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1. A computer-based design framework for collaborative design of a product comprising: a virtual database management system, which includes a processor and which receives data from a plurality of sources and creates a single database interface to said sources, wherein each of said plurality of sources represents a design team with one or more design team members provided access to said virtual database management system via a network, wherein the framework enables completion of multiple design tasks across architectural, functional and performance hierarchies of a complex design; program code associated with said virtual database management system for mapping various informational structures utilized by said sources to a common syntax, wherein the common syntax is an eXtensible Markup Language (XML); program code for providing platform-independent application and services exchange utilizing XML wrapped data, service, and application that is delivered to a client; additional logic associated with said virtual database management system that provides a set of publishing rules for extracting information on demand and publishing said extracted information in a format recognized by a requestor of said information; an Access Privilege Manager implemented with program code that: (a) monitors and controls access to said design framework by design teams, design team members, and other selected personnel, groups, and design automation tools; (b) maintains a control list of one or more authorization parameters from among users, user identification and passwords, a level of authorization for each user and group, a group to which each user belongs, specific group authority for access, and access authorization for one or more project administrators, wherein access to processes and designs within said framework is only granted to a user whose authorization and registered role supports said access; and (c) supports biometric security features for user-access to said framework; and a customer help at terminal (CHATSOC) function that provides an online collaboration and conferencing between design teams, design team members, and other personnel, wherein CHATSOC further provides outside assistance to a design team and design team member, wherein said outside assistance is selected from a compiled database of outside assistance personnel in response to a request for assistance by said design team or design team member, wherein a peer-to-peer connection is dynamically established when an outside assistance personnel accepts and acknowledges the request.

2. The computer-based design framework of claim 1 , wherein said program code for providing platform independent application and services exchange includes a universal description discovery and integration (UDDI) director for locating services and exchange data and service according to simple object access protocol (SOAP).

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17. The computer-readable storage medium of claim 16 , wherein the document score is generated based on the identified document's ordinal position in the results set in which the identified document is found, and the total number of documents contained in the results set in which the identified document is found.

18. The computer-readable storage medium of claim 17 , wherein the document score is generated according to the formula score=rank·log(count), where rank corresponds to the identified document's ordinal position in the results set in which the identified document is found, and count corresponds to the total number of documents contained in the results set in which the identified document is found.

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11. A computer system comprising: a processor; and memory coupled to the processor and having stored therein instructions that, if executed by the computer system, cause the computer system to perform operations comprising: providing, in a database, a plurality of entity table types relevant to a domain type, wherein each entity table type includes a respective entity table name field and at least one respective data item field; populating the respective entity table name fields and the respective data item fields by automatically: extracting a plurality of data items from a plurality of data sources; determining respective confidence values for the extracted data items based on a plurality of pre-determined confidence values, wherein a respective predetermined confidence value is provided for each respective entity table name and each respective data item according to which data source of the plurality of data sources provided the respective entity table name and the respective data item; integrating the extracted data items into respective entity table name fields and data item fields based on the respective confidence values for the extracted data items; storing a first data item extracted from a first data source in a first data item field and storing a second data item extracted from the first data source in a second data item field; populating a first row of a direct relationship table having a plurality of rows with a first direct relationship definition indicating that the first data item field and the second data item field store respective data items that have been extracted from the first data source; searching the direct relationship table for a second row having a second direct relationship definition indicating that a third data item field stores a third data item that has been extracted from a second data source from which the first data item has also been extracted, wherein the second data source is different than the first data source; determining a transitive relationship definition, based on the first direct and second direct relationship definitions from the direct relationship table, indicating that the second data item field is related to the third data item field, wherein the transitive relationship definition is based on at least two separate relationships between data item fields; and storing the third relationship definition in a transitive relationship table.

13. The computer system of claim 11 wherein the operations further comprise automatically establishing a field-to-field link in the database, wherein the field-to-field link is selected from the group consisting of: a field-to-filed link between two respective data items if both respective data items were integrated from a single structured data source; a field-to-field link between a first entity table name field and a second entity table name field if both the first and second entity table name fields were integrated with data items from a single structured data source; and a field-to-field link between a first entity table name field of a first entity table and a data item field of a second entity table if both the first entity table name field and the data item field of the second entity table were integrated with data items from a single structured data source.

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11. A system for obtaining individual profile information from individuals, comprising: an individual profile database storing profile information for an individual; a network-based application linked to the individual by a network, wherein the network-based application is configured to perform, during an automated session with the individual, steps comprising: provide a first system utterance to the individual over the network associated with a line of questioning for obtaining the individual profile information; receive a first user utterance from the individual over the network; analyze characteristics of the first user utterance to yield an analysis based on a temperament, a timing, and a content of the first user utterance; detect a mood of the individual from a characteristic of the first user utterance to the first system utterance based on the analysis and determine whether the mood meets a termination criteria; when the mood meets the termination criteria, terminate the line of questioning, continue the session with the individual and defer the obtaining of the individual profile information to a subsequent automated session; and when the mood does not meet the termination criteria, performing steps comprising: providing a second system utterance to the individual based on the analysis of the temperament, the content, and the timing for the first user utterance, the second system utterance selected from a hierarchy of question options organized by question content, temperament criteria, and timing criteria; receiving a second user utterance in response to the second system utterance; determining whether the first user utterance addresses a first category of information in the individual profile database to yield a first determination; determining, in response to the first determination, a first set of profile information from the first user utterance; when the first user utterance is adequate and direct, storing the first set of profile information in the individual profile database, and determining if the second user utterance addresses a second category of information in the individual profile database to yield a second determination; determining, in response to the second determination, a second set of profile information from the second user utterance; and storing the second set of profile information in the individual profile database.

20. The system of claim 11 , wherein the network-based application provides the second system utterance by selecting a time within which to present the second system utterance.

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29. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: receiving a first corpus of phrases, each of the phrases comprising at least one word; determining, for each phrase of the first corpus of phrases: (i) a commonality of the phrase; (ii) a commonality of each word of the phrase; (iii) a readability of the phrase; (iv) a number of words in the phrase, or (v) a source of the phrase; scoring each phrase of the first corpus of phrases based on the commonality of the phrase, the commonality of each word of the phrase, the readability of the phrase, the number of words in the phrase, or the source of the phrase; and based at least in part on the scoring of the phrases, filtering out at least a portion of the first corpus of phrases to define a second corpus of phrases; outputting phrases of the second corpus of phrases to a user; and responsive to receiving a selection of a phrase by the user, associating the selected phrase with at least one of a shipping address, a device or location data in a server that is associated with the user.

31. One or more computer-readable as recited in claim 29 , wherein the source of the phrase comprises a manner in which the phrase was generated.

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13. The computer readable medium of claim 12 , wherein the procedural language code is ABAP language code and the operational system is an SAP R/3 system.

14. The computer readable medium of claim 13 including executable instructions to: optimize the declarative specification prior to generating the ABAP program code.

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3. The method of claim 1 , further comprising: determining, using the processor, that an influencing condition exists based upon an analysis of the plurality of social media posts, wherein each of the plurality of social media posts relates to the topic and comprises a negative sentiment relating to the topic; and in response to determining that the influencing condition exists, posting, using the processor, social media to the social media website, wherein the social media is directed to the topic and is responsive to the plurality of social media posts.

1. A method comprising: collecting, using a computing device comprising a processor that executes a sentiment analysis module, a social media post that relates to a topic, the topic comprising a brand and a product type, wherein the social media post is created by a user and collected from a social media website; analyzing, using the processor, a sentiment expressed in the social media post, the sentiment comprising an opinion of the user, the opinion relating to the topic; determining, using the processor, a demographic category of the user, the demographic category comprising a user location of the user, an income level of the user, and an age of the user; archiving, using the processor, the social media post to a database stored on a storage device; indexing, using the processor, the social media post, wherein the indexing is based upon the sentiment, the topic, and the demographic category; generating, using the processor, a user interface that comprises a first interface, a second interface, and a third interface, wherein the first interface displays a real-time stream of a plurality of social media posts that relate to the topic, the plurality of social media posts comprising the social media post, the second interface displays most common phrases extracted from the topic during a time period, and the third interface displays a graphical representation of a count, for the time period, of the plurality of social media posts that relate to the topic in the real-time stream as updated in real-time; and providing, using the processor, the user interface to a social media analysis consumer.

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7. The system of claim 1 , wherein the operations further comprise updating the component reputation score before updating the user reputation score.

1. A system comprising: at least one processor and executable instructions accessible on a computer-readable medium that, when executed, cause the at least one processor to perform operations comprising: receiving, over a network at a social shopping platform, a request from a user in a first community of users, the social shopping platform including a plurality of network-based marketplaces respectively associated with a plurality of communities, the plurality of communities including the first community of users that is associated with a first network-based marketplace; identifying the first network-based marketplace from the plurality of network-based marketplaces based on the request, the request including an activity associated with the first network-based marketplace, the first network-based marketplace being used by the first community of users for transacting items of a single domain, the activity identifying a first logical row of component information in a component table based on the request, the component table being a logical table comprised of a plurality of logical rows, the first logical row of component information describing at least one user interface element for personalizing at least one user interface including a first user interface, the logical table further comprised of a plurality of logical columns intersecting the plurality of logical rows to define a plurality of logical cells, the plurality of logical columns describing information received from at least one user in the first community of users and component reputation scoring that is generated based on the information received from at least one user in the first community of users; communicating the first user interface, over the network, for display on a client machine, the first user interface being personalized with the at least one user interface element; updating a component reputation score based on the activity associated with the first network-based marketplace and; updating a user reputation score based on the component reputation score.

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1. A method of responding to a request, comprising: receiving the request; determining automatically a type associated with the request; and providing a portion of the request to a human assistant in an interface selected based on the type and providing information of a query in an order based on a ranking of the query.

3. The method of claim 1 , comprising: providing the portion of the request to the human assistant when an automation confidence function of the request is above a predetermined value.

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9. The computer readable-media as recited in claim 8 , wherein the filtering process comprises comparing a first and a last consonant in the misspelled entry with a first and a last consonant in a selected term.

12. The computer readable-media as recited in claim 9 , wherein the filtering process considers one or more consonants that are omittable from a start or end of the misspelled entry.

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15. The system of claim 13 , the operations further including receiving additional environmental data that includes video data or image data.

13. 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 data including (i) audio data that encodes a spoken natural language query, and (ii) environmental audio data; obtaining a transcription of the spoken natural language query; determining a particular content type associated with one or more keywords in the transcription; providing at least a portion of the environmental audio data to a content recognition engine; and identifying a content item that (i) has been output by the content recognition engine, and (ii) matches the particular content type associated with the one or more keywords in the transcription.

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7. The method of claim 1 , further comprising transmitting the data request to the online service in view of the client-side data scraping operation.

1. A method comprising: providing, by a hardware processor, an overlay client on a first computing device, the overlay client to provide an interface between a service application on the first computing device and an online service; identifying a set of content sources associated with a first user comprising a local storage device of the first computing device; obtaining, via the overlay client, content from the set of content sources; receiving, by the overlay client, a poll request associated with the content from a message server, wherein the poll request comprises an instruction to perform a client-side data scraping operation; originating, by the hardware processor, a data request in response to the client-side data scraping operation; causing, by the overlay client, the service application to submit the data request to the online service in view of the poll request; and receiving a message associated with a second user from the online service in view of the data request, wherein the message corresponds to an activity of the online service, wherein the first user has previously engaged with the online service, and wherein the activity is of interest to the first user.

