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15. The computer system of claim 11 , wherein determining whether the documentation repository includes the at least one archive including documentation content for update further comprises: comparing a value of a timestamp of the at least one archive including the documentation content for update and a value of a central timestamp that represents a time of a last documentation content update of the documentation application, and upon determining that the value of the timestamp of the at least one archive is later in time than the value of the central timestamp, determining that the at least one archive includes the documentation content for update.

11. A computer system to dynamically update help content on a cloud computing platform, the system comprising: a memory to store computer executable instructions; at least one computer processor coupled to the memory to execute the instructions, the instructions comprising: periodically checking a documentation repository by a documentation application to determine whether the documentation repository includes at least one archive including documentation content for update; upon determining that the documentation repository includes the at least one archive including the documentation content for update, retrieving from the documentation repository the at least one archive including the documentation content for update; parsing the at least one archive including the documentation content for update to read meta information specified in the at least one archive; based on the meta information, integrating a portion of the documentation content for update into the documentation application at runtime of the documentation application; determining whether a portion of a name of the at least one archive representing an application name is same as an application name portion of other archive including documentation content stored in the documentation repository; upon determining that the portion of the name of the at least one archive is same as the other archive stored in the documentation repository, comparing a timestamp value of the at least one archive with the timestamp value of the other archive to determine an older version from one of the at least one archive and the other archive; and based on the comparison, deleting from the documentation repository the older version from one of the at least one archive and the other archive.

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16. The device of claim 8 , wherein the speech translation system: further comprises: a second automatic speech recognition module for recognizing speech in the second language; and a second machine translation module for translating recognized speech in the second language to the first language: and is further configured to identify whether the utterance is in the first language or the second language.

18. The device of claim 16 , wherein the speech translation system further comprises an information extraction module for: generating usage statistics from system logs generated by the first and second automatic speech recognition modules, and the first and second machine translation modules; retrieving relevant information based on keyword occurrences in the usage statistics; and presenting the relevant information to the user via the user interface display.

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1. A method to provide internet-based services targeted to a geographic location, the method comprising: receiving a request from a user to provide internet-based services based on a target geographic location; obtaining a plurality of candidate geographic locations associated with the user, each candidate geographic location being associated with a respective candidate confidence level; calculating, with a computer, for one of the candidate geographic locations, a respective aggregate probabilistic utility score, the aggregate probabilistic utility score being based, at least in part, on distances from the respective candidate geographic location to the other candidate geographic locations and the confidence level scores of the other candidate geographic locations; selecting a geographic location based, at least in part, on the aggregate probabilistic utility score from among the candidate geographic locations; and providing internet-based services to the user targeting the selected geographic location.

2. The method of claim 1 , wherein calculating an aggregate probabilistic utility score further comprises: obtaining a route-utility factor indicative of the burden of traveling from the respective candidate geographic location to one of the other candidate geographic locations; and calculating the aggregate probabilistic utility score based on the route-utility factor.

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12. The computer program product of claim 1 , sending messages requires a sender user account, and wherein the sender user account has a user credit balance comprising at least one of earned credits and paid-for credits.

13. The computer program product of claim 12 , wherein at least one of the selection of a pre-existing recording by the sender or the selection of a lyric phrase within the pre-existing recording by the sender causes the user credit balance of the sender to be debited.

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5. The method of claim 1 wherein the at least one of the at least one data source that is not a relational database comprises a shared memory database.

1. A method in a computer system for providing an interface between at least one logical view of data and a plurality of data sources, comprising: receiving an indication of an operation to be performed on the at least one logical view, the at least one logical view including at least one combination of data constructed from and corresponding to two or more of the plurality of data sources, the two or more of the plurality of data sources including at least one data source that is not a relational database, each of the plurality of data sources storing data; automatically determining the corresponding plurality of data sources that were used to construct the at least one logical view; and transparently and automatically causing the stored data in the corresponding plurality of data sources to be adjusted in accordance with the indicated operation, thereby automatically performing the indicated operation on underlying data that corresponds to the logical view.

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8. The system of claim 1 , wherein the one or more types and quantities of virtual assets is determined based on a performance during gameplay.

1. A system for providing gameplay of word-based games puzzles comprising crossword puzzles or word search puzzles, the system comprising: one or more processors programmed with one or more computer program instructions to: receive a selection of a gameplay mode of operation from among a plurality of gameplay modes of operation; select at least a word-based puzzle from among a plurality of word-based puzzles obtained from one or more sources of word-based puzzles; cause the word-based puzzle to be communicated for gameplay based on the received selection of the gameplay mode of operation; impose during gameplay of the word-based puzzle a time limit that relates to an attempt to at least partially solve the word-based puzzle; determine one or more types and quantities of virtual assets to be awarded to a user based on gameplay of the word-based puzzle, wherein the one or more types and quantities of virtual assets is determined based on whether the user solved a word related to one or more input spaces that is associated with a bonus award; allocate the determined one or more types and quantities of virtual assets to the user based on gameplay of the word-based puzzle, wherein a virtual asset is exchangeable for one or more benefits related to gameplay depending on the type of virtual asset; and award the one or more types and quantities of virtual assets to the user.

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37. The method of claim 23 , further comprising: obtaining, from the state store, metadata associated with the query.

23. A method of executing a query in a HADOOP™ distributed computing cluster having multiple data nodes forming a peer-to-peer network for the query, each data node functioning as a peer in the peer-to-peer network and being capable of interacting with components of HADOOP™ cluster, each peer having an instance of a query engine running in memory, each instance of the query engine is configured to perform; the method comprising: receiving, by a one data node in the distributed computing cluster, a query; designating the one data node that receives the query as a coordinating data node; obtaining, by the coordinating data node and through a state store and a name node, (1) membership information regarding all query engine instances that are running in the cluster, and (2) location information regarding where data blocks relevant to the query are distributed among the plurality of data nodes, wherein the state store is separate from the data nodes; parsing the query to create fragments of the query based on data obtained from the state store and the name node; constructing a query plan based on the data obtained from the state store; distributing, by the coordinating data node and according to the query plan, the fragments of the query to data nodes in the distributed computing cluster that have data relevant to the query; receiving, from the data nodes having data relevant to the query, intermediate results corresponding to execution of the fragments of the query; and generating a final result based on the intermediate results for a client.

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2. The system of claim 1 , wherein the plurality of POS tags comprises: a POS tag for a proper noun that is a geographic name; a POS tag for a proper noun that is a name of a person; and a POS tag for a proper noun that is can be both a geographic name and a name of a person.

1. A system, comprising: one or more memory units; and one or more processing units operable to: access text comprising a plurality of words; tag each of the plurality of words with one of a plurality of parts of speech (POS) tags; create a plurality of tokens, each token comprising one of the plurality of words and its associated POS tag; cluster one or more of the created tokens into a chunk of tokens, the one or more tokens clustered into the chunk of tokens based on the POS tags of the one or more tokens; and form a phrase based on the chunk of tokens, the phrase comprising the words of the one or more tokens clustered into the chunk of tokens.

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1. An apparatus for converting a sequence of m-bit information words into a modulated digital signal, where m is an integer, the apparatus comprising input means for receiving the sequence of m-bit information words, m-to-n bit converter means for converting the sequence of m-bit information words into a sequence of n-bit codewords, where n is an integer larger than m, the sequence of codewords forming the modulated signal, which signal comprises bit cells having a first signal value and bit cells having a second signal value, determining means for determining a coding state related to a digital sum value at the end of a modulated signal portion, which digital sum value denotes for said modulated signal portion a running value of a difference between the number of bit cells having the first signal value and the number of bit cells having the second signal value, the m-to-n bit converter means comprising selection means for selecting for the conversion a code word from a set of codewords that depends on the coding state, at least one of the digital sum values determining a first and a second coding state, the first and second coding state being determined in response to the information word that corresponds to the previous codeword, wherein the apparatus is adapted to form a modulated signal satisfying the requirement that the number of consecutive bit cells in the modulated signal having the same signal value does not exceed 7.

4. An apparatus as claimed in claim 1, the apparatus further comprising sync word generator means for generating a sync word for a block of p consecutive code words in the modulated signal, the sync word generator means being adapted to generate said sync word from the following set of available sync words: 11100011111110, 10100011111110, 01100011111110 and 11000100000001, the sync word generator means being adapted to select one of the sync words in dependence upon the coding state.

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14. The system of claim 13 , further programmed to perform operations comprising detecting that the second input is suspicious, wherein: generating the order of the plurality of scoring functions includes giving more weight to the first input than to the second input.

13. The system of claim 12 , further programmed to perform operations comprising: receiving a second query; receiving a plurality of second search results responsive to the second query; selecting a third candidate scoring function and a fourth candidate scoring function from the plurality of scoring functions; presenting the plurality of second search results ordered according to the third scoring function and presenting the plurality of second search results ordered according to the fourth scoring function; receiving second input selecting the third scoring function over the fourth scoring function; and wherein generating the order of the plurality of scoring functions is based on the first input and the second input.

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2. A method in accordance with claim 1 , wherein the geographical locations include a plurality of sites that retain the documents.

1. A method, comprising: storing a plurality of documents distributed amongst a plurality of geographical locations, each document being located in a corresponding geographical location; associating the plurality of documents with respective corresponding geographical locations; associating at least one party with each of the geographical locations such that respective geographical locations have at least one party associated as a contact for that geographical location; assigning geographical markers to the plurality of documents according to the respective geographical locations; and permitting access to contact information for the at least one party associated with a geographical location in accordance with selecting that geographical location and also permitting access to documents located in that geographical location in accordance with the selecting of that geographical location; and wherein the access to the contact information is permitted via at least one clickable indicia displayed to a user and the access to the documents is permitted via at least one clickable indicia displayed to the user at a same time the at least one clickable indicia for the contact information is displayed to the user, the at least one clickable indicia for access to the contact information being different or separate from the at least one clickable indicia for access to the documents.

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5. The device of claim 1 , further comprising: a language selector in the housing structured to select the language in which the prompts are delivered by the user interface to the user during the defibrillation session.

18. The device of claim 5 , in which the language selector is further structured to determine whether the selected language is supported by the device.

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18. The system of claim 17 , wherein updating the speaker adaptation profile comprises modifying an acoustic model.

17. The system of claim 14 , further comprising updating the speaker adaptation profile.

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4. The method of claim 3 wherein determined boundary points on connected component regions are as points that have at least one "off" neighbor and wherein said curves are smoothed using a conventional line-segment approximation algorithm.

3. The method of claim 2 further comprising the step of estimating an intra-word separation from said handwritten text using the projecting of boundaries of the word segment regions lying on said lines of text.

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16. The method of claim 1 , further comprising accessing a database of diagram-to-graph conversion rules including graph topology rules, graph interconnection rules, linguistic rules, or a combination thereof, wherein applying the functional block recognition rules includes applying one or more of the diagram-to-graph conversion rules to the image data, and wherein the functional graph is computer-generated by applying the one or more of the diagram-to-graph conversion rules to the image data.

1. A method comprising: capturing an image of a scene that includes a portion of a diagram representing functional blocks, wherein the functional blocks include at least a first functional block associated with a first computer operation; applying functional block recognition rules to image data of the image to recognize the functional blocks; determining whether the functional blocks comply with functional block syntax rules, wherein the functional block syntax rules indicate a hierarchy of operations associated with the functional blocks; and computer-generating a functional graph corresponding to the diagram based on the functional blocks complying with the functional block syntax rules, wherein the functional graph includes a graphical representation of the functional blocks.

