigation control, the rotational input representing a request to navigate the textual content item, using the output indicator, to locate a specific word within the textual content item and further representing a request to navigate, in the audio content item, to a location corresponding to the specific word within the textual content item; displaying the output indicator at the third location specific word within the second textual content item; outputting a second portion of the audio content item from a location in the audio content item that corresponds to the specific word within textual content item located using the rotational input.

8. The computer-implemented method of claim 5 further comprising outputting an additional portion of the textual content item beginning at the specific word within textual content item.

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1. A method of providing cross-domain semantic ranking of complete input phrases for a digital assistant, comprising: receiving a training corpus comprising a collection of complete input phrases that span a plurality of semantically distinct domains; for each of a plurality of distinct words present in the collection of complete input phrases, calculating a respective word indexing power across the plurality of domains based on a respective normalized entropy for said word, wherein the respective normalized entropy is based on a total number of domains in which said word appears and how representative said word is for each of the plurality of domains; for each complete input phrase in the collection of complete input phrases, calculating a respective phrase indexing power across the plurality of domains based on an aggregation of the respective word indexing powers of all constituent words of said complete input phrase; obtaining respective domain-specific usage frequencies of the complete input phrases in the training corpus; and generating a cross-domain ranking of the collection of complete input phrases based at least on the respective phrase indexing powers of the complete input phrases and the respective domain-specific usage frequencies of the complete input phrases.

6. The method of claim 1 , further comprising: receiving the initial user input from a user; identifying, from the collection of complete input phrases, a subset of complete input phrases that each begins with the initial user input; ranking the subset of complete input phrases in accordance with the cross-domain ranking of the collection of complete input phrases; selecting a predetermined number of unique relevant domains based on respective domains associated with each of the subset of complete input phrases; and selecting at least one top-ranked input phrase from each of the unique relevant domains as one of the auto-completion candidates to be presented to the user.

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34. A method comprising: applying a full transformation file on a hierarchical data file containing a node, thereby producing a first rendering file; determining one or more elements of the rendering file that can change for possible changes of the node; changing the hierarchical data file by changing the node; creating a second rendering file by applying a full transformation file on the changed hierarchical data file; determining a difference between the first rendering file and the second rendering file; attempting to map the difference on the first rendering file; and producing a third rendering file, the third rendering file comprising a partial rendering file based on the difference if the map is successful and comprising a full rendering file if the map is not successful.

36. The method of claim 34 , wherein the first rendering file is written in XHTML and the hierarchical data file is written in XML.

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12. The system according to claim 7 , wherein the first DBMS has a first DBMS type and the second DBMS has a second DBMS type different than the first DBMS type.

7. A system for enabling collaborative development of a database application across multiple database management systems, the system comprising: at least one processing unit; memory operably associated with the at least one processing unit; and a database development collaboration tool (DDCT) storable in memory and executable by the at least one processing unit, the DDCT comprising: a development module configured to: receive a database, generated by a first user in a first database language, via a first database management system (DBMS); designate a set of tables from the database as a set of static data tables; commit the database and the set of static data tables to a repository; and deploy, from the repository, the database in a second DBMS; and a synchronization module configured to: receive a change to the database, by a second user in a second database language, via at least one of: the first DBMS, and the second DBMS, wherein the change is represented as metadata that is general to both the first DBMS and the second DBMS; and synchronize the change to the database within the repository based on the metadata.

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4. The method of claim 2 , wherein the step of determining the one or more first characters based on the recognition of the one or more second characters further comprises: if none of the codes is identified to be the one or more second inputted characters, the one or more second characters are recognized by the stroke recognition module as a new character input to be displayed by the result transmit module.

5. The method of claim 4 , further comprising substituting the default recognition result in the input window with the one of the recognition results upon determining the one of the recognition results is the one or more first characters.

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15. A system according to claim 11 , wherein the system uses a desktop-based ASR arrangement.

11. An automatic speech recognition system comprising: a cepstral mean normalization (CMN) module employing at least one hardware implemented computer processor for: i. storing a current CMN function in a computer memory as a previous CMN function, and ii. updating the current CMN function based on a current audio input to produce an updated CMN function; an audio pre-processor for normalizing the current audio input using the updated CMN function to produce a processed audio input; and a speech recognition engine employing at least one hardware implemented computer processor for attempting to perform automatic speech recognition of the processed audio input to determine representative text; wherein if the processed audio input is not recognized as representative text, the CMN module replaces the updated CMN function with the previous CMN function.