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5. A computer program product comprising a non-transitory computer usable storage medium storing computer usable program code for finding items that are related to a user selected item in a knowledge base comprising: computer usable program code for generating a first list of knowledge base items with a defined relationship to a user selected item in a knowledge base, a second list of knowledge base items that belong to the same category as a category of the user selected item, and a third list of knowledge base items having one or more tags identical to one or more tags of the user selected item; computer usable program code for selecting by the processor a first set of knowledge base items that are present in all three lists and further selecting by the processor a second set of knowledge base items that are present in only two of the three lists, and yet further selecting by the processor a third set of knowledge base items that are present in only one of the three lists; and computer usable program code for displaying the first set of knowledge base items as most relevant to the user selected item and displaying in the computer display the second set of knowledge base items as secondarily relevant compared to the knowledge base items present in all three lists and displaying in the computer display the third set of knowledge base items as least relevant compared to the knowledge base items present in all three lists and the knowledge base items present in only two of the three lists.

8. The computer program product of claim 5 , wherein the computer usable program code for displaying further comprises: computer usable program code for displaying in a user interface a set of information associated the first set of knowledge base items, wherein the first set is displayed as most relevant.

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7. The apparatus of claim 6 , wherein the parameter storage further comprises: an attack parameter storage; and a release parameter storage.

6. The apparatus of claim 1 , wherein the environment adaptation module includes parameter storage for each of the plurality of possible sources, the parameter storage comprising: a plurality of subband gain parameter storages.

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19. A search system for searching for electronic documents, and providing a search result in response to a search query, comprising: a processor; a database, wherein terms in the database are grouped in a cluster based on the terms belonging to a same word sense; a user interface module adapted to receive a search query from a user, said search query having at least one search query term; a query processing module that automatically determines a single assumed domain category for the at least one search query term selected form a group of retrieved domain categories, and wherein said user interface module is adapted to display alternative domain categories in which said search query term is used that are different from and exclusive of the single assumed domain category, and to allow the user to select at least one of the alternative domain categories, and wherein the query processing module identifies a plurality of any available alternative terms from a cluster based on the domain category selected by the user, and wherein the plurality of any available alternative terms include any available synonyms within the domain category selected by the user; a search engine that electronically searches for electronic documents that satisfy said at least one search query term and said plurality of available alternative terms; and wherein said user interface module is further adapted to display search results received from the search engine.

20. The search system of claim 19 , wherein said search engine executes a search based on said search query term and said plurality of available alternative terms simultaneously.

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1. A computer-implemented method for facilitating full-text search, the method comprising: receiving a plurality of search terms; organizing the plurality of search terms into a lexicographically-ordered set of search terms, the lexicographically-ordered set of search terms including at least a first search term and a second search term; wherein the first search term is a first character string and the second search term is a second character string; generating an interwoven search token from the first search term and the second search term by interweaving characters of the first character string with characters of the second character string such that the interwoven character string contains alternating characters of the first character string and the second character string; querying a full text search index using the interwoven search token; and receiving, based on the querying, a result set that is associated with the plurality of search terms.

7. The method of claim 1 , wherein the plurality of search terms are related to a destination search.

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5. The method of claim 1 further comprising identifying elements associated with the macroinstructions that are pointed to but not conspicuously named in the macroinstructions.

1. A method comprising: extracting, with a preprocessor in a computer system, macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define a proper CLI syntax for CLI commands input to a CLI prompt and include parse nodes used by the CLI parser to analyze whether one or more CLI commands input to the CLI prompt have proper CLI syntax, and wherein the macroinstructions are written according to a first computer system language; converting, with the preprocessor, the macroinstructions into at least one parse graph having an Extensible Markup Language (XML) format, wherein the converting includes encapsulating the parse nodes of the macroinstructions with XML tags and stitching together the encapsulated parse nodes of the macroinstructions to generate the parse graph, and wherein the first computer system language is different than an Extensible Markup Language (XML) language associated with the parse graph; and generating, with the preprocessor, an exportable representation of the at least one parse graph and outputting the exportable representation of the at least one parse graph from the computer system.

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1. A computer-implemented method for maintaining a hierarchical tree representation of an extensible markup language (XML) data string, comprising using at least one processor coupled to a memory to perform the following operations: detecting a modification to an XML data string; determining a location of the modification in the XML data string; correlating the location of the modification to at least one node in a hierarchical tree formed as a tokenized representation of the XML data string; deleting a portion of the hierarchical tree based at least in part on the modification corresponding to deleting a portion of the XML data string; determining a last node in the deleted portion of the hierarchical tree, and populating at least one sub-tree with nodes associated with the last node in the deleted portion of the hierarchical tree; and inserting the at least one sub-tree into the hierarchical tree following the deleting the portion of the hierarchical tree.

3. The computer-implemented method of claim 1 , further comprising incrementally reparsing a portion of the hierarchical tree based at least in part on the modification to the XML data string.

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3. The method of claim 1 , wherein the statistical information for a node is displayed adjacent the node within a display of the application flow.

4. The method of claim 3 , wherein the statistical information is displayed as a color-coded meter.

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1. A computer-implemented method for identifying popular topics for a group of online articles, the method comprising: analyzing text of each online article from the group of online articles to identify a plurality of topics relevant to the group of online articles and to generate a relevance score for each topic and each online article; computing an article topic score for each topic and each online article, the article topic score for a first topic and a first online article being computed as a function of the relevance score for the first topic and the first online article and visitor metrics for the first online article; generating an aggregated topic score for each of at least a portion of the topics, the aggregated topic score for the first topic being generated by summing the article topic scores for the first topic; and providing an indication of the popular topics for the group of online articles for presentation to a user, the indication of the popular topics being provided by: ranking at least the portion of the topics based on the aggregated topic score for each of at least the portion of the topics, generating a user interface providing information regarding ranking of at least the portion of the topics, and providing the user interface for presentation to the user.

2. The method of claim 1 , wherein the visitor metrics correspond to a particular visitor segment.

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1. A computer-implemented method comprising: maintaining in a data store information associated with a plurality of users of a system, a plurality of actions performed by the users, and a plurality of objects associated with one or more of the actions; receiving, from a device associated with a viewing user, a request identifying two or more users of the system for a page comprising objects associated with each identified user; and responsive to receiving the request for the page: identifying one or more objects associated with each of the identified users; determining relevancy scores for each image in a set of images, from the one or more objects associated with each of the identified users, based on a relevancy of each image to all of the identified users, wherein the relevancy of an image decreases when the image is associated with additional users other than the identified users; ranking the set of images according to the relevancy scores; selecting, from the set of ranked images, an image with a highest relevancy score; generating the requested page, the generated page including the selected image and the identified objects; and sending the generated page to the device associated with the viewing user for display.

8. The computer-implemented method of claim 1 , wherein an identified object comprises a video in which each of the identified users is tagged.

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19. For use with an electronic book, a computer-based method for performing live symbolic mathematical operations and for editing and processing mathematical expressions, the method comprising the steps of: displaying the electronic book on an output device of a computer, the electronic book including a table of contents with hyperlinks to sections of the electronic book; providing a symbolic evaluation operator signifying that a mathematical expression is to be evaluated symbolically; displaying mathematical expressions in standard mathematical form in the electronic book, a subset of the mathematical expressions comprising the symbolic evaluation operator; maintaining a dependency graph so that the dependency graph continuously represents mathematical dependencies between the mathematical expressions in the electronic book; symbolically evaluating each mathematical expression in the electronic book that includes the symbolic evaluation operator; displaying in the electronic book results of the symbolic evaluation of each mathematical expression evaluated at the previous step; editing one or more mathematical expressions in the electronic book; and automatically updating the electronic book whenever a mathematical expression is edited, said automatically updating step including the substeps of: automatically updating the dependency graph to include the edited one or more mathematical expressions, automatically ascertaining a subset of mathematical expressions that include the symbolic evaluation operator that need to be updated, and automatically symbolically evaluating each mathematical expression in the subset of mathematical expressions ascertained at the previous substep.

22. The method of claim 19 wherein the substep of automatically ascertaining a subset of mathematical expressions that need to be updated further comprises the step of utilizing the dependency graph to ascertain the subset of mathematical expressions that need to be updated.

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5. The method of claim 1 , further comprising: using the server device to perform the action associated with the identified word, phrase or symbol, wherein performing the action associated with the identified word, phrase or symbol comprises the server device translating the identified word, phrase or symbol from a first spoken language to a second spoken language.

1. A method comprising: receiving, at a server device, a sequence of characters optically or acoustically captured from a rendered document by a capture device remote from the server device; identifying, using the server device, a document that includes a sequence of characters that matches the captured sequence of characters; identifying, using the server device, a position, within the identified document, of the sequence of characters that matches the captured sequence of characters; and identifying, using the server device, a word, phrase or symbol that is within the sequence of characters at the identified position within the identified document and that is associated with an action.

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1. A method for accessing data in a computer system including a set of diverse data sources comprising data, the method comprising: defining an ontology for application to said set of diverse data sources comprising data; defining data access rights with respect to the ontology; collecting information in an ongoing manner regarding characteristics of the data sources; storing said information in a storage device on said computer system; employing at least one of wrappers and agents to automatically discover new or altered data sources associated with versions of said ontology; automatically generating new ontology mappings of said data sources and said data access rights to said versions of said ontology in order to accommodate said new or altered data sources, without disrupting responses to queries on the basis of earlier versions of said ontology; automatically generating new versions of said wrappers and agents to correspond with new versions of said ontology; and automatically generating new versions of query plans to correspond with new versions of said ontology, said automatically generating new ontology mappings, said automatically generating new versions of said wrappers and agents and said automatically generating new versions of query plans taking place without disruption of query response functionality of said computer system.

5. The method according to claim 1 , and comprising: associating with the ontology one or more logical rules applicable to semantics of the data in the data sources; receiving a query from a user regarding the data; determining a query plan for responding to the query by selecting one or more of the data sources responsively to the ontology and by identifying an operation to be applied to the data responsively to the applicable logical rules; and generating a response to the query in accordance with the query plan.

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3. The method as claimed in claim 2 , wherein the step of recommending research information further comprises the steps of: calculating how often said at least one new recent research keyword appears in each of said plurality of new recent research documents to obtain a respective appearing frequency or score of each of said plurality new recent research documents, and recommending at least one of said new recent research documents based on said respective appearing frequency or score of each of said plurality of new recent research documents.

4. The method as claimed in claim 3 , wherein said judging timing is set by a year range n and a condition of 0<n<4 such that said at least one new recent research keyword is defined as a prospective research keyword, and the step of recommending research information further comprises the steps of: calculating how often said prospective research keyword appears in each of said plurality of new recent research documents to obtain a respective prospective index of each of said plurality of new recent research documents, and selecting at least one of said new recent research documents to be set as a prospective research document based on said respective prospective index of each of said new recent research documents.