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8. Speech recognition apparatus as defined in claim 7 wherein each of said stored templates further includes a third array having a series of weighting values, one value being assigned to each stored word state based on the importance of the word state to recognition of the word; wherein said determining means is further responsive to said third array; wherein said error value generating means includes: means for increasing the error value by the absolute value of the difference between the values of said duration arrays corresponding to the particular states being compared when the classifications of the states being compared are the same; and means for increasing the error value by an amount equal to the weighting value of said weighting array corresponding to the particular state of said template state array being compared when the classifications of the states being compared are not the same.

9. Speech recognition apparatus as defined in claim 8 wherein said first comparing means further includes means for comparing the last compared incoming speech state with the next state in the template state array when the last compared states had classifications which did not match.

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4. The computer implemented system of claim 1 , wherein the inferred composite type of the variable is represented by a synthesized nominal type, wherein the synthesized nominal type is a data type generated by a compiler, and wherein the compiler generates the synthesized nominal type by generating a normal class definition with a multi-character name comprising at least one of a field associated with a member of the one or more members or a property associated with the member of the one or more members.

5. The computer implemented system of claim 4 , wherein the synthesized nominal type implements at least one of an Equals method or a GetHashCode method.

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1. An image processor-implemented method for associating metadata with image files, comprising: automatically identifying a single image file with existing metadata; automatically analyzing the image content of the single image file to determine candidate content-relevant metadata; automatically comparing the candidate content-relevant metadata to the existing metadata of the single image file to determine inconsistency; automatically using the determined inconsistencies to identify that the candidate content-relevant metadata is completely consistent with the existing metadata or inconsistent with the existing metadata or includes data that is both consistent and inconsistent with the existing metadata; when the candidate content-relevant metadata is completely consistent, then storing such candidate content-relevant metadata that is consistent with existing metadata in association with the single image file; when the candidate content-relevant metadata includes an inconsistency, then presenting the single image file and at least a portion of the inconsistent candidate content-relevant metadata to a user; permitting the user to accept the determined at least a portion of the inconsistent candidate content-relevant metadata or the existing metadata; and storing the user accepted metadata in association with the image file.

3. The image processor-implemented method of claim 1 , wherein storing the candidate content-relevant metadata further comprises storing changed metadata with an associated image.

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17. The system of claim 15 , wherein the translation engine is further operable to provide the output data stream to a question-answering system, wherein the output stream includes a translation map.

15. A system implemented in hardware, comprising: a processor executing a translation engine that is configured to: obtain field oriented electronic document data from an input document, wherein the document data is in a form other than a natural language form; determine, via communication with a detection and conversion database comprising records defining a plurality of data types, a data type of the document data; translate, based on the determined data type and appropriate conversion information records selected from plural different translation data stored in a detection and conversion database, the document data to natural language form; and output, in natural language form, the translated document data to an output data stream, wherein each one of the records is associated with a respective one of the plurality of data types, each one of the records comprises data used in comparisons against the document data during the determining, each one of the records further comprises at least one conversion rule applied to the document data during the translating, and the plurality of data types comprises: document header data; document field data; table header data; table detail data; and signature data.

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14. The database search system of claim 11 , wherein the expected transaction values comprise average values per order.

11. A database search system comprising: a storage element storing keywords entered by at least one user for a plurality of search terms and information related to converted transactions associated with a plurality of searches, the plurality of searches having been performed on the keywords; and a processing system coupled to the storage element, the processing system operative to perform steps comprising: estimating a general transaction probability; estimating unigram keyword probabilities; determining conditional probability values associated with the keywords based on the converted transactions; estimating keyword transaction probabilities based on the general transaction probability, the unigram keyword probabilities, and the conditional probability values; and generating expected transaction values based on the keyword transaction probabilities, wherein the expected transaction values are generated according to: E ⁡ ( T ❘ k , S ) = P ⁡ ( T ❘ k , S ) * ∑ ∀ t ⁢ R ⁡ ( t ❘ k , S ) C ⁡ ( t ❘ k , S ) , where C(t|k,S) is a non-zero value.

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15. The method of claim 10 , wherein a subset of satisfiability checks is combined into a single satisfiability check.

10. The method in claim 1 wherein the property checking schema for the said LTL operator G(p) for a given time frame bound comprises: a) starting search from a given start state at time frame i with a given constraint database, wherein i=0 corresponds to an initial state of the circuit, b) adding a constraint to the database to ensure that p is satisfied in the i th state of a path, and checking for satisfiability, c) if unsatisfiable, terminating the search with failure, d) if satisfiable, checking for each j th state from the start state to i th state whether it is a loopback state and terminating the search with success if a loopback state is found; e) checking for each j th state before the start state whether it is a loopback state and terminating the search with success if a loopback state is found; f) continuing the search by increasing i until the said time frame bound is reached and repeating steps a-e; g) terminating the search inconclusively if the said time frame bound is reached.

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9. The method of claim 1 , wherein the metadata type includes titles of segments of the streamed data.

1. A method comprising: causing streamed data to be stored in a file, wherein the file consists of media data and metadata enclosed separately, wherein causing the streamed data to be stored in the file includes storing in a reception hint track; identifying metadata applicable to two or more samples of the streamed data; causing at least one timed metadata track to be created based on the identified metadata, the at least one timed metadata track describing a referred media track and the reception hint track, wherein the hint track refers to samples comprising instructions for constructing packets for transmission over an indicated communication protocol, wherein the media track refers to samples formatted according to a media compression format; forming at least one group from the two or more samples of the streamed data, each sample in a group having identical metadata content for a metadata type; selecting each sample to group box associated with the reception hint track and the media track; and finding a sample group description index of a particular reception hint sample or a media sample.

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41. The computer readable storage medium defined in claim 34 wherein the plurality of actions comprise two or more of a group consisting of printing, faxing, sending by electronic mail, deleting, grouping, ungrouping, and playing.

34. A computer readable storage medium having instructions stored thereon which, when executed by a computer, cause the computer to perform operations comprising: scanning a coversheet having an overview of a collection; receiving an image of the overview of the collection that comprises a first plurality of indication areas associated with a plurality of documents and a second plurality of indication areas associated with a plurality of actions, wherein the plurality of actions includes printing, faxing, sending by electronic mail, and grouping; identifying at least one action from the plurality of actions set forth in the image; identifying at least one document from the plurality of document for the at least one action identified from the plurality of actions, wherein the identifying the at least one action is performed based on the second plurality of the indication areas in the image and the identifying the at least one document is performed based on the first plurality of the indication areas in the image, wherein the at least one action and the at least one document are identified by scanning the image; and performing the at least one action on the at least one document in response to the identifying the at least one action from the fourth plurality of actions set forth in the image and the identifying the at least one document from the third plurality of document from the image.

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12. The system of claim 7 , wherein the client computing device is further configured to: populate the key-value pair for the data into a repository for the model.

7. A system for implementing model definition, constraint enforcement, and validation, comprising: a client computing device that comprises at least a processor, a browser installed thereupon, and non-transitory memory allocated for the browser and is configured to at least: request a reference to one or more model definition resources for a representation of a model that pertains to a tax preparation or financial management software application at least by transmitting a request for the reference to a remote host computer hosting the tax preparation or financial management application via a network element; execute a model definition resolver, residing on and stored at least partially in memory of the client computing device, that identifies or determines one or more actual locations for the one or more model definition resources at least by resolving the reference and retrieving the one or more model definition resources from the one or more actual locations, wherein the one or more model definition resources specify constraints for constraint enforcement or validation on the model; reduce data processing and data to be populated into the model at least by removing a portion of the data and populating a remaining portion of the data into the model through using one or more validation modules and one or more formatting modules stored at least partially in the memory of the client computing device, wherein the client computing device reducing the data processing and the data is further configured to: disable the constraint enforcement or validation for a portion of a flow of the tax preparation or financial management application; reduce a total number of data elements and a total number of invalid data elements at least by formatting one or more user inputs for the tax preparation or financial management application at the one or more formatting modules; and perform the constraint enforcement or validation at the one or more validation modules on at least the one or more user inputs, which have been formatted, based in part or in whole upon at least the one or more model definition resources obtained by the model definition resolver residing on the client computing device from the remote host computer via the network element; and perform data binding for the data to bind the data to the model by using a first application programming interface located on the client computing device, wherein the client computing device that performs the data binding is further configured to: identify a model definition for a requested key of a key-value pair for the data and obtaining an actual implementation of the one or more model definition resources from the remote host computer by processing the reference with a mapping module; generate a first result at least by determining whether the requested key for the data is allowed in the model based at least in part upon the actual implementation of the one or more model definition resources and further generating a second result at least by determining whether a requested value of the key-value pair for the data matches the model definition; and perform the data binding for the data and the model based at least in part upon the first result and the second result.

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4. The method of claim 3, further comprising the step of searching at least one database for a third information item based on said second information item.

3. A method for defining an interface for a system to receive voice commands to connect a first user to a second user over a network, comprising the steps of: a) receiving a request to define said interface; b) receiving a first information item; c) searching at least one database for a second information item indexed by said first information item; and d) constructing a grammar for said interface using said first and second information items.

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8. An article of manufacture, comprising: a non-transitory computer-readable storage medium storing instructions that, when executed by a computer system, cause the computer system to perform a method comprising: loading a logical structure comprising questions and branches, wherein each said question represents a single interaction between a script and a user, and each said branch represents a link between one of said questions and another of said questions; determining an arrangement of the questions and the branches of the loaded logical structure, in accordance with the loaded logical structure, for presentation to said user; determining a set of questions to be simultaneously presented to the user by performing 1), 2), 3), 4), and 5), below: 1) adding a first question to the set of questions, which is initially empty; 2) designating the first question as a previous question for a test below; 3) adding a next subsequent consecutive question after the previous question to the set of questions if the following conditions are all true, the following conditions being referred to as the test: a) the previous question has only one branch, which is to the next subsequent consecutive question; b) the next subsequent consecutive question does not depend on the previous question, or questions prior to the previous question, for text substitution; and c) the next subsequent consecutive question is not on a different page than the previous question; 4) if conditions a), b), and c) were all true, designating the next subsequent consecutive question as the previous question for the test and looping back to 3); and 5) if conditions a), b), and c) were not all true, stopping the performance of 3), 4), and 5), and adding no further questions to the set of questions; and presenting the set of questions simultaneously to the user as part of a user interface.

10. The article of manufacture of claim 8 , wherein the non-transitory computer-readable storage medium further stores instructions that cause the computer system to perform: using an element of the user interface to interact with an intermediate unit to render the presentation of the questions at the user interface or to allow other manipulation related to the loaded logical structure.

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11. A method for providing hiring recommendations of agents within a call center, comprising: receiving into a call center, a voice sample collected from a candidate agent via a handset; gathering via a speech recognition server the voice sample from the candidate agent, wherein the server comprises a central processing unit, memory, an input port that receives the voice sample from the handset, and an output port; measuring via a spectrum analyzer device within the voice sample voice characteristics comprising at least one of pitch, range of resonance frequencies of vowel, average resonance frequency of particular vowels, spectral tilt, breathiness, creakiness, nasality, speed of words, pause duration and intonation and comparing the voice characteristics from the voice sample with at least one graph comprising voice characteristics for two or more populations of a trait, which are each represented by a curve; assigning a score to the candidate agent by identifying at least a portion of the voice characteristics from the voice sample on the graph based on the comparison, assigning a numerical value to each identified voice characteristic from the voice sample based on the comparison, and summing the numerical values for the identified voice characteristics as the score; identifying by the server one of the populations to which the candidate agent belongs for that trait based on the assigned score; and providing by the server a recommendation for hire within the call center for the candidate agent based on the assigned score and the identified population.