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19. The system of claim 18 , wherein the modified input information comprises the associated value substituted for the symbolic variable in the input information.

18. The system of claim 17 , wherein the input statement comprises the symbolic variable.

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7. The method of claim 1 , wherein at least one of the plurality of additional query terms includes a synonym.

1. A method for automatically providing a plurality of additional database query terms to a user, the method comprising: receiving a first query term from the user; receiving a plurality of characters from the user, wherein the plurality of characters is only a portion of a second query term; selecting a first set of records from a database based on the first query term, wherein the database comprises records, and wherein the records comprise text translated from audio data associated with a call, wherein each word in a record is associated with a corresponding confidence factor, the confidence factor representing an accuracy of translation of the word from audio to text, the records further comprising metadata that includes information about a party to the call, a time of the call and a date of the call; determining, in a first pass, a first plurality of additional query terms based on the plurality of characters, wherein the first plurality of additional query terms are in a semantic network; for each one of the first plurality of additional query terms, determining a relevance of the additional query term with respect to the first plurality of additional query terms by processing all records in the database, including the metadata, to select a second set of records from the database based on the additional query term and comparing the second set of records with the first set of records selected based on the first query term, wherein the relevance is also determined at least in part based on semantic information related to the records; recursively determining, in at least a subsequent pass to the first pass, a second plurality of additional query terms based on previously determined additional query terms and determining the relevance of the recursively determined second plurality of additional query terms, wherein the relevance is determined at least in part based on semantic information related to the records; displaying at least one additional query term selected from the first plurality of additional query terms and the second plurality of additional query terms to the user for selection, the display based on the relevance of each of the plurality of additional query terms and on the confidence factor of each additional query term.

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27. A non-transitory computer-readable medium including computer program instructions, which when executed by a computer, cause the computer to perform the method according to claim 1 .

39. The non-transitory computer readable medium of claim 27 , wherein each type of semantic class of the plurality of semantic classes is assigned a unique metric, the unique metric being utilized in the computation of one of the left contraction and a right contraction operations as a measure within one of the respective blades.

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1. A method for generating feature graphs employed for creation of a headnote in a legal document, the method comprising: identifying one or more predetermined features in a plurality of legal documents, wherein the one or more predetermined features are based on grammatical constituents of text in the legal document, the plurality of legal documents being manually identified as headnote and non headnote; obtaining data related to the availability of the one or more identified predetermined features in the sentences manually identified as headnote and non-headnote in the plurality of legal documents; computing likelihood of a sentence being a headnote based on the obtained data; generating feature graphs corresponding to each predetermined feature based on the computed likelihood and obtained data; and storing the generated feature graphs in a repository.

4. The method of claim 1 , wherein obtaining data related to the availability of the one or more identified predetermined features in the sentences manually identified as headnote and non headnote comprises: determining feature values for each of the identified predetermined features, wherein the feature values represent the number of occurrences of the identified predetermined features; obtaining number of headnote sentences for a specific feature value of each of the identified predetermined features; and obtaining number of non headnote sentences for the specific feature value of each of the identified predetermined features.

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8. The method of claim 7 , further comprising maintaining, by the virtual browser, the association between the dynamic subtree with the unique token identifier until termination of the connection between one of the plurality of servers and the virtual browser.

7. The method of claim 6 , further comprising constructing, by the virtual browser, a dynamic subtree representing non-matching dynamic content and associating the dynamic subtree with the unique token identifier.

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5. The invention in accordance with claim 4, wherein said N data section of said N-processor includes M command storage means for storing an M-level command produced thereby, and said P-processor includes N command storage means for storing an N-level command produced thereby.

4. The invention in accordance with claim 3, wherein said P-processor includes N instruction addressing means responsive to a fetched microinstruction for fetching a selected one or more N instructions from said N memory.

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2. The method as recited in claim 1 , wherein selecting includes tie-breaking between pages based on the navigation constraints to select a next qualified page from the set of all available and ready pages.