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21. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a spoken communication from a first user, the spoken communication comprising an address; extracting, via a processor, the address automatically from the spoken communication, to yield an extracted address; displaying to a second user a selection of addresses, the selection of addresses comprising the extracted address and an alternate address for the first user, the alternate address being stored in a contacts list, the selection of addresses displayed in an order prioritizing a preferred address of the extracted address and the alternate address, where the preferred address is determined based on a user history of the first user by the computing device; and receiving from the second user a selection of a selected address from the selection of addresses to initiate communication with the first user.

24. The computer-readable storage device of claim 21 , wherein the address comprises one of a phone number, an email address, a website, an internet protocol address, a file transfer protocol server, an instant messaging address, global positioning system coordinates, and a physical address.

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10. A non-transitory computer program product, encoded on a tangible program carrier, operable to cause a data processing apparatus to perform operations comprising: determining a plurality of error surfaces corresponding to a plurality of feature functions in a translation hypergraph, for each of one or more candidate translations represented in the translation hypergraph, including: generating a factor graph from the translation hypergraph, wherein the factor graph is an isomorphic transformation of the translation hypergraph, and generating the plurality of error surfaces from the factor graph; combining the plurality of error surfaces to produce a combined error surface; traversing the combined error surface to select weights for the feature functions that minimize error counts for traversing the combined error surface; and applying the selected weights to reduce an error count in a decoder that converts a sample of text from a first language to a second language.

11. The computer program product of claim 10 , wherein the operations further include generating the translation hypergraph using Synchronous Context Free Grammars (SCFG).

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18. A search system for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the search system comprising: a result pipeline extending through the search system; a deterministic finite automaton (DFA) engine to store first sub-expressions that comprise strings, the DFA engine having an input to receive the input string of characters from a data pipeline, and having an output to provide a first token onto the result pipeline in response to a match with one of the first sub-expressions; a non-deterministic finite automaton (NFA) engine to store second sub-expressions having selected quantified character classes, the NFA engine having an input to selectively receive the input string of characters from the data pipeline, and having an output to provide a second token onto the result pipeline in response to a match with one of the second sub-expressions; and a token stitcher, having an input to receive the tokens from the result pipeline, to combine the tokens to generate a latch signal indicating whether the input string of characters matches the regular expression, wherein the regular expression comprises an unbounded sub-expression, and the unbounded sub-expression is delegated to the token stitcher for processing without utilizing resources of the DFA or NFA engine and wherein the DFA and NFA engines and the token stitcher are implemented by at least one processor-based computing device.

20. The search system of claim 18 , wherein the NFA engine does not process tokens generated by the DFA engine.

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7. The system of claim 1 wherein the system is maintained in a mobile device.

1. A system that enables the recording of user-viewable visual stimuli comprising: a control application configured to, using a processor device, execute code that causes recording of a user-viewable stimulus at a first time, wherein the recording of a user-viewable stimulus at the first time is performed by: detecting a visual event; observing visual characteristics of the visual event; verifying that the visual event involves one or more parameters that change a viewable stimulus; and recording at least one of the parameters; and a storage platform, coupled to the processor device, configured to store data from the user-viewable stimulus wherein the stored data is configured to be used to recreate, at a second time different from the first time, at least a portion of the user-viewable stimulus.

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28. A user-interface method of selecting and presenting to a first user a collection of content items of a first content system in which the presentation is ordered at least in part based on content preferences of a second user learned from the second user selecting content of a second content system, the method comprising: receiving incremental input entered by the second user for incrementally identifying desired content items of the second content system, each content item having at least one associated descriptive term to describe the content item; in response to the incremental input entered by the second user, presenting a subset of content items of the second content system; receiving selection actions of content items of the subset from the second user; determining a user preference signature by analyzing the descriptive terms of the selected content items to learn the content preferences of the second user for the content of the second content system; determining a relationship between the content items of the first content system and the content items of the second content system, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first content system; and in response to receiving subsequent incremental input entered by the first user for incrementally identifying desired content items of the first content system, selecting and ordering a collection of content items of the first content system based on the learned content preferences of the second user determined to be relevant to the content items of the first content system.

33. The method of claim 28 , wherein the content items of at least one of the first and second content systems includes at least one of television program items, movie items, audio/video media items, music items, contact information items, personal schedule items, web content items, and purchasable product items.

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1. A method for facilitating text entry for an electronic device, the method comprising: activating a field for text entry on a display of the electronic device; displaying a current frame on the display associated with a viewfinder of the electronic device concurrently while also displaying the activated field for text entry; determining an area of interest in the current frame; recognizing text in the area of interest associated with the current frame, wherein recognizing text in the area of interest is performed without capturing the current frame in the viewfinder and without persisting in storage the current frame; and displaying text corresponding to the recognized text in the activated field.

13. The method of claim 1 , wherein a virtual keyboard is activated and displayed in response to activating the field for text entry, and wherein the viewfinder is displayed in response to detecting a selection to display the viewfinder.

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13. A computer program product, the computer program product tangibly embodied on a non-transitory computer-readable storage medium and including instructions that, when executed by at least one processor, are configured to: generate a new operator to add to a structured query language (SQL) query optimization process of a query by a query optimizer under a generic operator framework, wherein, under the generic operator framework, the new operator has a generic operator data structure that includes specifications for input attributes, output attributes and bypass attributes of the new operator; hold the generic operator data structure of the new operator in a knowledge base container; build, on query compile, the generic operator data structure of the new operator with reference only to the specifications for input attributes, output attributes and bypass attributes of the new operator; and apply optimization rules based on the generic operator data structure of the new operator during the structured query language (SQL) query optimization process of the query by the query optimizer.

19. The computer program product of claim 13 , the instructions further configured to: generate at least one query execution plan to access data from a database using the knowledge based container and define one or more execution paths for accessing data from the database; extend the query optimizer based on the at least one query execution plan and evaluate the at least one query execution plan by simulating one or more physical operations associated with the new operator; and execute the at least one query execution plan by performing physical operations associated with the new operator.

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13. The media of claim 8 , the logic further operable when executed to: determine, from the social graph, an additional device of the user; and determine, by analyzing interactions of the user with the social-networking system, which device the user is currently using.

8. One or more computer-readable non-transitory storage media in one or more computing systems, the media embodying logic that is operable when executed to: access a social graph of a social-networking system, the social graph comprising: user nodes that are each associated with a respective user of the social-networking system; concept nodes that each correspond to a respective device; and a plurality of ownership edges connecting the user nodes and the concept nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular concept node; determine from the social graph a device of a user of the social-networking system; determine, from the social graph, media content that a friend or a connection of the user in the social graph is currently viewing; and provide the media content that the friend or the connection of the user is currently viewing for display on the device of the user.

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1. A method for use of a medical ontology for computer assisted clinical decision support, the method comprising: providing a medical ontology indicating one or more semantic groupings of features; learning, by a processor, to identify at least one similar patient record from a set of patient records, the learning being a function of the one or more semantic groupings of features of the medical ontology; and outputting information derived from the learning.

13. The method of claim 1 wherein outputting comprises outputting validation results.

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24. A management system as recited in claim 23 , wherein the action includes a debug data acquisition.

23. A management system as recited in claim 22 , wherein the different products send resource information to the interference engine to process rules that depend on at least one fact representing the resource information.

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1. A system for proactively preventing a user from utilizing a restricted feature of a software application and for detecting and cleansing undesirable information from an electronic document, comprising: a software application operable by a user on one or more computing devices, to edit an electronic document by selecting and using features of the software application to enter and edit text in the electronic document; and a software module comprising an action listener, on one or more computing devices, wherein the action listener is configured to: access a plurality of policies defining protections to apply to the electronic document; disable a first manner of editing in the electronic document in response to opening the document and in response to a first policy; scan contents of the electronic document; determine that document content corresponding to the disabled first manner of editing the document is present in the document in response to the first policy; determine a level of protection to apply to the disabled first manner of editing the document; display a warning message in response to the determining the level of protection, wherein if the disabled first manner of editing is prohibited, the action listener directs the software module to remove content of the disabled manner of editing the document; permit the user to edit the electronic document according to a second manner of editing the document; determine that the second manner of editing is non-allowed based on content of the second manner of editing and in response to a second policy; display a warning message to the user in response to the second policy; permit the user to edit the electronic document according to a third manner of editing the document; determine the third manner of editing corresponds to one of a plurality of restricted entry of text and/or editing methods in response to a third policy; and scan the electronic document to determine if undesirable information in content of the third manner of editing is present in the electronic document, wherein if undesirable information is determined to be present based on the content of the third editing, the action listener determines whether the undesirable information is allowed or prohibited, and if the undesirable information is allowed, the action listener displays a warning message to the user prior to permitting the user to save, print, or transmit the electronic document, and if the undesirable information is prohibited, the action listener directs the software module to remove the undesirable information from the electronic document prior to permitting the user to save, print, or transmit the electronic document.

9. The system of claim 1 , wherein the disabled manner of editing the document comprises entering hidden data.

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3. The method of claim 1 , wherein said storing the preferred voice qualities comprises storing voice qualities comprising pacing of speech expressed as a time rate of speech text, volume of speech expressed as speech loudness, and gender of speech expressed as male or female, and wherein the method comprises determining the gender of speech from a range of sound wave frequency of the responses received from the user to said querying.

1. A method for enhancing user satisfaction with a telephonic response system comprising a computer, said method comprising: said computer querying a user at a telephone to determine preferred voice qualities while the computer is engaged in telephone communication with the user via the telephone; said computer receiving, from the user at the telephone, responses to said querying; said computer determining from the responses received from the user, using voice recognition functions of the telephonic response system, the preferred voice qualities; and said computer storing, in a user profile of the user located in a database accessible to the computer, the preferred voice qualities determined from the responses received from the user.

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2. The search system of claim 1 including a semantic dictionary builder which systematically examines the system log off line for new keyword queries to increase the keyword terms in the hierarchical structure and associate them with one or more semantic node terms used to identify the nodes of that structure.

3. The search system of claim 2 including ranking the results of searches using the enhanced queries to place terms in the semantic dictionary in order of most often used keyword query terms to reduce table lookup time.

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11. The method of claim 9 , wherein converting the identified range of the document into the new format further comprises: receiving an object node that references a range within the identified range: outputting an initial output associated with the object node; when the object node is a parent of at least one object node, recursively traversing any child object nodes of the received object node; when the object node is not a parent of any object nodes, outputting content from the content stream at the range referenced by the object node; and upon returning from any recursive traversal of child nodes, outputting a final output associated with the object node.

12. The method of claim 11 , wherein the new format is an HyperText Markup Language (HTML) format, and the initial and final outputs comprise HTML tags.

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1. A method for querying a database comprising: identifying an interface to the database for receiving a query including path expressions by a database management apparatus; receiving input defining a compliance rule, the input including: i) input identifying a configuration-item type, the identified configuration-item type determining a type of configuration item in an IT infrastructure of different types of configuration items; ii) input defining a rule scope, the rule scope determining which configuration items of the identified type are to be checked by the compliance rule; and iii) input defining a desired state for each of the configuration items to be checked by the rule, the desired state including at least one compliance condition that must be satisfied for a checked configuration item to be in compliance; receiving input identifying at least one path, each path being from an object in an object model to a related object in the object model or to an attribute of a related object in the object model; creating a path expression for each identified path, each path expression being composed from tokens selected from the group consisting of object identifiers, attribute identifiers, a relationship operator, and path qualifiers, the tokens sequentially added together to create the path expression; displaying at least one list of selectable items, each item associated with a token; receiving selection of at least one of the selectable items; including the at least one token associated with the selected at least one item into the path expression for one of the identified paths; creating a query for querying data structured in accordance with the object model, the query including at least one of the created path expressions; and executing the query on the database to query the data.