20. A method according to claim 11 , further comprising: providing a display with access to one or more of a recording of the voice sample and the score.

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9. The method as recited in claim 1 , further comprising receiving input modifying one of the one or more panels.

12. The method as recited in claim 9 , wherein the input modifying the panel is an additional erase input erasing a portion of the border of an additional panel, wherein the method further comprises reapplying the windowing algorithm to the additional panel in response to said erasing the portion of the border of the additional panel.

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16. The system of claim 14 , wherein processing the representation for the input acoustic sequence using an attention-based Recurrent Neural Network (RNN) comprises, for the initial position in the output sequence order: processing a placeholder start of sequence token and a placeholder initial attention context vector using the attention-based RNN to update a hidden state of the attention-based RNN from an initial hidden state to a hidden state for the initial position in the output sequence order; generating an attention context vector for the initial position from the representation of the input acoustic sequence and the RNN hidden state for the initial position in the output sequence order; and generating the set of substring scores for the initial position using the attention context vector for the initial position and the RNN hidden state for the initial position.

14. 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: obtaining a representation of an input acoustic sequence, the input acoustic sequence representing an utterance; processing the representation of the input acoustic sequence using an attention-based Recurrent Neural Network (RNN) to generate, for each position in an output sequence order, a set of substring scores that includes a respective substring score for each substring in a set of substrings, comprising, for each position after an initial position in the output sequence order: processing a substring at the preceding position in the output sequence order and the attention context vector for the preceding position in the order using the attention-based RNN to update the hidden state of the attention-based RNN from the hidden state for the preceding position to a hidden state for the position; generating an attention context vector for the position from the representation and the RNN hidden state for the position in the output sequence order; and generating the set of substring scores for the position using the attention context vector for the position and the RNN hidden state for the position; and generating a sequence of substrings that represent a transcription of the utterance.

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19. A process for deploying computing infrastructure comprising integrating computer-readable code into a computing system, wherein said computer-readable code in combination with said computing system is capable of performing a process of correcting semantic errors in code in an integrated development environment, said process comprising: inputting, using a code editor, code being developed by a developer in an integrated development environment; constructing, using a code parser, a syntax tree representation of said code inputted; identifying, in said syntax tree representation constructed for said code inputted, one or more nodes containing semantic errors pertaining to use of a third-party library; choosing a node of said one or more nodes identified in said syntax tree representation constructed containing said semantic errors; displaying multiple suggestions for correcting said semantic errors identified for said node chosen, wherein each of said multiple suggestions include one or more code snippets associated with one or more collaboration records located for said node chosen, and wherein said one or more code snippets are submitted by peer developers to correct said semantic errors identified for said node chosen; displaying a code snippet configuration interface for configuring said one or more code snippets, wherein the code snippet configuration interface comprises: an input parameter active field for identifying input parameters that are required, by said node chosen, to be used with said one or more code snippets; an output parameter active field for identifying output parameters that are required, by said node chosen, to be used with said one or more code snippets; an input/output parameter active field for identifying input/output parameters that are required, by said node chosen, to be used with said one or more code snippets; and a return value active field for identifying a return value that is required, by said node chosen, to be returned by said one or more code snippets; selecting at least one code snippet from said one or more code snippets displayed for correcting said semantic errors identified for said node chosen; and executing said code inputted in said integrated development environment, wherein said at least one code snippet selected is automatically invoked to correct said semantic errors identified for said node chosen.

23. The process according to claim 19 , wherein said identifying further comprises: ascertaining whether or not said at least one code snippet selected for said node chosen is configured to correct said semantic errors contained within said node; if said at least one code snippet selected for said node is configured to correct said semantic errors contained within said node, fetching said at least one code snippet from a code snippet processor; and executing said at least one code snippet fetched based on said type of invocation and said one or more parameters configured for said code snippet selected, wherein said type of invocation includes an execution order value comprising at least one of: before invocation, after invocation and only upon error.

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49. The computer readable medium of claim 33 , where the computer readable medium further comprises instructions for: associating undisplayed aspects of the graphical model with the second part; selecting the second part; and displaying the undisplayed aspects based on selecting the second part.

33. A non-transitory computer readable medium for use on a computing device, the medium storing instructions executable using the computing device, the instructions for: identifying a plurality of entities having relationships therebetween, the plurality of entities having at least one of a graphical model, generated code, a generated report, a requirements document, or an intermediate representation; accessing a first entity from the plurality of entities, the first entity including the graphical model that includes a graphical affordance; accessing a second entity from the plurality of entities, the second entity including at least one of the generated code or the intermediate representation that correspond to the graphical model; and mapping the first entity to the second entity to facilitate graphical identification of a bi-directional mapping between a first part of the first entity, that includes the graphical affordance depicted in the graphical model, and a second part, of the second entity, that includes a segment, of the at least one of the generated code or the intermediate representation, associated with the graphical affordance.

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6. A computer-readable storage medium whose contents cause a computing system to: extract metadata associated with a media file; parse the metadata into a plurality of metadata fields, the metadata in each of the metadata fields comprising a set of keywords, the set of keywords comprising at least one keyword; provide a valid database comprising a plurality of database records, each of the database records comprising a plurality of record fields, each of the record fields comprising a set of keywords, the set of keywords comprising at least one keyword; for each of the plurality of metadata fields, compare the contents of the at least one metadata field to the contents of each of a plurality of record fields to identify a matching record field that contains all of the keywords contained in the metadata field, the plurality of record fields being of a plurality of database records in a ground truth database comprising accurate metadata and not inaccurate metadata; determine a similarity score based on the degree of similarity between each of the plurality of metadata fields and its matching record field, the similarity score being indicative of the quality of the metadata and usable as a work flow process of a search engine; and perform prefix rule evaluation on the plurality of metadata fields and repeating comparing and scoring.

7. The computer-readable storage medium of claim 6 , further comprising contents that cause the computing system to replace the contents of the plurality of metadata fields with the contents of the database record containing the matching record field.

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12. The one or more computer-readable storage memories of claim 1 , the at least one object associated with the proxy object comprising a function.

1. One or more computer-readable storage memories comprising computer readable instructions which, when executed, implement: a security module configured to enable secure information transfer between a web browser's scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, the module configured to enable the at least one object to be returned across the one or more domains being configured to return a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine.

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1. A method comprising: receiving, using one or more processors, at least one image; acquiring, using the one or more processors, metadata associated with the at least one image, the metadata including location information for the at least one image; clustering, using the one or more processors, the at least one image into a plurality of image clusters, wherein each image cluster is associated with a geographic location based on the location information; and causing, using the one or more processors, the plurality of image clusters to be displayed on a map, wherein each image cluster is displayed on the map according to the geographic location associated with the image cluster, and wherein each image cluster of the plurality of image clusters includes a portion of the metadata associated with that image cluster and wherein the plurality of image clusters and corresponding metadata portions are displayed so as to be visible simultaneously.

15. The method of claim 1 , wherein the location information represents a location of a subject of the at least one image.

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1. An electronic mail management system for handling electronic mail in a shared multiple user environment, in which the users' incoming electronic mail are sent and received from external correspondents, said system includes a common mail server with a central storage wherein electronic mail items of the users are stored and may be retrieved, said system comprising: detecting means for monitoring the flow of in- and outbound electronic mails on the mail server for a specified set of users, and intercepting the in- and outbound e-mails; journalising means for creating a notification record of a set of e-mail information data for each of the intercepted electronic mails, wherein the users can decide if intercepted electronic mails are to be available for a search query, whereby electronic mails are journalized and shared between a multiple of users; an electronic mail manager database (EMM-DB) for storing said notification records and the associated electronic mails in a relation database so that the notification records and the associated electronic mails are archived and made accessible for the users in the multiple users environment by a search query; a query builder (EQB) for creating predefined and ad-hoc search queries that can be applied/submitted to the EMM-DB, wherein a search query is selecting a user-defined series of information data from the notification records in the electronic mail management database irrespective of recipients or senders of said electronic mails; a query database (QUERY-DB) for storing said predefined and ad-hoc search queries; user access means for providing all users access to queries in the QUERY-DB and electronic mails in the EMM-DB, whereby the electronic mails are searchable independent of senders and recipients; and access control means (EAC) for defining user access rights to queries in the QUERY-DB and electronic mails in the EMM-DB.

8. The system according to claim 1 , wherein the specified set of users being subjected to the detection means is all users in the multiple user environment is at least two users.

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1. A computer program product for facilitating memory access, said computer program product comprising: a non-transitory computer readable storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: providing a first partition within a system configuration, the first partition configured to support an operating system (OS) designed for a first address translation architecture, wherein configuration of the first partition to support the OS designed for the first address translation architecture is indicated in configuration information in a configuration data structure, and wherein the first partition is not configured to support an OS designed for a second address translation architecture; providing a second partition within the system configuration, the second partition configured to support the OS designed for the second address translation architecture, wherein configuration of the second partition to support the OS designed for the second address translation architecture is indicated in the configuration information in the configuration data structure, wherein the second partition is not configured to support the OS designed for the first address translation architecture, wherein the first address translation architecture is structurally different from the second address translation architecture; based on obtaining, as part of an address translation request of the first partition or second partition, an address for translation, determining, based on the configuration information in the configuration data structure, an address translation architecture to use to translate the address; and translating the address via the determined address translation architecture.

12. The computer program product of claim 1 , wherein the configuration data structure indicates at least one of a type of address translation structure to be used for host level translations or an indication of whether the first partition is to use a single level translation or a nested level translation.

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6. The computer-implemented method of claim 1 , wherein the first output word hash vector is equal to the first hash vector for the first word.

1. A computer-implemented method for selecting a word, the method comprising: computing, by a server, a word hash vector for each word of a vocabulary; obtaining the word hash vector for each word of the vocabulary; receiving a first sequence of words; generating a first sequence of word hash vectors by obtaining a word hash vector for each word of the first sequence of words; processing the first sequence of word hash vectors with a layer of a neural network language model to compute a first output vector; quantizing the first output vector to obtain a first output word hash vector; determining a distance between the first output word hash vector and a first hash vector for a first word in the vocabulary; selecting the first word from the vocabulary using the distance between the first output word hash vector and the first hash vector for the first word; generating a second sequence of words using the first sequence of words and the first word; generating a second sequence of word hash vectors by obtaining a word hash vector for each word of the second sequence of words; processing the second sequence of word hash vectors with the layer of the neural network language model to compute a second output vector; quantizing the second output vector to obtain a second output word hash vector; determining a distance between the second output word hash vector and a second hash vector of a second word in the vocabulary; and selecting the second word from the vocabulary using the distance between the second output word hash vector and the second hash vector for the second word.

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6. The method of claim 5 , further comprising displaying at least one second converted text chunk to the user.

5. The method of claim 4 , further comprising: receiving a selection of the displayed at least one text chunk from the user; and inserting the displayed at least one text chunk into the electronic document.

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3. The computer-readable recording medium according to claim 2 , wherein, the adding includes, when the overlap table is full, transferring the first hashed data to another overlap table having a larger capacity.