1. A method for web application navigation control, comprising: updating navigation data models used in navigation constraints with received data from an end-user or system, the data models being stored on a computer storage medium; without needing a centralized application-specific controller, automatically selecting from a collection of extensible navigation rules associated with each page of a plurality of pages the extensible navigation rules; evaluating the navigation constraints associated only with the pages potentially changing their ready state to execute from among the plurality of pages in an entire application to determine which pages are ready to run, wherein determining which pages are ready to run is based on updated data from the navigation data models; and selecting a preferred page to be actually navigated to next from among a set of all available and ready pages.

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3. The method of claim 2 , further comprising providing the suggested search query with search results for the subsequent search query.

2. The method of claim 1 , further comprising: receiving a subsequent search query after receiving the additional search query; associating the subsequent search query with the current search session to form an updated current search session; and identifying, from the similar subset of previous search sessions and as similar previous search sessions, one or more individual previous search sessions that are similar to the updated current search session, wherein each identified similar previous search session is identified as being similar to the updated current search session based on at least a subset of search queries of the updated current search session matching a subset of search queries of the identified similar previous search session.

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13. A machine learning system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a plurality of examples, separable by feature into at least two classes, for distribution to a plurality of workers in a mapreduce process, each worker only receiving examples associated with a first class or a second class, wherein the first class is a positive class and the second class is a negative class, and wherein a worker is selected from the group consisting of a mapper and a reducer; determining whether each example is either associated with the first class or associated with the second class; distributing an example associated with the first class to a first worker of the plurality of workers in the machine learning system, the first worker receiving only examples associated with the first class; and distributing an example associated with the second class to a second worker of the plurality of workers in the machine learning system, the second worker receiving only examples associated with the second class.

18. The system of claim 13 , the operations further comprise generating an updated weight based on an original weight and a weight function, wherein the weight function contains inputs selected from the group consisting of a statistic associated with the first class and a statistic associated with the second class.

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6. An apparatus for compressing visual descriptors from at least one image by exploiting redundancy of natural image descriptors, comprising: a receiver of visual descriptors extracted from at least one image, said visual descriptors describing key points in images; a processor, configured to determine model parameters of a generative probabilistic model from the extracted visual descriptors in a maximum likelihood sense; a quantizer of said model parameters; an encoder of said quantized model parameters; a quantizer of said extracted visual descriptors; and an encoder for encoding said quantized extracted visual descriptors using said model parameters by applying a model based arithmetic encoding to exploit redundancy of the visual descriptors within the at least one image for compression of the visual descriptors.

7. The apparatus of claim 6 , wherein at least one output of the model parameters and encoded visual descriptors encoders are stored.

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9. The user interface of claim 5 including selection means for selecting for viewing where a concept either contains the property declaration or the property constraint.

5. A computer program on a computer usable medium containing a search engine for a hierarchial database comprising: view computer code for providing computer screen displays of two search classes, one of the displays of a class covering concept terms and the other of the displays a class covering terms for properties attributable to one of more of the concepts of the hierarchy for the selection, by a user, of one of the classes; dictionary computer code for establishing a third computer screen display for displaying a dictionary of the terms in the hierarchy that fall within a selected one of the two classes and creating a visualization of terms of the selected class for the choosing of search terms from the dictionary; and further dictionary computer code for associating in the third display the terms of the selected class with terms from a nonselected class which terms are related to the search terms for selecting of one of the associated terms as a further search term by the user.

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17. The method of claim 16 , further comprising the steps of: obscuring at least some of the portions of the images of the physical scene that are automatically identified as depicting the physical objects of the predefined types.

18. The method of claim 17 , wherein the predefined types of the physical objects comprise automotive license plates.

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1. A system for providing television advertisements based on a telephone conversation between two or more persons comprising: a speech recognition system for a telephone service configured to monitor a telephone conversation between two or more persons and to recognize key words and phrases spoken by one or more of the persons during the conversation; a database having one or more advertisements indexed by words and phrases; a search engine for querying the database based on key words and phrases recognized during the conversation; a television broadcast for a television service configured to integrate at least one advertisement from the database into the video feed to the television of at least one of the persons based on key words and phrases recognized during the conversation, wherein the television broadcast including the at least one advertisement is received during the telephone conversation.

5. The system according to claim 1 , wherein the device used for receiving the television broadcast by at least one of the two or more persons is a television, monitor, display, or computer.

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18. The system of claim 13 , wherein: the data structure comprises a parse tree; and the one or more processors are operable to issue at least one of the one or more queries before addition of one or more nodes to the parse tree.