4. The method of claim 1 , wherein the object model is an object model for a storage area network.

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6. A computer-implemented method comprising: receiving a request for mapping information to be displayed to a user; determining point of interest (POI) data associated with the mapping information, the POI data including one or more POIs; analyzing the request to identify a specified area of interest; determining a value of a distance function based at least in part on the specified area of interest; determining a relevance score of each POI in the POI data based at least in part on the distance function as a multiplier to a baseline score of the each POI within the specified area of interest; selecting a portion of the POI data based at least in part upon the relevance score of the each POI of the POI data; and providing the portion of the POI data for display with the mapping information.

9. The computer-implemented method of claim 6 , wherein determining the relevance score of the each POI further comprises: determining that the request includes the specified area of interest; wherein determining the value of the distance function uses a logistic function.

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19. The method of claim 18 , wherein said aggregating step includes using a state transition mechanism for synchronization of aggregation boundaries.

20. The method of claim 19 , wherein said state transition mechanism synchronizes aggregated derived values and user-supplied literals.

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1. A method for searching a database of information, the database of information comprising information related to at least one content unit, the information related to the at least one content unit comprising a plurality of stored annotations related to the at least one content unit, wherein a first stored annotation of the plurality of stored annotations comprises a semantic label and content of the first stored annotation, wherein the database stores the semantic label for the first stored annotation in a first table and stores the content of the first stored annotation in at least one second table different from the first table, the method comprising: receiving a query for searching the database; determining at least one query annotation related to the query, the at least one query annotation comprising a first query annotation, wherein determining the first query annotation comprises determining a semantic label for the first query annotation and determining content of the first query annotation; searching the database based at least in part on the first query annotation, the searching comprising searching the first table of the database using the semantic label for the first query annotation and searching the at least one second table of the database using the content of the first query annotation; and receiving, in response to the search, information regarding at least one matching content unit to which at least one stored annotation relates, the at least one stored annotation comprising an annotation having a semantic label and content matching the semantic label and content of the first query annotation related to the query.

9. The method of claim 1 , wherein: the determining the at least one query annotation related to the query comprises determining a plurality of query annotations related to the query, the plurality of query annotations comprising the first query annotation and a second query annotation, the first query annotation and the second query annotation relating to a portion of the query having multiple interpretations, the first query annotation relating to a first interpretation of the portion of the query and the second query annotation relating to a second interpretation of the portion of the query; the searching the database based at least in part on the first query annotation comprises: evaluating the first query annotation and the second query annotation based at least in part on a ranking of interpretation types for portions of queries having multiple interpretations; and searching the database based at least in part on the first query annotation in response to determining that an interpretation type of the first query annotation is ranked higher in the ranking that an interpretation type of the second query annotation.

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6. The apparatus of claim 1 wherein said addressing means is further responsive to a signal representing the number of data words stored in said data storage means such that a respective number of successive data words are stored together with said qualified data word in said data storage locations.

1. An apparatus for acquiring data words which are present on synchronous logic circuitry of a system under test, comprising: (a) detecting means coupled to said data bus for producing an acquisition signal indicative of the occurrence of at least one particular data word on said logic circuitry; (b) data storage means having a plurality of storage locations and addresses corresponding with said locations, said data storage means coupled to said data bus for storing a plurality of successive data words; and (c) addressing means, responsive to said acquisition signal and to the presence of data words on said data bus, for producing the storage addresses of said successive data words in said data storage means such that a predetermined number of successive data words preceding each said particular data word on said logic circuitry are stored in locations in said data storage means corresponding to said storage addresses.

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19. A method for facilitating information transfer between a host computer and a client computer via a server computer topologically intermediate to the host computer and the client computer, comprising: configuring a presentation space buffer within a memory of the host computer and storing computer display information into the presentation space buffer; exchanging information using data streams, including transmission of the presentation space buffer as a presentation space data stream, via a communications interface of the host computer; displaying a markup language document and forwarding user inputs using a web browser application of the client computer; and interfacing to the host computer via a communications medium over which data streams are exchanged, including the transmitted presentation space data stream, using a display control of a server application framework of the server computer; converting the transmitted presentation space data stream into a markup language document using a host extension of the server application framework of the server computer, the markup language document having instructions that identify position information for a cursor on a Web page and for modifying the presentation space buffer in the host; and interfacing to the client computer via a network medium over which the markup language document is served and the forwarded user inputs received using a web server application of the servor computer.

20. A method according to claim 19, further comprising: storing display information received from the host computer via the transmitted presentation space data stream into the display control of the server application framework of the server computer; exchanging data and commands over the communications medium using an interface of the client computer to the host computer; and exchanging data and commands over a bi-directional data path using an interface of the client computer to the host extension.

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1. A face recognition method on a computing device, comprising: obtaining a plurality of training face images which belongs to a plurality of face classes, wherein a face class includes one or more training face images and represents an identification of the one or more training face images; obtaining a plurality of training dictionaries corresponding to the plurality of training face images, wherein the plurality of training dictionaries include a plurality of deep feature matrices; obtaining an input face image; partitioning the input face image into a plurality of blocks; extracting corresponding deep feature vectors of the plurality of blocks of the input face image using a deep learning network; applying a collaborative representation model to represent the deep feature vectors of the blocks of the input face image with the training dictionaries and representation vectors; computing residual errors for the face classes, a residual error for a face class being a summation of errors for all blocks corresponding to the training face images in the face class, wherein an error for a block exists between a feature vector of the block in the input face image and the collaborative representation model of the block corresponding to the face class; classifying the input face image by selecting a face class that yields a minimum residual error as a recognition face class; and presenting the recognition face class of the input face image.

6. The face recognition method according to claim 1 , wherein: provided that T denotes the training face images, y denotes the input face image, the training face images and the test face image are partitioned into p blocks, F(•) denotes deep features extracted from blocks in training face images, F(T r ) denotes the deep feature matrix of a r th block in the training face images, F(T i r ) is a submatrix of F(T r ) and denotes the deep feature for the r th block in a i th face class, f(y r ) denotes the deep feature vector of the r th block from the input face image, a*r denotes a resultant representation vector of the r th block obtained from the collaborative representation model, w* r denotes a weight corresponds to the resultant representation vector a* r , a* i r denotes a segment of a resultant representation vector a* r associated with class i, and e i (y) denotes the residual error for the class i, the residual for the face class i is computed as e i (y)=Σ r=1 p w* r |f(y r )−F(T i r )a* i r ∥ 2 2 ; and the identity of y is given as, Identity(y)=argmin i {e i }.

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1. A method of providing content for display, comprising: receiving, at one or more of a plurality of servers, a first plurality of content items including a first content item, and a second plurality of content items including a second content item, the second content item comprising a review, a comment, or a social-network share; annotating, by any of the plurality of servers, the first content item with one or more entity annotations descriptive of one or more entities of the first content item based on a mapping of phrases in the first content item to pre-defined entities, wherein each of the one or more entities of the first content item is a respective place or respective thing represented in the first content item; selecting the first content item from the first plurality of content items for display at a client device; annotating, by any of the plurality of servers, the second content item with one or more entity annotations descriptive of entities of the second content item; comparing the one or more entity annotations of the selected first content item to the respective one or more entity annotations of two or more of the second plurality of content items including the one or more entity annotations of the second content item; selecting, based on the comparison, the second content item based on the one or more entity annotations of the second content item matching the entity annotation of the first content item; generating a content section comprising the first content item along with the second content item; and providing, based on the selection of the second content item, the content section to the client device for aggregate display of the first content item and the second content item.

10. The method of claim 1 , comprising: annotating the first content item further based on a relevancy of the phrases in the first content item to a particular entity.

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13. A system comprising: a memory for storing executable instructions; a processor for executing the instructions for training a language engine to train for statistical machine translation and training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; at least two translating parts stored in memory and executable by the processor, wherein at least one translating part is a non-statistical translation part, each of the at least two translating parts operational to translate information from a first language to a second language and each of the at least two translating parts capable of translating equivalent phrases, each of the at least two translating parts being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translating parts that are to be utilized to translate the substrings; and a classifier part stored in memory and executable by the processor to automatically select a preferred component from the at least two translating parts, the preferred component providing a translation having a highest probability of being correct.

14. A system as in claim 13 , further comprising a training corpus.

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3. The computing device of claim 1 , the instructions to further configure the at least one processor to: receive an order of sharpness indicating that a fifth image frame is sharper than a sixth image frame and the sixth image frame is sharper than a seventh image frame; generate, using the first feature metric, a fourth feature value associated with the fifth image frame; generate, using the first feature metric, a fifth feature value associated with the sixth image frame; generate, using the first feature metric, a sixth feature value associated with the seventh image frame; receive a third score output by the image classifier based on the fourth feature value; receive a fourth score output by the image classifier, the fourth score based on the fifth feature value; receive a fifth score output by the image classifier, the fifth score based on the sixth feature value; determine a first correlation between the order of sharpness and the third score, the fourth score and the fifth score output by the by the image classifier; determine that the first correlation satisfies a second selection criteria; and select the first feature metric for use in image frame selection.

4. The computing device of claim 3 , wherein the first correlation is a Pearson correlation or a Spearman correlation.

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10. The method of claim 8 wherein the trigger event is a change in the requesting user's current context data.

11. The method of claim 10 wherein the change in the requesting user's current context data is a change in the requesting user's current physical location.

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16. The method of claim 14 , further comprising: computing a value of information based on a set of inferred likelihoods of receiving different answers from one or more users, and based on receiving context information about the one or more users; and generating the series of one or more questions when the value of information that is computed breaches a threshold.

18. The method of claim 16 , further comprising inferring the items of interest from the context information about the one or more users.

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15. The computer program product of claim 10 , wherein the step of determining the data to be provided into the specific portion of the template document comprises determining confidence scores for the recognised part of the verbal passage and the recognised handwritten information.

10. The computer program product of claim 7 , wherein the step of determining the data to be provided into the specific portion of the template document comprises: determining a part of the verbal passage that contains the information for the specific portion of the template document and recognising that part of the verbal passage by identifying words or phrases; recognising the handwritten information corresponding to the verbal passage by recognising text or graphics; and determining the data to be provided into the specific portion of the template document based on the recognised part of the verbal passage and the recognised handwritten information.

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1. A computer-implemented method comprising: receiving a user input at a computing device, the user input defining behavioral and static aspects of a target process artifact and comprising business process information for use in a specific business process model within an organization, the behavioral aspect comprising inputs for one or more behavioral reasoning processes comprising substitution, auto-completion, and deadlock/liveliness verification; automatically defining a query specification comprising: an axiom component expressing the static aspect using a logical expression, and a process definition component expressing the behavioral aspect using ontologized π-calculus; querying a process artifact library using the query specification, the process artifact library provided as a computer-readable repository that stores one or more of process patterns, models, fragments, and guidelines, the querying comprising: querying the process artifact library relating to the static aspect of the target process artifact to obtain a subset of the process artifact library; after querying, performing π-calculus reasoning, related to the behavioral aspect of the target process, on the subset of the process artifact library; and outputting a candidate process artifact matching the behavioral and static aspects, based on querying the process artifact library.