2. The computer-readable recording medium according to claim 1 , wherein the adding includes, when a piece of the first hashed data obtained by N-dimensionally hashing words collides with another, registering the piece of the first hashed data in an overlap table.

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11. A method using electronic computing functionality to provide implicit labels for use in training a statistical tagging model, comprising: identifying, using the electronic computing functionality, items selected by users in association with queries submitted by the users; identifying, using the electronic computing functionality, schema information associated with the items; selecting, using the electronic computing functionality, implicit labels associated with the queries, based on the schema information training a tagging model based, at least in part, on a training set that includes the implicit labels; and using the tagging model to associate terms of an input query with labels to transform the input query to a structured query.

13. The method of claim 11 , wherein the items correspond to network-accessible pages selected by the users.

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3. The system of claim 1 , wherein the update document includes only updated portions for the target document.

1. A system for merging documents comprising: a computer system including at least one processor configured to: receive an update document and a target document, wherein the update document and target document are document instances of a common document schema; determine whether an item of information in the update document is associated with an eligible path of the document schema in a predefined update table; generate, responsive to affirming that the item of information is associated with the eligible path, a specification of an operation by which the item of information is merged into the target document in compliance with the document schema; and apply the specified operation to the target document to produce an updated document in compliance with the document schema.

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45. The system of claim 44 wherein the at least one negation term comprises at least one prefix negation term and at least one suffix negation term.

44. A ranking system comprising: a memory comprising at least one negation term; a processor comprising a document ranking application comprising modules executable by the processor to rank documents retrieved from a data source in response to a search request, the document ranking application comprising: a term frequency module to: query the data source to identify a plurality of documents that each comprises a key term, the key term matching a search term in the search request; and determine a corresponding term frequency value for the key term in each of the plurality of documents, the term frequency value comprising a total number of occurrences of the key term in a particular document; a negation module to: retrieve the at least one negation term from the memory; compare the at least one negation term to other terms included in each document that are within a selected proximity of each occurrence of the key term to determine if each occurrence of the key term has a negative context; determine that the at least one negation term matches another term within the selected proximity of the particular occurrence of the key term according to the at least one negation rule and exclude a particular occurrence of the key term in at least one document for having the negative context; and determine a corresponding term weight value for the key term in each document based on each occurrence of the key term that has not been excluded; a ranking module to determine a corresponding relevancy ranking value for each document based on the corresponding term frequency value and corresponding term weight value; and a user interface module to generate a list of document data for display, the list identifying each document of the plurality of documents in order based on the corresponding relevancy ranking value of each document.

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37. The method of claim 36 , wherein the transforming operation comprises transcoding.

38. The method of claim 37 , wherein the transcoding is performed in accordance with XSL transformation (XSLT) rules.

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22. A non-transitory computer-readable storage medium having executable instructions stored thereon, wherein the executable instructions, when executed by a processor, cause the processor to: access a structured document comprising content stored according to an underlying structure, wherein the underlying structure comprises a plurality of blocks arranged in a hierarchical relationship, and wherein one or more of the plurality of blocks comprise one or more inline elements; display a What-You-See-Is-What-You-Get (WYSIWYG) editor that comprises the content and receives user input for editing the content; graphically represent the underlying structure of the content in a grid by displaying a vertical pane on a vertical side of the WYSIWYG editor, wherein the vertical pane comprises a representation for each of the plurality of blocks and graphically represents the hierarchical relationship between the plurality of blocks, and wherein each representation of one of the plurality of blocks is located in the vertical pane on the vertical side of the WYSIWYG editor at a position corresponding to a vertical position of a portion of the content in the WYSIWYG editor corresponding to the block, receiving a selection of one of the plurality of blocks, and displaying a horizontal pane that is horizontal to the WYSIWYG editor, wherein the horizontal pane comprises a representation of inline elements within the selected block, and wherein each representation of an inline element is located in the horizontal pane at a position corresponding to a horizontal position of a portion of the content in the WYSIWYG editor corresponding to the inline element; receive a user input on the selected block; in response to the user input on the selected block, display editing options applicable to the selected block; receive a user input selecting one of the displayed editing options; in response to the user input selecting the displayed editing option, apply the selected editing option to the selected block; and update one or more of the displayed content in the WYSIWYG editor, representations of the plurality of blocks in the vertical pane, and representations of inline elements in the horizontal pane to reflect the application of the selected editing option to the selected block.

23. The non-transitory computer-readable storage medium of claim 22 , wherein the executable instructions further cause the processor to, when a selection of a portion of the content, displayed in the WYSIWYG editor and corresponding to an inline element, is received, highlight a representation of the corresponding inline element in the horizontal pane.

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2. A method as set forth in claim 1 wherein the step of inputting includes a step of inputting one or more undesirable software entity signatures, each of the one or more undesirable software entity signatures including at least one portion of the undesirable software entity, the at least one portion including a sequence of bytes that is unlikely to vary from a first instance of the undesirable software entity to a second instance of the undesirable software entity.

1. A method for operating a digital data processor to obtain one or more valid signatures of an undesirable software entity, the digital data processor including a memory that is bidirectionally coupled to the digital data processor, the method comprising the steps of: storing in the memory a corpus of computer programs that are representative of computer programs that are likely to be infected by an undesirable software entity; inputting to the digital data processor at least one portion of the undesirable software entity, the at least one portion including a sequence of bytes of the undesirable software entity that are likely to remain substantially invariant from a first instance of the undesirable software entity to a second instance of the undesirable software entity; storing the at least one inputted portion in the memory; selecting at least one candidate signature of the undesirable software entity from the stored at least one portion of the undesirable software entity; constructing with the digital data processor a list of unique n-grams from the sequence of bytes, each of the unique n-grams being comprised of from one to a chosen maximal number of sequential bytes (B) of the sequence of bytes, the constructed list of unique n-grams being stored in the memory; for each of the unique n-grams of the stored list, estimating with the digital data processor a probability of an occurrence of the unique n-gram within sequences of bytes obtained from the stored corpus of computer programs; for each candidate signature that is comprised of one or more of the unique n-grams, estimating with the digital data processor a false-positive probability of an occurrence of the candidate signature within the sequences of bytes obtained from the corpus of computer programs; comparing the estimated false-positive probabilities of the candidate signatures with one another and with a set threshold probabilities, the threshold probabilities having values selected to reduce a likelihood of an occurrence of a false positive indication during the use of a signature; and outputting at least one signature for subsequent use in identifying an occurrence of the undesirable software entity or a modified version of the undesirable software entity, the outputted at least one signature being determined to exhibit a false alarm probability that is comparable to or less than a lowest false alarm probability of others of the candidate signatures.

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29. A computer readable storage medium comprising computer-executable instructions tangibly stored thereon, which when executed by a processor, perform a method comprising: receiving a plurality of candidate images; using a learned probabilistic composition model to divide each candidate image in the plurality of candidate images into a most probable rectangular object region and a background region, wherein the most probable rectangular object region has a maximal composition score from possible composition scores computed according to the composition model for possible divisions of the candidate image into object and background regions, each possible composition score is based upon at least one image feature cue computed over the object and background regions, and the composition model is trained on a set of images independent of the plurality of candidate images; ranking the plurality of candidate images according to the maximal composition score of the most probable rectangular object region of each image determined using the learned probabilistic composition model; removing non-discriminative images from the plurality of candidate images; clustering a plurality of highest-ranked images from the plurality of candidate images ranked according to the maximal composition score of the most probable rectangular object region of each image determined using the learned probabilistic composition model to form a plurality of clusters, wherein each cluster includes a plurality of images selected from the plurality of highest-ranked images and having similar object regions according to a feature match score; selecting a representative image from each cluster as an iconic image representative of the object category; and causing display of the iconic image.

31. The computer readable storage medium of claim 29 , wherein the composition model is a Naive Bayes model.

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15. The method of claim 12 , further comprising presenting a pop-up dialog via which a customization to a graphing operation is performed.

12. A computer-implemented method of handling math information in a word processor, comprising acts of: receiving and rendering math-based content in a word processing document; converting the math-based content into converted content having a math markup language format for processing by a math engine; analyzing the converted content by the math engine to produce analyzed content; selecting a mathematical operation and generating a math result using the math engine based on the analyzed content; inserting the math result into the word processing document; and utilizing a computer to execute instructions stored in memory to perform at least one of the acts of receiving, converting, analyzing, selecting, or inserting.

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44. A machine-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 13 .

13. The method of claim 11 , wherein the SQL statement with embedded XML Query operations comprises the second set of one or more operations indicated in an argument of an XMLQuery statement.

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15. The system of claim 12 , wherein the aggregator is further configured to automatically communicate a number of iterations to the number of monitors until no sketch-sets below the first threshold value and above the second threshold value are identified.

12. A system for detecting an anomaly in a network, the system comprising: a number of agents configured to collect flow data from a number of devices; a number of monitors configured to create a number of sketch-sets using the collected flow data; and an aggregator configured to: combine the number of sketch-sets received from the number of monitors into a number of common sketch-sets; identify a first sketch-set among the number of common sketch-sets above a first threshold value as the anomaly; eliminate a second sketch-set among the number of common sketch- sets below a second threshold value; and send a request, to the number of monitors, to create a number of finer sketch-sets for a third sketch-set among the number of common sketch-sets below the first threshold value and above the second threshold value.

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13. A method to manage voice activated threads in a voice activated data packet based computer network environment, comprising: receiving, by a natural language processor component executed by a data processing system, via an interface of the data processing system, data packets comprising a first input audio signal detected by a sensor of a first client computing device; parsing, by the natural language processor component, the first input audio signal to identify a first request and a first trigger keyword corresponding to the first request; generating, by a direct action application programming interface (“API”) of the data processing system, based on the first trigger keyword and in response to the first request, a first action data structure with a parameter defining a first action; receiving, by the natural language processor component, via the interface of the data processing system, data packets comprising a second input audio signal detected by a sensor of a second client computing device, and parsing, by the natural language processor component, the second input audio signal to identify a second request and a second trigger keyword corresponding to the second request; generating, by the direct action API, based on the second trigger keyword and in response to the second request, a second action data structure with a parameter defining a second action; determining, by a pooling component of the data processing system, based on a heuristic technique applied to the parameter of the first action data structure and the parameter of the second action data structure, a pooling parameter that indicates a level of overlap between the first action data structure and the second action data structure, the pooling parameter used to generate a pooled data structure that causes a reduction in processor or bandwidth utilization as compared to separate transmissions of the first action data structure and the second action data structure; generating, based on the pooling parameter, the first action data structure and the second action data structure, the pooled data structure; and transmitting, via a computer network, the pooled data structure to a service provider computing device to cause the service provider computing device to perform an operation defined by the pooled data structure and corresponding to the first action and the second action.

18. The method of claim 13 , comprising: determining the level of overlap between the first action data structure and the second action data structure based on subject matter indicated by the first action data structure and subject matter indicated by the second action data structure.