13. A system for modifying a file written in a formal language, the system comprising a computer system comprising one or more processors and one or more memories, the one or more processors programmed with instructions to: parse, based on code of a parser, an input file written in a formal language to generate by the parser a data structure of the input file, the parser implemented using a formal language specification for the formal language of the input file; issue, at an intermediate point in generation of the data structure of the input file by the parser and according to one or more query triggers in the code of the parser, one or more queries to a rule engine for evaluation of a first plurality of rules for modifying the input file, wherein the one or more queries include a subset of terminal symbols used to make up the data structure, wherein modifying the input file comprises altering the functionality of the input file by altering computer code of the input file according to the first plurality of rules; the first plurality of rules comprising at least one rule distinct from the formal language specification used to implement the parser, the rule engine configured to analyze the one or more queries, determine whether the one or more queries trigger any of the first plurality of rules for modifying the input file, and communicate a query result to the parser, the query result instructing the parser to take an action in accordance with any of the triggered first plurality of rules as determined by the rule engine; generate, at the intermediate point, the data structure by executing the action indicated by the query result; and wherein the one or more processors are programmed with instructions to reuse the parser with a second plurality of rules distinct from the first plurality of rules.

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19. A method for managing versioned content files, comprising: receiving a request for learning content from a user, the learning content associated with a plurality of learning objects, each learning object comprising at least one content file and at least a subset of the learning object files being reusable for other learning content; identifying a versioning object from a content repository based, at least in part, on a first learning object in the requested request, wherein the version object identifies updated content files for the first learning object and a relative path to content files substantially matching content files of a prior version of the first learning object; generating a mapping table from the versioning object, the table comprising a plurality of mapping entries, each entry indicating a relative path for one of the plurality of content files; comparing a first content file in the first learning object to the mapping table; if a mapping entry is found for a particular requested content file, collecting the referenced file using the relative path; and if no mapping is found for the particular requested content file, collecting the referenced file from the versioning object.

20. The method of claim 19 , wherein the loading, generating, comparing, and collecting steps are performed at an API and the method further comprises communicating the one or more collected content files from the API to a network-based application for presentation to the user.

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11. A system comprising: a memory to store instructions; and a processor to execute the instructions to: receive a first document that includes a plurality of advertisements; identify one or more advertisements, of the plurality of advertisements, that have been selected more than any other advertisements of the plurality of advertisements; retrieve particular documents associated with the one or more advertisements; extract concepts from the retrieved particular documents, at least one extracted concept of the extracted concepts being associated with anchor text associated with a link in one of the retrieved particular documents; and associate the extracted concepts with the first document.

14. The system of claim 11 , where the processor is further to: label the extracted concepts as relevant to the first document.

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1. A method comprising, by one or more computing devices: selecting, by one or more of the computing devices, a first text string from a set of text strings to be translated, wherein each text string of the set of text strings is associated with a priority value, and wherein the first text string is selected based on its priority value, wherein the priority value of the first text string is determined based on one or more previously calculated reliability-values of one or more translations for the first text string; sending, to a client system of a first user, instructions configured to present a translation prompt comprising the first text string and a translation-input field, wherein the first user is associated with a credibility-score based on prior translation activity of the first user; receiving, from the client system, an input by the first user at the translation-input field, wherein the input corresponds to a first translation for the first text string; and calculating, by one or more of the computing devices, a reliability-value for the first translation based on the input and the credibility-score of the first user.

8. The method of claim 1 , wherein the credibility-score of the first user is based on a language proficiency of the first user, the language proficiency of the first user being determined based on a history of language usage by the first user in communications authored by the first user.

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5. The knowledge base system according to claim 1 , wherein said operation unit is configured to, when one entity is designated as an operation target, perform the logic operation on an attribute of the designated entity.

11. The knowledge base system according to claim 5 , wherein said operation unit is further configured to, when two attribute sets each of which includes one or more attributes are designated: count, in a case where each attribute is associated with a true-false value indicating whether the attribute is true or false, a number of attributes that are included in both of the two attribute sets and associated with a same true-false value between the two attribute sets, as a degree of commonality; and count, in a case where each attribute is not associated with the true-false value, a number of attributes that are included in both of the two attribute sets, as the degree of commonality.