17. The method of claim 1 , further comprising: determining a business guideline associated with the candidate process artifact; and outputting the business guideline.

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10. The method of claim 1 , further comprising: outputting a proposed spelling correction differing from the misspelled word at most by replacements of characters with equivalent characters and resolutions of incorrect numbers of sequential actuations of particular keys at a position of priority with respect to a proposed spelling correction differing from the misspelled word by an INSERT, a SWAP, a REPLACE, or a DELETE operation with respect to a nonequivalent character.

1. A method of identifying a proposed spelling correction for a word that has been determined to at least potentially be misspelled, the method comprising: receiving from a data source a series of characters of a candidate spelling correction; making a determination for each character of at least a portion of the series that at least one of: the character validly corresponds with a predetermined portion of a canonical version of the word, and the character is, according to at least one spell check algorithm from among a number of spell check algorithms, within a predetermined edit distance from a predetermined portion of the canonical version of the word; and outputting at least a portion of the candidate spelling correction as a proposed spelling correction, wherein the canonical version of the word includes a character set having both diacritical and non-diacritical forms of at least one character.

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13. A computer-readable storage medium containing instructions for controlling a computer system to adjust the influence of a first author on a topic, by a method comprising: identifying articles posted by the first author on the topic during a current period and an earlier period; identifying other authors that cited or posted articles on the topic during the current or earlier periods; for each of the other authors, determining the authority of each of the other authors based on whether the other authors cite during the current period an identified article posted by the first author; and adjusting the influence of the first author on the topic based at least upon the determined authority of each of the other authors that cites during the current period an identified article posted by the first author, and whether the first author published an article during the earlier period; before adjusting the influence for the current period of the first author's post of the identified article, initializing the influence for the current time period based on the influence for the latest earlier period; and adjusting the influence to reflect an increase in authority if the first author has published on the topic during the current period; wherein adjusting the influence of the first author on the topic based at least upon whether the other authors cite during the current period an identified article posted by the first author for each author identified as the other authors includes increasing the influence if the other authors cite during the current period the identified article and decreasing the influence if the other authors do not cite the identified article during the current period.

17. The computer-readable storage medium of claim 13 wherein determining whether an author cited a post includes identifying links to the post.

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30. The method of claim 1 , wherein said sub-portion is a frequently used plurality of words and said test method includes replacing said frequently used plurality of words with a word or a different plurality of words.

1. A method for identifying a critical textual passage and test method that influence the pagination of electronic documents such that the modification of text to said critical textual passage by said test method has the effect of decreasing or increasing the page count of the document, said method comprising the steps of: providing a document comprising a plurality of paragraphs and a plurality of page breaks; determining a first plurality of existent page break locations in the document; selecting a sub-portion of the document's text; selecting a test method for modifying said sub-portion of the document's text; performing said test method on said sub-portion of the document's text; recalculating changes in page break positions resulting from performing said test method; determining a second plurality of updated page break locations in the document; detecting a change in page break positions between said first plurality of page break locations and said second plurality of page break locations; recording the location of said sub-portion of document text and said test method used to create the change in page break locations.

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26. The sink device of claim 25 , wherein, responsive to determining, based on an indication of compression status for a second current set of graphical command tokens, that a received version of the second current set of graphical command tokens is compressed using frame based compression, the at least one module is further executable by the one or more processors to generate a reconstructed version of the second current set of graphical command tokens based on a second previous set of graphical command tokens and a received delta between the second current set of graphical command tokens and the second previous set of graphical command tokens of the plurality of sets of graphical command tokens, wherein the received version of the second current set of graphical command tokens is compressed using frame based compression where a length of the second current set of graphical command tokens is the same as a length of the second previous set of graphical command tokens.

25. A sink device comprising: a memory; one or more processors; and at least one module executable by the one or more processors to: receive, from a source device, a version of a current set of graphical command tokens and an indication of a compression status of the current set of graphical command tokens, wherein the current set of graphical command tokens is from a plurality of sets of graphical command tokens respectively renderable into a plurality of frames of video data; responsive to determining, based on the indication of the compression status, that the version of the current set of graphical command tokens is compressed using token based compression: determine that the version of the current set of graphical command tokens indicates respective deltas between respective graphical command tokens of the current set of graphical command tokens and similar graphical command tokens of a previous set of graphical command tokens, wherein: the version of the current set of graphical command tokens further includes a token prediction map that indicates, for each graphical command token of the current set of graphical command tokens, whether a similar graphical command token can be located in the previous set of graphical command tokens, for each respective graphical command token of the current set of graphical command tokens for which the token prediction map indicates that a similar graphical command token cannot be located in the previous set of graphical command tokens, the version of the current set of graphical command tokens further includes the respective graphical command token, and for each respective graphical command token of the current set of graphical command tokens for which the token prediction map indicates that a similar graphical command token can be located in the previous set of graphical command tokens, the delta for the respective graphical command token includes: a list indicating respective locations of one or more chunks of data within the respective graphical command token that are different than the located similar graphical command token of the previous set of graphical command tokens, and the one or more chunks of data within the respective token that are different than the located similar graphical command token; and generate reconstructed versions of respective graphical command tokens of the current set of graphical command tokens based on the previous set of graphical command tokens and the respective deltas; and render a frame of video data based on the reconstructed version of the current set of graphical command tokens.

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7. The system of claim 6 , wherein the axiom is stored in a knowledge base.

6. A system for assigning a confidence level to an axiom extracted from a text of a transcription of a voice recording, comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and an audio transcription tool coupled to the bus that when executing the instructions causes the system to: receive the text of the transcription; compare every word from the text to a customer specific dictionary and a dictionary of common language words; determine a number of inaccurately spelled words in the transcription based on the comparing; assign, using a Gaussian distribution, a confidence level to the text of the transcription based on the determining; estimate an accuracy of the text based on the assigned confidence level; gather external information related to words in the text by retrieving a set of axioms that further define the words in the text of the transcription from a set of sources, each axiom in the set of axioms comprising a proposition that is regarded as being at least one of established, accepted, and self-evidently true; determine a confidence level of each source of the set of sources; and assign a confidence level to each axiom of the set of axioms based on a combination of the confidence level of the set of sources and the accuracy of the text estimated based on the assigned confidence level.

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37. The system of claim 22 , wherein the plurality of dependency links are obtained from a document containing the dependency links, the document contents are described in the structured definition language.

22. The system of claim 21 , wherein the events are selected from the group comprising user events and system events.

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39. The method of claim 33 , wherein the algorithm determines a best-individual-fit for the at least one value for each frame individually.

43. The method of claim 39 , wherein the algorithm further comprises automatically assessing the best-individual-fit values to determine the scaling factor.

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36. The mobile device of claim 35 , wherein tagged content is converted into the visual items of playable content using specific tags and patterns of tags and values on the web page of tagged content to identify content on the web page.

35. The mobile device of claim 33 wherein the processor is configured to: parse the web page for content to detect a directory of feeds, particular tagged contents, images, and text.

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18. A system comprising: at least one processor; at least one memory device; at least one data storage device; a grammar store on the at least one data storage device storing a grammar rule, the grammar rule including a grammar rule item, the grammar being a descriptive specification composed of grammar rules used to computationally determine content types to facilitate selection of grammar rules suitable to translate electronic content to a desired form utilizing grammar rule items; a data structure parsing module retrievable from the at least one data storage device to the at least one memory device and executable by the at least one processor to access a first data object and a second data object of a data structure, the data structure representing a page description language document that includes page description language document content and non-page description language document content included or referenced in data objects of the page description language document, the second data object being associated with the first data object, to select, based on first content included in the first data object, the grammar rule, to select, based on second content of the second data object, the grammar rule item, and to generate, based on the second content and the grammar rule item, a portion of a first markup language document representation of the page description language document, the second content is non-page description language document content; a textual representation parsing module retrievable from the at least one data storage device to the at least one memory device and executable by the at least one processor to access a second markup language document representation of electronic content, the second markup language document representation including a first textual element semantically containing a second textual element, to select the grammar rule and to create a third data object for inclusion in a second page description language document, the selection of the grammar rule and the creation of the third data object being based on at least the first textual element, to select, based on at least third content in the second textual element, the grammar rule item, and to associate, according to the grammar rule item, a data element with the third data object, the data element including fourth content in the second textual element; and wherein the non-page description language document content is at least one of digital video, frames or sets of frames of digital video, digital audio, an animation, an image, and a media stream.

37. The system of claim 18 , wherein the first textual element is a first markup language opening tag paired with a markup language closing tag, and wherein the second textual element is a second markup language opening tag located in the second markup language representation between the first markup language opening tag and the markup language closing tag and located within the next containment level below the first textual element.

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9. The method as claimed in claim 8, wherein the weightings are determined using a statistic quality measure for the reliability of a feature vector component.

8. The method as claimed in claim 7, wherein the method further comprises calculating the modified local emission probability, for generating a feature vector by a state of a hidden Markov model, by calculating a logarithmic emission probability for each component of this feature vector and multiplying the logarithmic emission probability by a weighting, and by summing these weighted logarithmic emission probabilities over all components of this feature vector; the weighting of a component of a feature vector being in this case a measure of the reliability of this component on an assumption that only two specific states of a hidden Markov model are to be compared with one another.

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1. A system for processing encrypted information, the system comprising: key generator hardware for processing an input key associated with the encrypted information according to an alogorithm to generate a unique output key, the decryption key generator comprising a single chip microprocessor programmed as a finite state machine which, in each of a plurality of states, responds to one of a plurality of predetermined input words to change to another of a plurality of states and output a corresponding output key word, a plurality of repeatable output key word sequences being generated only with predetermined input key word sequences with each word of a repeatable output sequence being dependent on the present state of the microprocessor and on an input word to the microprocessor which is acceptable at that state; and decryptor means for receiving the encrypted information and a corresponding output key from the key generator hardware and for decrypting the received encrypted information based on the received output key.

3. A processing system as claimed in claim 1 wherein the decryption key generator provides a pseudorandom output when other than an acceptable input key word sequence is received.

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4. An interface according to claim 3 wherein the first physical format differs from the standard physical format and the second physical format differs from the standard physical format, and wherein the physical compatibility means comprises: a first translator element connected between the executive means and the instrument, the first translator element changing the physical format of digital signals communicated to and from the instrument to effect physical compatibility, and a second translator element connected between the executive means and the host computer, the second translator element changing the physical format of digital signals communicated to and from the host computer to effect physical compatibility.

6. An interface according to claim 4 further comprising: means for converting prohibited digital data characters from the instrument into digital characters which are allowed inputs to the host computer.