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1. A prioritization method, comprising: extracting, by a web crawler in a computing system, a set of candidate web pages to be crawled, wherein said computing system comprises a memory unit, and wherein said memory unit comprises said web crawler, said set of candidate web pages, an online analysis software application, an offline analysis software application, a web page score database, and a website score database; simultaneously executing, by said computing system, said online analysis software application and said offline analysis software application in order to simultaneously perform an online analysis and an offline analysis: associating, by said online analysis software application, each web page in said set of candidate web pages with a website in a computer network; determining online, by said online analysis software application that a first website score for said website is not available in said website score database; requesting, by said web crawler, a first sample set of web pages from said website, wherein said first sample set of web pages does not include a total set of web pages from said website; first analyzing offline, by said offline analysis software application, each sample web page of said first sample set of web pages with a plurality of offline heuristics; generating, by said offline analysis software application, a first group of web page scores for each said sample web page of said first sample set of web pages based on results of said first analyzing offline; storing, each said first group of web page scores in said web page score database; determining, by said offline analysis software application, that a number of Web pages in said first sample set of web pages has reached a predetermined threshold; generating, by said offline analysis software application in response to said determining, that said number of Web pages in said first sample set of web pages has reached said predetermined threshold, a first final web page score for each said web page of said first sample set of web pages, wherein each said first final web page score is generated by combining each web page score within each said first group of web page scores; storing, each said first final web page score in said web page score database; generating, by said offline analysis software application in response to said determining online, a first website score for said website, wherein said first website score is generated by combining said first final web page scores for said first sample set of web pages; storing, said first website score in said website score database; associating, by said online analysis software application, said first website score for said website with associated web pages in said set of candidate web pages; prioritizing, said set of candidate web pages with respect to a first associated website score for each web page in said candidate set of web pages; retrieving, by said web crawler, first content from said candidate web pages using said prioritizing; extracting, by said online analysis software application, first hyperlinks from said first content; storing said first hyperlinks in said memory unit; determining by said online analysis software application that a specified time period has elapsed since said generating said first website score; requesting, by said web crawler, a second sample set of web pages from said website, wherein said second sample set of web pages does not include a total set of web pages from said website, and wherein said second sample set differs from said first sample set; second analyzing offline, by said offline analysis software application, each sample web page of said second sample set of web pages with said plurality of offline heuristics; generating, by said offline analysis software application, a second group of web page scores for each said sample web page of said second sample set of web pages based on results of said second analyzing offline; storing, each said second group of web page scores in said web page score database; generating, by said offline analysis software application, a second final web page score for each said web page of said second sample set of web pages, wherein each said second final web page score is generated by combining each web page score within each said second group of web page scores; storing, each said second final web page score in said web page score database; generating, by said offline analysis software application, a second website score for said website, wherein said second website score is generated by combining said second final web page scores for said second sample set of web pages; generating, by said online analysis software application, data specifying a date associated with said generating said second website score; storing, said second website score and said data in said website score database; associating, by said online analysis software application, said second website score for said website with said associated web pages in said set of candidate web pages; second prioritizing, said set of candidate web pages with respect to a second associated website score for each web page in said candidate set of web pages; retrieving, by said web crawler, second content from said candidate web pages using said second prioritizing; extracting, by said online analysis software application, second hyperlinks from said second content; and storing said second hyperlinks in said memory unit.

7. The method of claim 1 , wherein said plurality of offline heuristics consists of determining that each said sample Web page of said first sample set of web pages links to a PDF file.

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6. The method of claim 1 , wherein the audio data corresponding to the previously received utterance and audio data corresponding to the subsequently received utterance include an amount of background noise within a same background noise range.

1. A computer-implemented method comprising: receiving, by a computing device that uses voice-based speaker identification, data identifying a user; prompting the user to confirm whether a previously received utterance was properly identified, properly rejected, falsely identified, or falsely rejected using voice-based speaker identification; receiving, from the user, data indicating that the previously received utterance was properly identified, properly rejected, falsely identified, or falsely rejected; and in response to receiving the data indicating that the previously received utterance was properly identified, properly rejected, falsely identified, or falsely rejected, using audio data corresponding to the previously received utterance to perform voice-based speaker identification on subsequently received utterances.

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13. The article of claim 10 , wherein the word matrix comprises a two dimensional array of words, each row storing a plurality of words, with each column of the word matrix storing words of a predetermined type.

14. The article of claim 13 , wherein the word matrix comprises a plurality of blocks, each block having a predetermined number of rows, and at least some blocks of the word matrix have rows that store the same words as rows in other blocks but the position of the rows within each block are randomly different as compared to other blocks.

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2. The system of claim 1 , further comprising an application that provides the query and cursors on the query result utilizing the advanced key.

3. The system of claim 2 , wherein the application is at least one of the following: a client database application; an email client; a file system client; a database application; a pure database application; a web application; and an online catalog that displays data.

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4. The method for forming entailment relations according to claim 1 , wherein a set P of input patterns (p) with N pattern slots (N>1) is provided, and wherein the extracted pattern is added to the pattern set P.

1. A method for forming entailment relations; comprising a) providing to a computer device at least one input pattern (p) with N pattern slots, wherein N is an integer greater than 1, said input pattern (p) expressing a specific semantic relation between N entities that fill the N pattern slots of the input pattern (p) as slot fillers (s 1 , s 2 , . . . , s N ), b) providing to the computer device at least one cluster (c) of articles, said articles of said cluster (c) relating to a common main topic; c) processing, by the computer device, said articles with respect to the input pattern (p) and identifying identities of said articles which match a semantic type of the N pattern slots; d) based on determining that said at least one input pattern matches a portion of at least one of said articles of said at least one cluster (c): i) storing the N slot fillers (s 1 , s 2 , . . . , s N ), which match the slots of the pattern (p), and a cluster identifier I c of the cluster (c) into a first table S, wherein an N-tuple (s 1 , s 2 , . . . , s N ) and the cluster identifier I c of the associated cluster (c) form one element of table S; ii) for each element of table S, identifying, by the computer device, appearances of the slot fillers (s 1 , s 2 , . . . , s N ) in a plurality of articles of the cluster (c) and for each appearance so identified, storing the slot fillers (s 1 , s 2 , . . . , s N ) together with a sentence in which they occur into a second table C 0 ; iii) from the sentences stored in table C 0 , extracting, by the computer device, patterns which span over the corresponding N slot fillers (s 1 , s 2 , . . . , s N ), said extracted pattern expressing a semantic relation between said N slot fillers; and iv) forming, by the computer device, an entailment relation between said extracted patterns and said input pattern.

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17. The method of claim 1 wherein providing includes providing the creative responsive to a received request for a creative to fill a slot.

1. A computer-implemented method comprising: identifying, using one or more processors, a creative for processing, the creative including a title portion, a body portion and optionally a reference portion, wherein the title portion constitutes a first line of text, and the body portion includes second and third lines of text; evaluating the body portion including determining when the body portion includes one or more words that can be added to the title portion, wherein evaluating the body portion includes evaluating either or both of the second and the third line of text to identify the one or more words; promoting, using the one or more processors, the one or more words into the title portion; and providing the creative including the title portion with the promoted one or more words.

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4. The computer readable storage medium of claim 3 wherein the set of box elements is embodied as a vector of box elements and further comprising: an integer number of box elements in the DRS indicative of a length of the vector of box elements.

3. The computer readable storage medium of claim 1 and the DRS further comprising: an integer number of boxes in the DRS indicative of a length of the array of boxes.

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8. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, receive queries over information sources; for each of the queries, generate a polynomial by defining each query against the information sources as input parameters in polynomial form; provide irreducible polynomials over a finite field of a degree of orthogonality by factoring polynomials generated from the queries; adjust the degree of orthogonality of the irreducible polynomials to provide adjusted irreducible polynomials, each of which is a signature and corresponds to a signature fragment, such that the signature fragments have overlapping portions; and cause at least in part storage of the signatures or the signature fragments in a signature domain over an information space.

14. An apparatus of claim 8 , wherein the apparatus is further caused to: adjust sizes of the overlapping portions and the signature fragments by adjusting the degree of orthogonality of the irreducible polynomials.

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1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: receive text corresponding to a request of a user; process the text in a first natural language understanding (“NLU”) module to generate a first interpretation of the text, and in a second NLU module to generate a second interpretation of the text, wherein the first NLU module is associated with a first domain, and the second NLU module is associated with a second domain, wherein the first interpretation is associated with a first score indicative of a confidence in the first interpretation, and wherein the second interpretation is associated with a second score indicative of a confidence in the second interpretation; select the first interpretation based at least partly on the first score and the second score; and generate a response based at least partly on the first interpretation.

7. The system of claim 1 , wherein the executable instructions further program the one or more processors to rank the first interpretation and the second interpretation using the first score and the second score, wherein the first interpretation is ranked higher than the second interpretation, and wherein selecting the first interpretation comprises selecting a highest-ranked interpretation of the text.

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1. A method comprising: detecting, via a microphone of an electronic device, an audible speech stream; converting the audible speech stream to text; detecting speech loss in the audible speech stream indicating an inability to complete a thought associated with the audible speech stream; generating a query in response to the detecting the speech loss, wherein the query includes at least a portion of the text; searching a catalog on the electronic device using the query to find related catalog data, wherein the catalog includes one or more of text strings, images, contact information, and global positioning system information associated with the electronic device; and presenting the related catalog data.

9. The method of claim 1 , wherein the related catalog data is presented via a preferred media-type, the preferred media-type indicated via user input.

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16. A data analysis system for performing a data analysis task having an associated analysis context, the system comprising: a processor configured to define the analysis context associated with the data analysis task, wherein data items have a variable relevance in accordance with the context, and wherein data items are grouped together to form logical transactions conducted by a user over a predetermined time period; a network interface configured to receive the logical transactions exchanged over a communication network; the processor configured to define a plurality of logical transactions based on one or more transaction criteria, wherein each logical transaction of the plurality of logical transactions comprise at least two data items of the plurality of data items, process the logical transactions with a set of prioritization rules to generate relevance scores that quantify a relevance of the logical transactions to the analysis context, wherein the relevance scores are assigned according to a common scale, and generate a prioritization of the logical transactions based on the relevance scores.

20. The system of claim 16 further comprising the processor configured to display the prioritization of the logical transactions on a user interface.

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10. The method of claim 1 , wherein, the merging compares lines of the reordering tables sequentially and where two lines match the method includes converting the feature scores in each line into counts, summing counts for each orientation, as well as the total count, and converting the updated counts of the orientations back to scores.

1. A method for updating a reordering model of a statistical machine translation system comprising: at a first time, receiving new training data for retraining an existing statistical machine translation system, the new training data comprising at least one sentence pair, each of the at least one sentence pair comprising a source sentence in a source language and a target sentence in a target language; extracting phrase pairs from the new training data, each phrase pair including a source language phrase and a target language phrase; generating a new reordering file from the extracted phrase pairs, the new reordering file including a set of the phrase pairs extracted from the new training data; updating a reordering model of the existing statistical machine translation system based on the new reordering file, the reordering model including a reordering table, the reordering table comprising phrase pairs and a set of features, the set of features comprising, for each of a set of orientation types, at least one feature which is a function of a count of the orientation type for the respective phrase pair, each phrase pair in the reordering table occurring only once, and wherein the updating of the reordering model includes merging an existing reordering table with the new reordering file or merging the existing reordering table with a new reordering table generated from the new reordering file, the merging including updating feature scores for each of the orientation types for at least some of the phrase pairs based on the counts stored in the existing reordering table; at a second time after the first time, receiving new training data for training the existing statistical machine translation system, the new training data comprising at least one sentence pair, the sentence pair comprising a source sentence in the source language and a target sentence in the target language; and reiterating the extracting of phrase pairs, generating of the new reordering file and the updating the reordering model based on the new training data received at the second time, wherein at least one of the extracting phrase pairs, generating the new reordering file, and updating the reordering model is performed with a computer processor.