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7. A system for analyzing workflows associated with a computer application, the computer application installed in a client environment, the system comprising: a memory; and at least one processor in communication with the memory, wherein the computer system is configured to perform a method, the method comprising: identifying first metadata describing an original workflow, the original workflow providing an original configuration of the computer application, the original configuration providing original functionality; identifying second metadata describing a customized workflow, wherein the customized workflow is a modified version of the original workflow, the customized workflow providing a customized configuration of the computer application, the customized configuration providing customized functionality different from the original functionality; comparing, by a computer processor, the first metadata and the second metadata; and generating, based on the comparing, analysis results representing the customized functionality; identifying third metadata describing an updated original workflow, wherein the updated original workflow is a second modified version of the original workflow, the updated original workflow providing updated configuration of an updated version of the computer application, the updated configuration providing updated functionality different from the original functionality and different from the customized functionality; further comparing, by the computer processor, the third metadata with the first metadata and the second metadata; generating, based on the further comparing, second analysis results representing customized updated functionality, the customized updated functionality including the customized functionality and the updated functionality; and creating a merged workflow based on the second analysis results, the merged workflow and the updated version of the computer application providing the customized updated functionality.

12. The system of claim 7 , wherein each of the workflows includes a plurality of workflow steps, wherein each workflow step is associated with step-specific metadata, wherein the step-specific metadata is organized into metadata categories, and wherein the metadata categories include at least one of an origin category, a type-of-step category, and a dependency category.

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43. The computer-implemented method of claim 36 , wherein generating a respective input data hash value HV N comprises: applying a hash function to the N th input data symbol B N and a predetermined number of adjacent input data symbols in the sequence of input data symbols.

45. The computer-implemented method of claim 43 , wherein determining the range of matching input data symbols comprises: iteratively comparing different ranges of input data symbols including the respective input data symbol B N to different ranges of dictionary data symbols including the dictionary data symbol HB N .

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20. A method as recited in claim 7 wherein said step of processing said reset selection further comprises the substeps of displaying a warning that said reset has been selected, determining whether said selection is confirmed, wherein when said reset selection is confirmed, probability weights for all character styles are reset to default values.

7. A method as recited in claim 3 wherein said step of processing inputs further comprises determining whether a reset selection has been made, wherein when said reset has been selected, said reset selection is processed.

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1. A method of decoding video data in a merge mode, comprising: constructing a merge list using available spatial and temporal merge candidates; setting a merge candidate on the merge list corresponding to a merge index as motion information of a current prediction unit; generating a prediction block of the current prediction unit using the motion information; generating a quantized block by inverse-scanning quantized coefficient components, generating a transformed block by inverse-quantizing the quantized block using a quantization parameter, and generating a residual block by inverse-transforming the transformed block, wherein when the current prediction unit is a second prediction unit partitioned by asymmetric partitioning, a spatial merge candidate corresponding to a first prediction unit partitioned by the asymmetric partitioning is excluded from the merge list, and a motion vector of the temporal merge candidate is determined depending on a position of a current block within a largest coding unit (LCU), wherein the quantization parameter is generated per quantization unit, and a minimum size of the quantization unit is adjusted by a picture parameter set, wherein the quantization parameter is generated using a differential quantization parameter and a quantization parameter predictor, wherein if two or more quantization parameters are available among a left quantization parameter, an above quantization parameter and a previous quantization parameter of a current coding unit, the quantization parameter predictor is generated using two available quantization parameters determined according to a predetermined order, wherein if only one is available among the left quantization parameter, the above quantization parameter and the previous quantization parameter of the current coding unit, the available quantization parameter is set as the quantization parameter predictor, and wherein the differential quantization parameter is restored using a bin string indicating an absolute value of the differential quantization parameter and a bin indicating a sign of the differential quantization parameter.

2. The method of claim 1 , wherein a reference picture index and a motion vector of a current prediction unit are a reference picture index and a motion vector of a merge candidate specified by a merge index.

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12. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for performing client-side page layout of web content using templates, the code for: receiving a source comprising a plurality of assets of different asset types; identifying a plurality of candidate templates from a template database, where each identified candidate template comprises a plurality of slots, and where each slot is configured to receive an asset of a particular asset type; for each particular slot of each of the plurality of identified candidate templates, calculating a slot subscore by: identifying an aspect ratio of an image asset included in the source, scaling the image asset to fill the particular slot when the particular slot is an image asset type slot, determining an area of the image asset to be cropped based on an area of the scaled image that extends beyond one or more boundaries of the particular slot, determining whether the determined area of the image asset to be cropped included a specified area of the image asset that should not be cropped, and calculating the slot subscore for the particular slot based at least in part on an amount of cropping to be performed inside the specified area and the determination of whether the determined area of the image asset to be cropped included the specified area; determining a score for each of the plurality of identified candidate templates, wherein the score for an identified candidate template is determined by: aggregating the calculated slot subscores for the plurality of slots included in the identified candidate template, and, comparing a number and types of slots included in the identified candidate template with a number and types of assets included in the source; selecting a particular template from the scored plurality of identified candidate templates based on the scoring; and generating a readable article on a client device, the readable article comprising the assets of the source placed in the readable article according to the selected particular template.

19. The computer program product of claim 12 , wherein determining a score for each of the identified candidate templates comprises scoring frames of the identified candidate templates based on avoiding typographical widows and orphans.

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18. The system of claim 17 , wherein the receiving of the message comprises receiving a multimedia messaging service (MMS) message.

17. A system comprising: a memory that stores instructions; and one or more processors configured by the instructions to perform operations comprising: receiving a message, the message including an image of a product item; identifying, using image recognition, a product keyword based on the image of the product item; comparing the product keyword with a database of candidate keywords associated with candidate product items, the product item being one of the candidate product items; detecting a match between the product keyword and a candidate keyword of the candidate keywords associated with the product item; and based on the detecting of the match, accessing product information for the product item and automatically generating, based on the product information, a draft version of an item listing that lists the product item as being for sale.

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10. The method of claim 9 , wherein configuring the application for the user comprises: receiving user input modifying the selected potential profile; and configuring the application with the modified selected potential profile.

9. A method comprising: operating a computing system to provide a graphical user interface to facilitate determination of user preferences for operation of an application by: rendering on a display of the computing system a user interface for specifying a profile for configuring the application, the graphical user interface comprising at least a first display area, a second display area and a third display area, the first display area configured to display available states that are capable of being categorized among categories by the user to provide a state categorization of the profile, each of the categories corresponding to a respective cost of interruption for the available states that are included in the respective category, the second display area configured to display the state categorization of the profile, the third display area configured to display profiles of one or more other users that include respective subsets of the available states categorized among the categories; receiving at least one user input specifying a first categorization of a first available state of the available states that is chosen by the user in a first category of the categories that is chosen by the user; selecting the first category from the categories to be associated with the first available state based at least in part on the first category being chosen by the user; adding the first available state to the first category, based at least in part on the first available state being chosen by the user, in response to selecting the first category from the categories to be associated with the first available state; displaying an indication of the first available state in the first category in the state categorization of the profile in the second display area based at least in part on the first categorization; automatically determining a plurality of potential profiles, including respective subsets of the available states categorized among the categories based at least in part on preferences from users other than the user in a community of users of the application, based at least in part on an extent to which categorization of the subsets among the categories in the potential profiles is similar to categorization of one or more of the available states among the categories in the state categorization; rendering the plurality of potential profiles accessible to the user through the third display area of the user interface; receiving input from the user through the third display area of the user interface, the input selecting a potential profile; and configuring the application for the user based at least in part on the selected potential profile.

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5. The computer-readable memory device of claim 4 , wherein the dual linear learning algorithm is a support vector machine training algorithm.

4. The computer-readable memory device of claim 1 , wherein the prediction algorithm is a runtime algorithm that is determined by a dual linear learning algorithm that admits a kernel.

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1. A method comprising: receiving a request, at a lightweight directory access protocol (LDAP) directory server, to retrieve data from a LDAP repository communicably coupled to the LDAP server, wherein the request is in the form of a filter that is a logical expression including search terms related to the data; evaluating, by the LDAP server, the filter in terms of statistical data being tracked by the LDAP server; adding, by the LDAP server, statistical data related to the filter to a set of filter tracking data maintained by the LDAP server for one or more filters, wherein the filter tracking data includes at least one of an access frequency of each filter, an evaluation time of each filter, a time that a request for each filter is received, system load when the request for each filter is received, and a number of entries processed for each filter; generating, by the LDAP server, one or more LDAP indices for each of the one or more filters; selecting, by the LDAP server, a defined number of the one or more LDAP indices with a highest dynamic ranking to maintain in the LDAP repository, wherein the dynamic ranking is determined from the statistical data determined for the filter associated with each LDAP index; and deleting, by the LDAP server, a remaining one or more LDAP indices that are not selected for maintenance; wherein the filter tracking data is updated each time the LDAP server receives another request, and the selecting and deleting the remaining one or more LDAP indices is repeated using updated dynamic rankings based on the updated filter tracking data on an on-going basis.

20. The method of claim 1 , wherein selecting one or more of the LDAP indices to maintain further includes selecting LDAP indices whose dynamic ranking is above a threshold level.

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5. The method recited in claim 1 , wherein the neural network employs a mergesort process to compare potential characters from the first and second lists.

1. A method implemented by a stylus-based personal computer for recognizing handwriting of a particular user, the method comprising: storing a set of handwriting samples of a particular user; receiving a handwritten inputs from the particular user for recognition; separately providing the handwritten input to first and second recognition engines, respectively, each of the first and second recognition engines applying a separate process for recognizing the handwritten input; producing by the recognition process of the first recognition engine a first list of alternative classifications of the handwritten input by matching features of the handwritten input to features of the stored handwriting samples of the particular user, each of the classifications of the first list comprising a potential character with an associated recognition probability; producing by the recognition process of the second recognition engine a second list of alternative classifications of the handwritten input without utilizing the stored handwriting samples, the process of the second recognition engine being designed to generically recognize handwriting for a plurality of users, each of the classifications of the second list comprising a potential character with an associated recognition probability; applying data of the handwritten input, the first list, and the second list to a comparative neural network for processing, the applied data including a context feature of the handwritten input, a descriptive feature of a potential character and an associated recognition probability from the first list, and a descriptive feature of a potential character and an associated probability from the second list; outputting a character as a recognition result of the handwritten input based on the processing of the neural network, the outputted character being one of the potential characters in the first and second lists; and adapting the stored set of handwriting samples by adding a previously received handwritten input from the particular user to the set before a subsequently received handwritten input from the particular user is provided to the first and second recognition engines, wherein the neural network is configured to merge the first and second lists by coalescing common classifications of the handwritten input in the first and second lists, wherein the neural network is based on a computational model comprising a group of interconnected processing units, and wherein the recognition process of the first recognition engine matches context features of the subsequently received handwritten input to the context features of the adapted set of handwriting samples to produce the first list for the subsequently received handwritten input.

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15. A system, comprising: one or more computers including a non-transitory memory device; and software stored in the memory device in data communication with the one or more computers, the software including instructions executable by the one or more computers and upon such execution cause the one or more computers to perform operations comprising: receiving, for each target document of a plurality of target documents that a search engine has identified in response to a query, an address of the target document, the target document including query-relevant text at an intra-document portion of the target document; for each address of the target document of the target documents: generating an artificial anchor, the artificial anchor corresponding to the intra-document portion of the target document and undefined in the target document; appending the artificial anchor to the address of the target document; and providing, to a client device, a plurality of search results, wherein each search result of the search results identifies a corresponding target document and includes the address of the target document appended with the artificial anchor as a search result link to the target document; wherein the artificial anchor includes a preassigned artificial anchor designator designating the artificial anchor to an artificial anchor module in the client device, wherein the artificial anchor includes the preassigned artificial anchor designator as either a prefix or a suffix and wherein the preassigned artificial anchor designator includes a preassigned set of text characters, and the artificial anchor designator and the artificial anchor are ignored by a client web browser in a client device not having the artificial anchor module.

18. The system of claim 15 , wherein the artificial anchor includes query-relevant text from the intra-document portion of the target document.

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12. The computer storage medium of claim 11 , wherein: the optimal conditional rule for a node or leaf is the rule that is optimal for the condition that a parent node of the node or leaf is associated with a particular canonical suffix-rewriting rule; and selecting an optimal canonical suffix-rewriting rule for each node according to the optimal conditional rules for the node comprises: determining an optimal canonical suffix-rewriting rule for a root of the suffix tree; and determining an optimal canonical suffix-rewriting rule for each remaining node in the tree, wherein the optimal canonical suffix-rewriting rule for a node in the tree is the optimal conditional rule for the canonical suffix-rewriting rule associated with a parent of the node.

11. The computer storage medium of claim 8 , wherein selecting the minimum colored subset of the nodes and leaves in the suffix tree comprises determining optimal conditional rules for each node and leaf in the suffix tree, and then selecting the minimum colored subset and the optimal canonical suffix-rewriting rule for each node and leaf in the subset according to the optimal conditional rules.

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3. The non-transitory processor-readable medium of claim 1 , wherein the narrative template is selected based at least in part on a pseudo-random selection process.

1. A non-transitory processor-readable medium storing code representing instructions that when executed cause a processor to: select, based on a statistic indicative of a tone associated with an event, a narrative tone type; select, based on a narrative content type associated with the event, a narrative template that includes a set of phrases; select, based on the selected narrative tone type, a phrase variation from a set of phrase variations associated with a first phrase from the set of phrases; select, based on the selected narrative tone type, a phrase variation from a set of phrase variations associated with a second phrase from the set of phrases; send a signal indicative of a narrative content portion that includes the phrase variation associated with the first phrase and the phrase variation associated with the second phrase; and send a signal such that the narrative content portion is output to a display.

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20. A method as described in claim 19 , wherein the part-of-speech is a noun, verb, adjective, or adverb.

19. A method implemented at least partially in hardware of a computing device comprising: receiving a natural language input by the computing device; processing the natural language input by the computing device to identify an image editing operation, the processing performed using a vocabulary that includes a set of words and a sense that identifies a part-of-speech for each of the words that is biased for a domain that includes image editing operations, the natural language input not being part of the set of words of the vocabulary, the processing comprising disambiguating the natural language input according to a term sense bias applied to a term semantic distance, the term sense bias relating to the sense that identifies the part-of-speech for each of the words based on the domain that includes image editing operations; and performing the image editing operation by the computing device.

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6. The method according to claim 5 , wherein the text features of the block comprise at least one of: number of the block's occurrences in the plurality of historical versions; size of the block; positions of the block in pages of the plurality of historical versions; number of differences in the block; distribution style of differences in the block; and positions of differences in the block.

7. The method according to claim 6 , wherein evaluating a level of the block in the document structure on the basis of text features of the block among the plurality of blocks comprises: with respect to at least one aspect of the text features, calculating a score component; and calculating the probability score of the block on the basis of the score component.

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10. The apparatus of claim 7 wherein the input device controllable, operational indicia further comprise a search indicia enabled for searching the textual matter data file.

7. An apparatus for use in improving reading speed with comprehension comprising: a computer system having a means for data storage, a means for data computation and presentation formatting, and a means for data display; the data display means providing an animated designated word display area and a plurality of animated, input device controllable, operational indicia; the data computation and presentation formatting means being enabled for presenting a textual matter data file selected from the data storage means, on the data display means as a series of textual portions in timed sequence with each of the textual portions being replaced by a next said textual portion in turn; a set of selectable burst buttons on the video monitor screen enabled for displaying a preset number of words or sentences before stopping such that users can burst back to re-read a previous set of words, repeat to reread the last set of words, or go forward with a new set of words; a set of selectable search buttons on the video monitor screen enabled for selecting one of the search buttons to find a specific word within the textural matter, selecting another of the search buttons to find a set of words within the textural matter, and selecting a still further one of the search buttons to find a sentence within the textural matter; and an operational indicia enabled for searching the textual matter data file forward or backward and for displaying the data file accordingly by dragging the operational indicia with a pointing device.

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20. The method according to claim 16 , wherein the document comprises image identification numbers for indexing each of said plurality of images in said document.

16. A method for transmitting a plurality of images within a document, said method comprising the steps of: selecting, by a user of a display device, said document stored within a central database said document comprising a plurality of images and a corresponding plurality of image identification numbers, said document downloaded earlier to said central database from a local database, said central database storing therein full images for each page of said document and thumbnail images corresponding thereto, whereby said image identification numbers index said plurality of images; transmitting, by said central database to said display device, said plurality of images corresponding to said document, a first of said plurality of images, in a first file, being a full image, and the remainder of said plurality of images, in a second single file, being thumbnail images; and logging and tracking functions are performed by the document image management system on said documents stored in said central database in a system journal element, whereby when said user of said display device selects a given thumbnail image from said second file of thumbnail images, the central database forwards the full image corresponding to said given thumbnail image.

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11. The computer-implemented method of claim 8 , further comprising receiving a data structure as part of the query, the data structure containing data field names of at least some of the specified data fields, a search range for each one of the data field names and a Boolean term specifying a relation between the data field names, and further comprising transforming the data structure into a character string and using the character string for execution of the query.

8. A computer-implemented method for performing a database query, the database having a database table for storing records comprising data values, the database table having first columns for storing the data values, each one of the first columns being assigned to a data field of a set of predefined data fields, and at least one second column for storing keys, each key identifying one of the records stored in the database, and a set of index tables, each index table being assigned to one of the data fields and having assigned thereto an index table identifier, the method comprising: receiving a query, the query specifying a subset of the set of data fields and a search range for each specified data field, and processing the query by checking each one of the index tables for being relevant for the execution of the query, one of the index tables being relevant if the one of the index tables is assigned to one of the specified data fields, storing the index table identifier for each relevant index table in a query execution table, sorting the query execution table in accordance with a predetermined ordered sequence of index table identifiers, executing the query using the index tables identified in the query execution table in the order given by the sorting of the query execution table.

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21. The system of claim 20 , wherein the term of experience is a number of seconds, minutes, hours, days, weeks, months, years, or decades.

20. The system of claim 19 , wherein the processor is further configured to: when the experience range is zero: set the term of experience to zero; and when the experience range is greater than zero: determine a start time for the experience range; determine an end time for the experience range; compute a time difference between the start time and the end time; and set the term of experience to the time difference.

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1. A method comprising: identifying a data record for deletion from a database and storage in a data archive, the data record comprising a plurality of data record attributes, each of the plurality of data record attributes comprising a value that comprises at least one term; creating an archive record that comprises a first subset of attribute values of the plurality of data record attributes and an index record that comprises a second subset of attribute values of the plurality of data record attributes; storing the archive record in a data archive that is stored separately from the database; adding a reference to a location of the archive record in the data archive to the new index record; adding the new index record to a dictionary-based archive index that is stored separately from the database, the dictionary-based archive index comprising a plurality of index records and a dictionary, the adding of the index record to the dictionary-based archive index comprising identifying every term of the second subset of attribute values of the plurality of data record attributes and adding each of the terms to the dictionary except for those terms that are already in the dictionary, wherein at least one index record of the plurality of index records in the dictionary-based archive index comprises one term from terms stored in the dictionary, references to locations of multiple archive records in the data archive that contain the one term, and information regarding locations of the one term within the referenced multiple archive records, the location information including indications, for each of the multiple of archive records referenced by the at least one index record, respective attributes of the each of the multiple archive records in which the one term is found; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index.

7. The method of claim 1 , wherein: the second subset of attribute values at least includes the first subset of attribute values; and accepting a query for a desired archive record comprises accepting a query to find the desired data record in the dictionary-based archive index based on the values for the second subset of attribute values; the method further comprising: accepting a query from a user for a desired archive record; performing a search of the archive index to find the desired archive record; and returning as a response to the query a responsive subset of the values for the second subset of attribute values for the desired data record.

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7. The method of claim 4 , wherein said content suggestions and said engagement suggestions are provided auditorily.

4. The method of claim 3 , wherein said at least one suggestion comprises a summary of said information associated with said URI, and wherein said summary comprises at least one of a fact, a quote, and a metric associated with the relevancy and/or importance of said at least one suggestion.

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18. The digital image processing method as recited in claim 17 , wherein said sub-step of performing discretization uses constrained K-means clustering.

19. The digital image processing method as recited in claim 18 , wherein said at least one hard constraint includes a hard negative constraint that two persons found in the same image from said plurality of digital images have different identities.

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16. The method of claim 1 , wherein the multiple selected operations comprise a semantic operation.

1. A computer-implemented method comprising: accessing a single, natural language voice command; determining, using a repository that associates multiple operations with natural language voice commands, multiple selected operations that correspond to the received single, natural language voice command; and applying the multiple selected operations to a user interface, the single, natural voice command comprising a command to switch between first and second user interfaces, and the multiple selected operations further comprising: a first operation operable to exit the first user interface, a second operation operable to start, after exiting the first user interface, the second user interface, and a third operation operable to log into the started second user interface.

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24. The non-transitory, computer-readable medium of claim 20 , wherein: the source graph comprises a supplemental graph comprising a plurality of supplemental objects; and the object selected from the source graph is a supplemental object corresponding to the second speaker.

20. A non-transitory, computer-readable medium having a computer-executable component for processing content, the computer-executable component comprising: a content processing component configured to: from an item of original content comprising audio content and a plurality of original objects, select an original object corresponding to a first speaker; identify, in the audio content, at least one original recitation affiliated with the first speaker; extract a plurality of objects from a source graph; select an object from the source graph corresponding to a second speaker; obtain one or more audio clips affiliated with the second speaker; and replace, in the audio content, the at least one original recitation with at least one replacement recitation based at least in part on the one or more audio clips affiliated with the second speaker to form an item of modified content.

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6. The method of claim 4 , wherein the one or more network constraints comprise at least one of: available bandwidth, network delay, network packet loss, and node fanout.

4. A method of clustering a plurality of network nodes comprising: using a processor to perform steps comprising: forming a plurality of network attribute maps based on one or more network constraints; forming a communication interest space map based on one or more application constraints, wherein the forming the communication interest space map is based on a distance measurement of a similarity between at least two of one or more communication interest feature vectors, and wherein the similarity is measured using a non-linear distance function; extracting the one or more communication interest feature vectors from the communication interest space map; extracting one or more network attribute feature vectors from the plurality of network attribute maps; obtaining one or more network quality of service constraints; forming a single feature vector for each of the plurality of network nodes, the single feature vector being based on the one or more communication interest feature vectors, the one or more network attribute feature vectors, and the one or more network quality of service constraints; and forming a list in which one or more of the plurality of network nodes are labeled based on the single feature vector for each of the plurality of network nodes.