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1. A method comprising: receiving, at a network entity, a multimedia message from a sending entity and addressed to one or more recipients, wherein the multimedia message includes media content; determining, by the network entity, whether a recipient rule specified by at least one recipient of the one or more recipients exists; and responsive to a determination that the recipient rule exists, delivering the media content to the at least one recipient of the one or more recipients based upon the recipient rule.

4. The method according to claim 1 , wherein the recipient rule comprises state information based upon a state of the at least one recipient of the one or more recipients.

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10. A method, comprising: receiving, at a speech recognition engine on a client device, content of a first web page in response to a first request at the client device to execute the speech recognition engine, the content of the first web page including text in a first identified language, the first web page being presented to the user on a display screen of the client device; determining, via the speech recognition engine, a set of character indices related to the text of the first web page when the first web page is presented at the client device; mapping, via the speech recognition engine, a first set of spoken words to a set of textual words in the text of the first web page based on the set of character indices related to the text of the first web page, the first set of spoken words being associated with the content of the first web page; sending a signal to cause the client device to visually highlight, on the display screen presenting the first web page, each word from the set of textual words in the text of the first web page when an associated spoken word from the first set of spoken words is output at an audio device associated with the client device; receiving, at the speech recognition engine, content of a second web page in response to a second request at the client device to execute the speech recognition engine, the content of the second web page including text in a second identified language, the second web page being presented on the display screen of the client device; determining, via the speech recognition engine, a set of character indices related to the text of the second web page when the second web page is presented at the client device; mapping, via the speech recognition engine, a second set of spoken words to a set of textual words in the text of the second web page based on the set of character indices related to the text of the second web page, the second set of spoken words being associated with the content of the second web page; and sending a signal to cause the client device to visually highlight, on the display screen presenting the second web page, each word from the set of textual words in the text of the second web page when an associated spoken word from the second set of spoken words is output at the audio device.

12. The method of claim 10 , wherein each character index from the set of character indices related to the text of the first web page is a plain text character index, the method further comprising: defining a data structure configured to map the set of character indices related to the text of the first web page to a set of Document Object Model (DOM) element indices associated with the first web page.

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12. An imaging scanner comprising: an image capturing component configured to sequentially capturing two or more images of a single document; and a processor configured to: identify a first location in a first captured image where information to be decoded is located, analyze each character in the first location, and produce a first string including both a corresponding character and a first confidence value for each character in the first location; determine that a first measurement of the confidence values in the first string is beyond a range associated with a first confidence threshold; identify a second location in a second captured image where information to be decoded is located, analyze each character in the second location, produce a second string including both a corresponding character and a second confidence value for each character in the second location; compare the first confidence value for each character in an identified location in the first string with the second confidence value for the character in the same identified location in the second string; select a character from one of the first string or the second string with a higher confidence value; and produce and output a combined string including the selected characters.

20. The imaging scanner of claim 12 , wherein the processor is configured to determine that a first measurement of the confidence values in the combined string is beyond the range associated with the first confidence threshold, identify a third location in a third captured image where information to be decoded is located, analyze each character in the third location, and produce a third string including a corresponding character and a confidence value for each character in the third location.

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7. The method of claim 6 , further comprising creating a synthetic font library from prototypes corresponding to respective single type characters and each respectively created synthetic ligature.

6. The method of claim 2 , wherein the comparing the plurality of prototypes to the two or more touching characters of the ligature to identify two or more matched prototypes further comprises: identifying two or more type characters corresponding to the two or more touching characters of the ligature; and matching the two or more identified type characters to corresponding prototypes of the plurality of prototypes to identify the two or more matched prototypes.

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8. The system of claim 3 wherein: each optimum set is represented by a corresponding master row having the set of columns from the corresponding initial subset of rows, each corresponding master row comprising a binary vector comprising a binary 1 in particular columns in the set of columns for the corresponding initial subset of rows that are elements of the corresponding optimum set and a binary 0 in other particular columns in the set of columns for the corresponding initial subset of rows that are not elements of the corresponding optimum set; and the division module comprises a thresholding module using a thresholding algorithm to: determine a distance threshold for each corresponding initial subset of rows for distances from each of the one or more text rows in each corresponding initial subset of rows to the corresponding master row; split the one or more text rows in each corresponding initial subset of rows into at least a first group of text rows and a second group of text rows, the first group of text rows comprising first text rows with first distances under the threshold, the second group of text rows comprising either no text rows or second text rows with second distances not under the threshold; and select the first group of text rows to be in the corresponding final subset of rows.

9. The system of claim 8 wherein: the thresholding module determines a final distances vector for each final subset of rows, each final distances vector comprising corresponding first distances of a corresponding first group of text rows; and the confidence factor comprises a confidence factor ratio with at least one member of a another group consisting of: a rows frequency in the numerator and a variance of the first distances of the first group of text rows in the corresponding final distances vector in a denominator, the rows frequency comprising a number of the first text rows in the corresponding final subset of rows; the rows frequency and a master row length in the numerator and the variance and an average of the first distances of the first group of text rows in the corresponding final distances vector in the denominator; and a quantity of a rows frequency cubed multiplied by the master row length in the numerator and another quantity of the variance multiplied by the average of the first distances of the first group of text rows in the corresponding final distances vector plus one in the denominator.

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13. The one or more non-transitory computer-readable media of claim 8 , further comprising instructions to selectively merge a plurality of clusters.

8. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon, wherein when executed by one or more processors, the computer-executable instructions cause the one or more processors to: receive a plurality of content files; determine at least one statistical measure of the content of the plurality of content files: store the at least one statistical measure within a statistics repository for a content of the plurality of content files; determine a number of clusters to be included in a first level of a hierarchy of clusters; assign a plurality of content files to the first level of the hierarchy of clusters based on the at least one statistical measure stored in the statistics repository; generate a first aggregate data file of the content files for each cluster in the first level of the hierarchy of clusters; cluster the aggregate data file to generate a second level of the hierarchy of clusters; aggregate the content files of each cluster; form a third level of the hierarchy of clusters using the aggregated content file: determine a label for each cluster in the hierarchy of clusters based on the at least one statistical measure, which identifies a topic of the content files within the cluster, the topic related to at least one of a problem experienced by a user and a request for assistance in solving the problem; and output a taxonomy based on the determined labels.

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2. A non-transitory computer readable storage medium embodying instructions executable by a processor to perform method steps for providing automated programming assistance for proposing alternative code snippets, the method comprising: maintaining a code repository of code snippets, wherein the code snippets are software program source code; receiving quality scores corresponding to the code snippets; providing automated programming assistance by utilizing the code snippets and associated quality scores, wherein providing automated programming assistance comprises, processing program code input to identify a code pattern, wherein the input program code is a code snippet of software program source code; and retrieving from the code repository at least one different code snippet for replacing the code input, the at least one different code snippet having a code pattern that is similar to an identified code pattern of the input program code and having a higher quality score.

5. The non-transitory computer readable storage medium of claim 2 , wherein processing the program code comprises using one or more predetermined code pattern templates to identify a code pattern in the input program code that matches to a code pattern template.

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12. The system according to claim 11 , wherein the memory storing computer usable program code executed by the central processing unit is further configured to: generate information used by said display to provide a screen image that displays said predetermined graphical template; wherein the analysis of the structure of said predetermined graphical template and identification of at least one content area further comprises code executed by the central processing unit further configured to: generate information used by said display for displaying to a user, a list of content areas determined from analyzing the structure of said predetermined graphical template; and accept selection of said at least one content area of said predetermined graphical template from among the displayed content areas included in the predetermined graphical template.

11. A system to process structured documents, comprising: a computer system having a central processing unit, a memory, a storage device, a display and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the central processing unit to: enable a user to select a predetermined graphical template; analyze the structure of said predetermined graphical template and identify: at least one content area for setting or editing different contents according to documents to which said predetermined template is applied and at least one common area to be used in common among said documents to which said predetermined template is applied; enable a user to select a first structured document that said predetermined graphical template is to be applied to; analyze the structure of said first structured document so as to identify various structural components of said first structured document; enable a user to select at least one content area of said predetermined template; enable a user to select a particular structural component of said first structured document to be inserted into each selected content area of said predetermined template; store in the storage device, an association between template structure information and document structure information for each selected content area and the corresponding selected particular structural component; apply said predetermined structural template to said first structured document so as to insert each said particular structural component into the corresponding selected content area of said predetermined template and to include said at least one common area of said predetermined template into said first structured document; and process a plurality of additional documents so as to: select a next one of said plurality of additional structured documents; analyze the structure of said next one of said plurality of additional structured documents so as to identify various structural components thereof; use the stored associations between template structure information and document structure information to automatically select a similarly situated structural component of said next one of said plurality of additional structured documents to be inserted into each selected content area of said predetermined template; iteratively repeat until insertion is valid from a structural viewpoint for each particular selected structural component: check whether insertion of said particular structural component selected for the corresponding content area of said predetermined template is valid from a structural viewpoint; and expand from said selected particular structural component to select a higher structural component based upon the analysis of said structure of said next one of said plurality of additional structured documents if a check indicates that an insertion into its corresponding content area is invalid from a structural viewpoint; and apply said predetermined structural template to said next one of said plurality of additional structured documents so as to insert each validated structural component into the corresponding selected content area of said predetermined template and to include said at least one common area of said predetermined template into said next one of said plurality of additional structured documents.

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21. A method according to claim 19, further comprising: storing computer display information representing a plurality of computer displays into the presentation space buffer; receiving the presentation space data stream containing the computer display information representing the plurality of computer displays into the display control of the server application framework of the server computer; and converting substantially the entire presentation space data stream containing the computer display information representing the plurality of computer displays into a single markup language document using the host extension of the server application framework of the serve computer.

22. A method according to claim 21, wherein the plurality of computer displays comprises a single session running on the host computer.

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1. A method for providing a natural language voice user interface, comprising: receiving a natural language utterance from an input device associated with a computing device, wherein the natural language utterance relates to navigation, and wherein the computing device is moving; determining a current location and direction of travel of the computing device; selecting, from among a plurality of sets of location-specific grammar information, a set of location-specific grammar information based on proximity between the current location and a location associated with the set of location-specific grammar information and based on whether the direction of travel of the computing device corresponds with movement towards the location associated with the set of location-specific grammar information; generating a recognition grammar with the set of location-specific grammar information; generating one or more interpretations of the natural language utterance using the recognition grammar; identifying, by a navigation agent executing on the computing device, one or more requests in the natural language utterance that relate to navigation from the one or more interpretations of the natural language utterance; and resolving, by the navigation agent executing on the computing device, the one or more requests.

12. The method of claim 1 , wherein the computing device comprises a memory, wherein the generating the recognition grammar comprises retrieving the selected set of location-specific grammar information and storing the selected set in memory, the method further comprising: detecting a change in the current location of the computing device; selecting another set of location-specific grammar information from the plurality of sets of location-specific grammar information based on the change in the current location; and replacing the set of location-specific grammar information in the memory with the another set of location-specific grammar information.

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2. The method of claim 1 , wherein client device comprises one of one of a mobile phone, a smartphone, a laptop, a network, or a tablet PC.