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13. The document rating calculation system according to claim 1 , wherein the item information database stores a document reference history for each document, and the document rating calculation system comprises: reference score calculation unit that calculates a reference rating of a document based on the reference history of a document fulfilling the retrieval condition which is retrieved by the retrieval unit; and score integration unit that integrates the document rating calculated by the score calculation unit and the reference rating calculated by the reference score calculation unit to calculate an integrated rating of the document.

14. The document rating calculation system according to claim 13 , wherein the score calculation unit calculates the document rating based on a sum of ratings of items included in a set of related items fulfilling the retrieval condition and stored in the item information database, the reference score calculation unit calculates the reference rating based on a number of times the document has been referred, and the score integration unit calculates the integrated rating by multiplying values of the document rating and the reference rating that are respectively normalized with predetermined criteria by a weight, and adding the weighted values.

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15. A machine-readable hardware storage device containing instructions that, when executed by a machine, cause the machine to perform operations comprising: providing, in a user interface, a graphical element that includes an identification of a context in relation to a product or service; in response to receiving a selection of the graphical element in the user interface: processing information from a plurality of users of a network marketplace regarding the product or service to determine attributes relevant to the context, and displaying, in the user interface, a list of the determined attributes; in response to receiving a selection of at least one of the determined attributes: generating result data by retrieving data associated with the context and filtering the retrieved data according to the at least one selected attribute, grouping the result data based on corresponding data types, and providing graphical tabs, in the user interface, for each group of result data, each tab including an identification of the corresponding data type; and in response to receiving a selection of a graphical tab, updating the user interface to display an entry field for entering a new result data of the corresponding data type for which the selected graphical tab is provided.

16. The storage device of claim 15 , the operations further comprising: in response to receiving a selection of a graphical tab, updating the user interface to display the group of result data for which the selected graphical tab is provided.

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33. The system of claim 1 , further comprising: a translation cache, the translation cache storing translations of tokens and combinations of tokens from the source language to the target language, and the translations comprise machine translations and manual human translations.

1. A system comprising: a plurality of machine translation resource servers, each machine translation resource server storing and operable to serve a partition of a collection of machine translation resource data for translation from a source language to a target language, the respective partitions together constituting the collection of machine translation resource data and each respective partition being less than the collection of machine translation resource data; and at least one translation server operable to receive source text in the source language to be translated into the target language, the translation server further operable to obtain machine translation resource data from the plurality of machine translation resource servers and to use the obtained machine translation resource data to translate the source text into the target language, wherein the plurality of machine translation resource servers comprise: a plurality of language model servers each storing and operable to serve a partition of a language model for the target language, each partition being less than the entire language model and the respective partitions together constituting the entire language model, and a translation model server storing and operable to serve to the translation server a translation model for translation between the source language and the target language, and wherein the translation server is operable to: i) obtain translation model data from the translation model server, ii) translate the source text into a set of possible translations based on the translation model data, iii) obtain language model data from at least one of the partitions of the language model based on the set of possible translations, the language model data matching at least one token in at least one possible translation of the set of possible translations, and iv) determine a translation of the source text based on the obtained language model data and the set of possible translations.

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9. A method comprising: (i) for each of a plurality of client devices, storing a corresponding client profile at a server, each corresponding client profile comprising a font capabilities list for a respective one of the plurality of client devices, each font capabilities list comprising a list of fonts for which the respective client device has font structure data stored in a client font data store of the respective client device, the font structure data defining the structure in which text formatted with the respective font is to be rendered on the respective client device; (ii) receiving an electronic data transfer at the server, addressed to a designated one of the plurality of client devices, the electronic data transfer comprising text data and one or more font identifiers identifying one or more fonts to use to render the text data on the designated one of the plurality of client devices; (iii) comparing the one or more font identifiers in the electronic data transfer with a current version of the fonts in the capabilities list stored by the server for the designated device, to determine fonts in the electronic data transfer for which the designated device lacks font structure data; (iv) determining that one of the fonts in the electronic data transfer has an equivalent font that is not included in the current version of the font capabilities list stored by the server for the designated device or in the electronic data transfer; (v) transferring, from the server to the designated device, the font structure data of the equivalent font and the text data, wherein the font structure data of the equivalent font and the text data are included in the same electronic data transfer, and wherein the designated device stores the received font structure data in the client font data store; and (vi) updating the font capabilities list stored by the server for the designated device to include, in a new version of the font capabilities list, the equivalent font whose font structure data is transferred to the designated device.

11. The method of claim 9 further comprising, between steps iv and v: requesting and receiving from another server the font structure data of the equivalent font.

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14. The method of claim 13 , wherein said searching comprises locating all available solutions of the problem in said expert knowledge base based on at least one search pattern to obtain said solutions list.

13. The method of claim 12 , wherein at least one search pattern from said list of patterns includes a relevance value representing a degree of relevance of said search pattern to said formal semantic representation of said user query problem description.

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1. A method comprising, by one or more computing devices: receiving, from a client system of a first user of an online social network, a search query comprising one or more n-grams; determining, based on a contextual speller model, that at least one n-gram of the one or more n-grams is misspelled, wherein the contextual speller model is based at least on a standard language model and a personal language model customized for the first user based on social-networking data associated with the first user; identifying, for each misspelled n-gram, one or more variant-tokens based at least on the search query and the contextual speller model; generating one or more unique combinations of the n-grams and variant-tokens, wherein each unique combination comprises a variant-token corresponding to each misspelled n-gram; calculating a relevance-score for each unique combination based at least in part on the search query and the contextual speller model, wherein the relevance-score for a unique combination is based on a comparison of a probability associated with the n-grams or variant tokens of the unique combination in the standard language model of the contextual speller model to a probability associated with the n-grams or variant tokens of the unique combination in the personal language model of the contextual speller model; generating one or more corrected queries, each corrected query comprising a unique combination having a relevance-score greater than a threshold relevance-score; and sending, to the client system of the first user for display in response to receiving the search query, one or more of the corrected queries.

4. The method of claim 1 , wherein calculating the relevance-score for each unique combination based at least in part on the search query and the contextual speller model comprises: accessing, for each variant-token or n-gram of the unique combination, the contextual speller model to retrieve a probability of the variant-token or n-gram appearing in the search query; and calculating the relevance-score for the unique combination based at least on one or more of the retrieved probabilities.

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14. A text detection process, comprising: preprocessing an image by segmentation using statistical region merging, removing regions that are definitely not text and grouping regions based on criteria of height similarity, color similarity, region distance and horizontal alignment defined as follows: height similarity is defined as max ⁡ ( HEIGHT 1 , HEIGHT 2 ) min ⁡ ( HEIGHT 1 , HEIGHT 2 ) < T h ⁢ ⁢ e ⁢ ⁢ i ⁢ ⁢ g ⁢ ⁢ h ⁢ ⁢ t ⁢ ⁢ _ ⁢ ⁢ s ⁢ ⁢ i ⁢ ⁢ m , where HEIGHT 1 and HEIGHT 2 are heights of two regions and min(HEIGHT 1 ,HEIGHT 2 ) is a non-zero number; color similarity is defined as D ( c 1 ,c 2 )=√{square root over (( R 1 − R 2 ) 2 +( G 1 − G 2 ) 2 +( B 1 − B 2 ) 2 )}< T color , where c 1 =[ R 1 G 1 B 1 ] and c 2 =[ R 2 G 2 B 2 ] are average colors of two regions; region distance is defined as D region <T region , where D region is the horizontal distance of the two regions, and horizontal alignment is defined as D top <T align or D bottom <T align , where D top and D bottom are vertical distances between a top boundary and a bottom boundary; carrying out a feature extraction process to describe each remaining region, where each feature is represented by a stroke feature, an edge feature and a fill factor feature of the region; and classifying each feature by use of a support vector machine (SVM) classifier engine which outputs whether the region is text or not using the following equation: sgn ⁡ ( ∑ i = 1 l ⁢ y i ⁢ α i ⁢ K ⁡ ( x i , x ) + b ) , where (x i , y i ) are feature vectors and groundtruth labels of training samples, x are feature vectors of the regions to be classified, α i and b are parameters obtained by solving the optimization problem defined as min α ⁢ 1 2 ⁢ α T ⁢ Q ⁢ ⁢ α - ⅇ T ⁢ α and subject to y T α=0 (0≦α i ≦C, i=1, . . . , l), and K is defined as K ⁡ ( X , X j ) = exp ⁢ { -  X - X j  2 2 ⁢ σ 2 } where 2σ 2 is a non-zero number to obtain a classification output where 1 indicates the presence of text and −1 indicates the absence of text.

17. The method according to claim 14 , where the binarization is carried out using a plurality of binarization methods with each binarized output being processing by an optical character reader to produce multiple outputs that are combined.

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20. A method according to claim 19, further comprising: storing display information received from the host computer via the transmitted presentation space data stream into the display control of the server application framework of the server computer; exchanging data and commands over the communications medium using an interface of the client computer to the host computer; and exchanging data and commands over a bi-directional data path using an interface of the client computer to the host extension.

19. A method for facilitating information transfer between a host computer and a client computer via a server computer topologically intermediate to the host computer and the client computer, comprising: configuring a presentation space buffer within a memory of the host computer and storing computer display information into the presentation space buffer; exchanging information using data streams, including transmission of the presentation space buffer as a presentation space data stream, via a communications interface of the host computer; displaying a markup language document and forwarding user inputs using a web browser application of the client computer; and interfacing to the host computer via a communications medium over which data streams are exchanged, including the transmitted presentation space data stream, using a display control of a server application framework of the server computer; converting the transmitted presentation space data stream into a markup language document using a host extension of the server application framework of the server computer, the markup language document having instructions that identify position information for a cursor on a Web page and for modifying the presentation space buffer in the host; and interfacing to the client computer via a network medium over which the markup language document is served and the forwarded user inputs received using a web server application of the servor computer.

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7. A storage medium having instructions stored thereon that, when executed by one or more computers, cause the one or more computers to perform a method comprising: obtaining a plurality of model representations of predictive models, wherein each model representation is associated with a respective user and expresses a respective predictive model; and selecting a model implementation for each of the model representations, each model implementation comprising one or more computer programs operable to be executed on one or more computing devices, each model implementation being selected for a corresponding model representation based on one or more system usage properties associated with the user associated with the corresponding model representation, wherein the one or more system usage properties comprise one or more of the following: (i) an amount of system resources that the user has consumed over a given period of time, (ii) a time of day during which system resources were previously used by the user, or (iii) an amount of money that was previously paid by the user for the system resources.

10. The storage medium of claim 7 , wherein the method further comprises: assigning a system resources quota to the user; determining the amount of system resources that the user has consumed over the given period of time; and selecting the model implementation based on an amount of unconsumed system resources according to the system resource quota, wherein an amount of system resources that can be consumed by the selected model implementation does not exceed the amount of unconsumed system resources.

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16. The non-transitory processor-readable medium of claim 15 , further comprising determining that the DNS query is associated with a malicious activity.

18. The non-transitory processor-readable medium of claim 16 , wherein the determining that the DNS query is associated with the malicious activity includes: obtaining historical DNS data associated with the same DNS query; calculating a QC for the DNS query; determining that the QC is higher than a predetermined threshold value; determining that the domain name of the DNS query does not have a predetermined rank; and associating the DNS query with a malicious activity.