1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, audio data from a client device; determining, by the one or more computers, specific content from captured media that matches the received audio data, wherein the captured media is captured from one or more media sources at a backend system and includes at least one of audio media or audio-video media, and wherein determining the specific content that matches the received audio data includes identifying an advertisement that is (i) included within the captured media and (ii) included within the media programming associated with the received audio data, wherein the captured media comprises a collection of audio fingerprints stored in an audio fingerprint repository, wherein each audio fingerprint is generated from at least a portion of an audio stream extracted from one or more monitored digital television broadcast channels; obtaining, by the one or more computers, additional information associated with the advertisement included within the media programming associated with the received audio data; generating, by the one or more computers, a search query based at least in part on the obtained additional information associated with the advertisement included within the media programming associated with the received audio data; and returning, by the one or more computers, one or more search results to the client device responsive to the search query.

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4. The electronic keyboard entry and display device of claim 2 comprising a text memory and wherein said positioning of said display point in a predetermined manner comprises recalling from said text memory a sequence of commands for moving said display point.

2. The electronic keyboard entry and display device of claim 1 wherein said means for encoding words comprises a keyboard for entering said words into said device.

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1. A device, comprising: a processor; and a memory having instructions stored thereon that, when executed by the processor, cause the processor to perform operations comprising: identifying a sender of a voice message; selecting an abbreviation library associated with the sender of the voice message; producing a text representation of the voice message; and compacting the text representation using the abbreviation library selected to produce a compact text representation, wherein the compact text representation includes an abbreviation from the abbreviation library selected, and an extent to which the voice message is compacted is based on network capacity and a subscriber profile.

2. The device of claim 1 , wherein the extent to which the voice message is compacted is further based on network congestion.

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15. The term-translation-enhanced information-description-providing system of claim 14 wherein the term-translation filter: identifies the term-translation regions within a partially-term-translation-enabled information description; and for each term within each identified term-translation region, determines whether a target-language translation is available for the term, and when a target-language translation is available for the term, electronically marks the term as a translatable term.

16. The term-translation-enhanced information-description-providing system of claim 15 wherein the term-translation filter determines whether a target-language translation is available for the term by comparing the term to a list of terms for which translations are available to the target language obtained from a translation database.

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1. A method of compiling a pattern into a non-deterministic finite automata (NFA) graph, the method comprising: examining the pattern for a plurality of elements and a plurality of node types, each node type corresponding with an element, each element of the pattern to be matched at least zero times, the element representing a character, character class or string; generating a plurality of nodes of the NFA graph, each node of the plurality of nodes configured to match with one of the plurality of elements and store the node type corresponding to the element, a next node address in the NFA graph, a count value, and the element, wherein the next node address and the count value are applicable as a function of the node type stored and wherein the plurality of nodes generated enable a graph walk engine to identify the pattern in a payload with less nodes relative to another NFA graph representing the pattern and employed by the graph walk engine to identify the pattern in the payload.

15. The method of claim 1 , wherein the plurality of node types includes a fixed-variable count node type and the fixed-variable count node type represents a portion of the pattern to match for the element a fixed number of times followed by a variable number of times.

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14. The non-transitory computer-readable storage medium of claim 9 , wherein the operation further comprises: training the first classifier using a set of positive training examples depicting instances of the first classification type; training the second classifier using a set positive training examples depicting instances of the second classification type; providing a first set of negative training examples and a second set of negative training examples to the first and second classifiers, respectively, for classification; for each negative training example incorrectly classified by the first classifier, training the first classifier on the incorrectly classified negative training examples; for each negative training example incorrectly classified by the second classifier, training the second classifier on the incorrectly classified negative training examples.

9. A non-transitory computer-readable storage medium containing a program which, when executed by a processor, performs an operation for analyzing an object being tracked in a sequence of video frames, the operation comprising: receiving a representation of the tracked object, as depicted by a current video frame, of the sequence of video frames; evaluating the representation of the tracked object using at least a first classifier and a second classifier, wherein the first classifier is configured to determine a first classification score indicating whether the tracked object depicts an instance of a first classification type, and wherein the second classifier is configured to determine a second classification score indicating whether the tracked object depicts an instance of a second classification type; determining a final classification value for the tracked object, based on the first and second classification scores; and passing the final classification value for the tracked objects to a machine learning engine configured to identify patterns of behavior engaged in by the tracked object, based at least in part on the final classification value.

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10. A method, comprising: transmitting to a group of users, by a computing device of an unauthorized disclosure identification system, a first document including a data item field, the group of users including a first portion of users including a first plurality of users and a second portion of users including a second plurality of users different from the first plurality of users; receiving, by the computing device of the system and from a first user of the group of users, first user input accessing the first document; providing, by the computing device of the system and to the first user of the group of users, access to the first document and the data item field, the data item field including a first data item, wherein the first data item is a first numerical item that is visible in the first document; receiving, by the computing device of the system and from a second user of the group of users, second user input accessing the first document; providing, by the computing device of the system and to the second user of the group of users, access to the first document and the data item field, the data item field including a second data item different from the first data item, wherein the second data item is a second numerical item that is visible in the first document, wherein alternating users accessing the first document and the data item field access data items in the data item field alternating between the first data item and the second data item, and wherein users accessing the first document with the first data item in the data item field form the first plurality of users forming the first portion of the group of users and users accessing the first document with the second data item in the data item field form the second plurality of users forming the second portion of the group of users; receiving, by the computing device of the system, data identifying a disclosure, the disclosure including one of the first data item and the second data item; responsive to receiving data identifying disclosure of the first data item, identifying, by the computing device of the system, users of the first plurality of users as a potential source of the disclosure; and responsive to receiving data identifying disclosure of the second data item, identifying, by the computing device of the system, the users of the second plurality of users as a potential source of the disclosure.

15. The method of claim 10 , wherein the first plurality of users is approximately one half of the group of users and the second plurality of users is approximately another half of the group of users.

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10. The method of claim 1, wherein said bio-signal is related to the user's emotional state.

1. A method for training a speech recognition system to recognize a user's utterance, comprising the steps of: providing an utterance to the speech recognition system while in a training mode; monitoring a bio-signal derived from the user; and using said bio-signal to identify said utterance for retraining.

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5. The system of claim 4 , wherein the user interaction score is calculated as a function of a quantity of views of the network page.

4. A system, comprising: at least one computing device; a content evaluation application executed in the at least one computing device, the content evaluation application configured to at least: receive from a client computing device over a network, a network request for a network page; associate one of a plurality of user accounts with the network request; retrieve the network page from a network page server over the network; calculate a plurality of component scores for the network page including a user interaction score, wherein the user interaction score is a function of user interaction data, the user interaction data comprising at least data representing previous interactions with the network page by at least one viewer of the network page; determine a plurality of weights to be multiplied to the plurality of component scores from configuration data associated with the user account, each of the plurality of user accounts associated with configuration data; generate a quality score for the network page by applying the plurality of weights specified by the configuration data associated with the user account to the plurality of component scores; encode for rendering by the client computing device a report embodying at least the quality score within a header portion of the network page; determine a dynamic threshold value as a function of aggregate values of quality scores of a plurality of other network pages; and responsive to the quality score falling below the dynamic threshold value, output a one of the plurality of component scores to be improved; and a network page server application executed in the at least one computing device, the network page server application configured to generate search results comprising a list of network pages, wherein the list of network pages is sorted according to respective quality scores associated with the network pages in the list.

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16. The method of claim 10 , further comprising receiving query parameters at query form pages, wherein the query form pages are generated from query form annotations and templates.

10. A computer implemented method to query data modeled by an XML schema, comprising the following steps: using at least one XML data schema describing contents of data to be queried, wherein a collection of data from multiple different databases that are not homogeneous is populated with instances of the at least one XML data schema, wherein the XML data schema is used to generate a query form user interface, wherein the query form user interface comprises an input portion and an output portion; generating query statements in XML Query Language through the use of at least one generator in response to user interaction with the input portion; and invoking from a query assembler to the generator to assemble and submit query requests received at the input portion to the multiple different databases for the execution of the specified query upon the collection of data, wherein a response to the query requests is displayed on the output portion; wherein the input portion of the query form comprises query form controls that are mapped to the XML data schema; wherein a first query form control comprises an instance of a control schema defined by an XML Schema Definition Language file and maps to a specific element of the XML data schema and identifies one or more subquery generators.

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4. The method of claim 1 , further comprising; retrieving metadata corresponding to a search domain; extracting entity names based on the retrieved metadata; determining, for each of the entity names, the entity type and the entity score associated with the entity name; and generating an entity table that includes, for each of the entity names, the entity name and the associated entity type and entity score.

6. The method of claim 4 , further comprising: determining the search domain from a plurality of search domains based on the received search query; and accessing the entity table from a plurality of entity tables based on the determined search domain.

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5. The information displaying apparatus according to claim 1 , further comprising a plural dictionary retrieval setting section to set whether or not to use the sub-dictionary information together with the main dictionary information according to a user operation.

1. An information displaying apparatus comprising: a main dictionary storing section to store main dictionary information in which words to be studied are associated with respective explanation information; a sub-dictionary storing section to store sub-dictionary information in which words to be studied are associated with respective explanation information; a displaying section including a retrieval character input area, a word list displaying area to display word lists of the words to be studied respectively retrieved from the main dictionary information and the sub-dictionary information regarding a retrieval character, and an explanation information displaying area to display respective explanation information of the main dictionary information and the sub-dictionary information regarding words specified from the respective word lists displayed in the word list displaying area; a main word changing section to change a main dictionary specified word by specification of one of the words from the main dictionary word list displayed in the word list displaying area, the specification being made according to a user operation; a sub-dictionary word update displaying section to retrieve the changed main dictionary specified word as a new retrieval character from the sub-dictionary information and to update display of the sub-dictionary word list in the word list displaying area; a sub-word respecifying section to specify a first word in the updated display of the sub-dictionary word list as a sub-dictionary specified word, wherein the first word is the same as the changed main dictionary specified word, and is listed first in the sub-dictionary word list by skipping each word stored only in the sub-dictionary information in the sub-dictionary word list between the word in the sub-dictionary word list corresponding to the main dictionary specified word before the change and the word in the sub-dictionary word list corresponding the main dictionary specified word after the change; and an explanation information update displaying section to update display of the explanation information to display explanation information of the changed main dictionary specified word and explanation information of the sub-dictionary specified word, which is the same as the changed main dictionary specified word and is listed first in the sub-dictionary word list, in the explanation information displaying area.

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1. In a repository environment, a method of providing entities the ability to create, manage, and/or store fine-grained metadata, artifacts, or other software related items of a domain by providing a relational model that stores these items in a way that allows rich querying using database routines and other tools, the method comprising: exposing, via an interface stored in memory of a computer system a set of schema guidelines that describe how software related items of a schematized model of a domain are to be categorized in query tables of a repository, the software related items including both executables and metadata that describes the executables, wherein the set of schema guidelines includes two or more of: naming guidelines; script file guidelines; table guidelines; indexing guidelines; viewing guidelines; procedure and function guidelines; foreign key guidelines; query guidelines; or cursor use guidelines; receiving from one or more entities software related items that are organized according to one or more schema guidelines in the set of schema guidelines, the software related items being received by the repository; and storing the organized software related items into a plurality of query tables of the repository, wherein the organized software related items are stored in rows of the query tables, wherein each row includes a container version ID field storing a container version ID that identifies a container to which the organized software related items stored in the row pertain, and wherein the containers are versioned based on when changes to the organized software related items the containers contain are made.

10. The method of claim 1 , wherein the procedure and function guidelines include one or more of: using updatable view instead of basic database functions; not using schema binding; avoiding cursors; not allowing for change of primary key columns; not altering identity or timestamp columns; or using column lists in insert statements.

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20. The apparatus of claim 19 , wherein said order identifier is configured to use said identified language for determining a rule against which to compare said character data in said document, in order to determine said second order.

19. The apparatus of claim 15 , further comprising a language identifier for identifying at least one language associated with said character data in said document, wherein said language identifier is configured to analyze at least one of: vocabulary associated with said character data; at least one character encoding associated with said character data, and script data associated with a script of said character data.

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4. The method of claim 1 wherein at least one of the one or more inspiration selections is structure selection, the method further comprising: identifying the one or more musical characteristics corresponding to the structure selection, wherein at least one of the one or more musical characteristics correspond to a melody of the musical composition; and loading the one or more musical characteristics into the environment of the reinforcement learning model, wherein the environment generates the plurality of rewards based on the one or more musical characteristics.

1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: configuring a reinforcement learning model based on one or more inspiration selections received from a user, each of the one or more inspiration selections corresponding to one or more musical characteristics, wherein the configuring further comprises: determining one or more emotion characteristics of one or more songs corresponding to at least one of the one or more inspiration selections; displaying one or more emotion objects to the user on a display, each of the one or more emotion objects corresponding to one of the one or more emotion characteristics; receiving at least one emotion object adjustment from the user that adjusts a size of at least one of the one or more emotion objects; adjusting at least one of the one or more musical characteristics based on the emotion object adjustment; and loading the at least one adjusted musical characteristic into an environment in the reinforcement learning model to adjust a reward structure of the environment; performing a plurality of training iterations using the configured reinforcement learning model, wherein the plurality of training iterations generate a plurality of actions and the environment generates a plurality of rewards corresponding to the plurality of actions; and generating a musical composition based on the plurality of actions in response to determining that the plurality of rewards reach an empirical threshold.

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1. A method for making merging decisions for a translation comprising: providing a translated text string in a target language of a source text string in a source language; with a merging system, wherein the merging system is implemented with a computer processor, outputting decisions on merging of pairs of words in the translated text string, the merging system comprising at least one of: a set of stored heuristics comprising at least a first heuristic by which two consecutive words in the string are considered for merging if an observed frequency f 1 of the two consecutive words as a closed compound word is larger than an observed frequency f 2 of the two consecutive words as a bigram, and a merging model trained on features associated with pairs of consecutive tokens of text strings in a training set and predetermined merging decisions for the pairs to predict merging decisions for a new translated text string; and outputting a translation in the target language based on the merging decisions for the translated text string.

2. The method of claim 1 , wherein the merging system comprises the set of heuristics.

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4. The method of claim 1 , wherein each of the first and second Boolean connectors is one of an ‘AND’ operator, or an ‘OR’ operator.

1. A method for programmatically providing a user interface for forming a query, comprising: displaying a first row of query criteria, wherein the query criteria comprises a first operand, a second operand, and a comparative operator for comparing the first operand with the second operand; displaying a second row of query criteria, the second row being logically connected to the first row by a first Boolean connector; displaying a third row of query criteria, the third row being logically connected to the second row by a second Boolean connector; displaying a fourth row of query criteria; displaying the second row and third row together in a bounded area, wherein the bounded area indicates that the second row and the third row are on a child level from the first row, and that the query criteria from the second row and third row will be evaluated together before the query criteria from the first row; in response to a user drag-and-drop operation comprising moving the fourth row within the bounded area, nesting the fourth row of query criteria with the second row and third row of query criteria; and executing a query comprising evaluating the query criteria from the second row, third row, and fourth row together before evaluating the query criteria from the first row, wherein nested query criteria are evaluated before query criteria that are not nested.

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8. The method of claim 1 , wherein the access rules specify the print servers that are allowed to print the document.

1. A method for securely transporting in a networked environment a document to be printed, the method comprising: providing a policy server; wherein a user defines a set of access rules for the document through the policy server; wherein the policy server stores the access rules and a decryption key for the document; wherein the access rules apply to any of: the entire document or individual pages of the document; providing a print server; providing document encryption means for encrypting the document; wherein the encryption means attaches the policy server's name, IP address, or URL address to the document; sending the encrypted document to a receiving user's computer; wherein the receiving user's computer stores the document locally; providing notification means for notifying a receiving user of the existence of the document on the receiving user's computer, and responsive to the receiving user requesting, at a later time than when said document was locally stored, the document be printed, the receiving user's computer retrieving the document from local storage, contacting the policy server, and requesting therefrom the set of access rules and the decryption key for the one document, wherein the policy server references the document, an identifier of the receiving user, and a computer ID of the user's computer to retrieve the decryption key and access rules for the document and wherein the policy server tracks which computers can print the document and which printer that the user's computer is connected to can print the document.

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20. The service of claim 14 wherein packaging comprises structuring the canonicalized format of each occurrence to support hierarchical date querying.

14. A processor-implemented service for searching for all occurrences of a queried date in a plurality of electronic documents, the service comprising: receiving the electronic documents; invoking an autonomic hardware configuration utility, wherein the electronic documents are made available to the autonomic hardware configuration utility for automatically searching for all occurrences of the queried date by: processing each of the electronic documents via extended regular expression matching to generate a canonicalized format of each occurrence of any date in any date format in the document; packaging the canonicalized format of each occurrence to support one or more types of date querying; processing a reconstruction of a span and location of one of the occurrences of the queried date after removal of html tags from crawled html content of one of the electronic documents; and outputting all occurrences of the queried date using the packaged canonicalized format.

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12. The method according to claim 4 , wherein the step of arranging includes inserting a link contained in the content in the first language in the current content in the second language.

18. The method according to claim 12 , wherein the link includes a Universal Resource Locator (URL).

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16. The method of claim 12 , wherein the substitution probability associated with a substitutable term is based on an occurrence frequency of the substitutable term relative to the corresponding term in related documents.

12. A method for processing a search query having at least two search terms for searching for documents, the method comprising: expanding the query selecting one or more substitutable terms for at least one search term in the query; calculating a substitution probability for each substitutable term; for each substitutable term, calculating a co-occurrence probability with each of the remaining search terms in the search query; determining an occurrence probability for each substitutable term; calculating a score based on the combination of the substitution probability, the co-occurrence probability, and occurrence probability; and ranking the documents in an order determined by the score.

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1. A method for crowd sourcing tasks, comprising: identifying, by a computer system, a group of potential candidates for crowd sourcing, wherein each candidate of the group of potential candidates is identified based on the candidate being expected to accept an offer for performance of a certain type of task, the certain type of task being at least performable within a predetermined range of time; receiving, by the computer system, a request to perform a particular task from a requester; determining, by the computer system, if the particular task corresponds to the certain type of task; and transmitting, by the computer system, an offer for performance of the particular task to a subgroup of the group of potential candidates in response to the particular task corresponding to the certain type of task for a target candidate, wherein transmitting the offer for performance of the particular task to the subgroup of the group of potential candidates comprises: determining when any candidates are currently performing the same task or similar task to the particular task, and transmitting the offer for performance of the particular task to the candidates that are currently performing the same task or the similar task; determining when any candidates have a history of completing the same task or the similar task to the particular task faster than other candidates, and transmitting the offer for performance of the particular task to the candidates that have the history of completing the same task or the similar task faster than the other candidates; determining when a particular candidate has completed a specific task, and transmitting the offer for performance of the particular task to the particular candidate in response to the particular candidate having completed the specific task, wherein the specific task is related to the particular task being offered; and determining when any candidates have reached a predefined quota of one of a total time in performing a group of tasks during a set time period or a number of tasks performed during the set time period, and not transmitting an offer for performance of another task to any candidates that have reached the predefined quota until a next set time period, wherein the next set time period is configurable by a user based on a policy.

4. The method of claim 1 , further comprising setting a maximum quota of crowd sourcing tasks for each potential candidate, wherein the maximum quota comprises at least one of a maximum number of the certain type of tasks that are performable within the set time period and maximum time spent performing the certain type of tasks within the set time period.

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18. A non-transitory computer readable storage medium containing instructions that, when executed by a processor cause the processor to perform a method comprising: prerendering a search engine page in a hidden browser instance, such that at least some portion of content of the search engine page other than search results responsive to a search query is rendered; receiving the search query via a text entry field; passing the search query to the search engine page to perform a search using the search query; and merging the prerendered content of the search engine page with display content loaded in an active browser instance to facilitate display of one or more search results responsive to the search query as the one or more search results are received via the search engine.

20. The non-transitory computer readable storage medium of claim 18 , wherein the text entry field determines whether the text entry is a search query or a website address.

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8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: starting an automatic speech recognition session for a phone call initiated from a communication device, wherein the communication device is associated with a plurality of users; identifying a group of speech recognition models comprising a speaker independent model and a speaker dependent model; recognizing an utterance received from a user in the plurality of users using each model in the group of speech recognition models in parallel, to yield recognition results; selecting a dominant speech model from the group of speech recognition models using a heuristic search algorithm based on the recognition results; and continuously using the dominant speech model to recognize speech received from the user for a remainder of the automatic speech recognition session.

14. The system of claim 8 , wherein the dominant speech model is associated with a current location of the communication device for use in future speech dialogs.

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9. A method of communicating between an automatic speech recognition (ASR) enabled telecommunications system and a DTMF-controlled communications system, comprising: (a) establishing communication between the ASR-enabled telecommunications system and the DTMF-controlled communications system; (b) detecting a presence of speech energy at the ASR-enabled telecommunications system from the DTMF-controlled communications system; (c) detecting an absence of the speech energy at the ASR-enabled telecommunications system from the DTMF-controlled communications system; and (d) transmitting at least one DTMF signal from the ASR-enabled telecommunications system to the DTMF-controlled telecommunications system in response to the detected absence of speech energy.

16. The method of claim 9 , wherein a user-supplied telephone number is used to establish communications between the ASR-enabled telecommunications system and the DTMF-controlled communications system.

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17. The computer readable medium of claim 14 , wherein the expanded speech recognizer is configured to recognize one or more of a collection of general grammar terms, a collection of placeholder terms, a collection of proper names, and a collection of voice command terms.

14. A non-transitory computer readable medium storing instructions executable by a data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving audio data that corresponds to an utterance; obtaining a first transcription of the utterance that was generated using a limited speech recognizer, wherein the limited speech recognizer comprises a speech recognizer that includes a language model that is trained over a limited speech recognition vocabulary that includes one or more terms from a voice command grammar, but that includes fewer than all terms of an expanded grammar; obtaining a second transcription of the utterance that was generated using an expanded speech recognizer, wherein the expanded speech recognizer comprises a speech recognizer that includes a language model that is trained over an expanded speech recognition vocabulary that includes all of the terms of the expanded grammar; aligning the first and second transcriptions of the utterance to generate an aligned transcription; and classifying the utterance based at least on a portion of the aligned transcription, as a voice command or a voice query.

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12. The computer program product of claim 11 wherein said translatable information is located at edge nodes of said data tree.

11. The computer program product of claim 10 wherein said data representation is configured into a data tree.

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25. The method of claim 24 , wherein the notification comprises at least one of an email, messaging on a social network, or instant message.

24. The method of claim 1 , wherein providing the list of inquiries to the at least one author of the first file comprises electronically communicating the list of inquires to the at least one author using a notification.