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26. The server of claim 24 , wherein the one or more processors are configured to execute instructions to receive, from the UE, a subset of hypotheses that the UE can use and the and the selected unit sourced hypothesis and the selected unit sourced hypothesis are selected from the subset of hypotheses stored on the UE, where the subset is less than a set of hypotheses stored on the UE.

24. The server of claim 23 , wherein the received information further comprises weights associated with the selected hypothesis for the corresponding modem function.

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2. The computer readable storage medium of claim 1 further comprising executable instructions to resolve a query using the context, wherein the context associates at least two tables specified by the query.

5. The computer readable storage medium of claim 2 further comprising executable instructions to remove any context with mandatory joins excluded by a selected element.

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

14. The method of claim 1 , further comprising: accessing a second single, natural language voice command; determining, from the repository, additional multiple selected operations that correspond to the received second single, natural language voice command; and applying the additional multiple selected operations to the user interface.

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16. A non-transitory computer-readable medium tangibly encoding computer program instructions executable by data processing apparatus to perform operations comprising: providing a plurality of computer-readable master tables, each computer-readable master table associated with a respective business objects data source of a plurality of business objects data sources, each business objects data source stores a plurality of data items; receiving a search query including one or more query terms, each query term represents first metadata included in metadata associated with a plurality of business objects data sources; identifying, for each query term, one or more business objects data sources that are associated with the first metadata by searching a plurality of computer-searchable index documents, each computer-searchable index document references the metadata associated with a respective business objects data sources; identifying, for each query term, the metadata associated with the identified one or more business objects data sources by searching the plurality of computer-readable master tables, wherein the identified metadata associated with the identified one or more business objects data sources includes the first metadata and additional metadata associated with the identified one or more business objects data sources; searching the identified one or more business objects data sources for data items that satisfy the identified metadata; and providing representations of the data items and identified metadata in response to receiving the search query.

17. The medium of claim 16 , the operations further comprising, for each business objects data source, representing a respective plurality of data items stored in a respective business objects data source in a table structure including one or more tables including one or more columns, each column including one or more cells representing the respective plurality of data items.

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10. The method of claim 1 , further comprising analyzing a telephonic communication associated with the electronic customer communication data, wherein analyzing the telephonic voice communication includes: receiving a telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the analyzing of constituent voice data and based on behavioral assessment data for the electronic customer communication data.

1. A method for analyzing electronic customer communication data and generating behavioral assessment data, the method comprising the acts of: receiving electronic customer communication data of two or more types by a contact center, wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, or a social media data stream; identifying a customer associated with the electronic customer communication data received by the contact center; analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; and displaying instructions to a contact center agent via a reporting engine, wherein the instructions are based on the generated behavioral assessment data.

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5. The computing system of claim 4 , the memory further comprises instructions that further configure the computing system to: determine a third plurality of features from the second block, the third plurality of features relating, at least in part, to the second title portion; provide the third plurality of features to a second classifier, the second classifier to identify whether the second block is likely to be where the hypothetical person would begin reading the first electronic document based on the second title portion; and determine, based on a third score output by the second classifier in response to the third plurality of features, that the second block is not likely to be where the hypothetical person would begin reading the first electronic document, wherein the third score is determined prior to the second plurality of features being provided to the first classifier.

6. The computing system of claim 5 , the memory further comprises instructions that further configure the computing system to: process each document in a training set of documents to determine training blocks, each training block constituting a logical entity within the training set; categorize a portion of each training block as being a title portion of the training block; determine a frequency of occurrence of each words appearing in title portions of the training blocks; rank the words based on their frequency of occurrence; and select a set of the words based on their ranking, wherein the instructions to determine the third plurality of features further configure the computing device to: determine which of the words in the set occur in the second title portion and which of the words in the set do not occur in the second title portion, wherein the third plurality of features include an indication of how many of the words in the set do occur in the second title portion, and how many of the words in the set do not occur in the second title portion.

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1. A method for analyzing a probabilistic graphical model, comprising: by a back-end server component, retrieving a logical graph model, the logical graph model having one or more variables wherein each variable is represented as a logical class with attributes, wherein the logical graph model includes variables of the probabilistic graphical model; selecting a variable in the logical graph model and comparing the selected variable to other variables in the logical graph model; generating, for the one or more variables in the logical graph model, a value subclass for each of a variable's scenarios when a user asserts discrete scenarios for the variable; generating, for each variable, index subclasses, each index subclass having at least one attribute comprised of a property and an object, the latter a subclass of an index object class; asserting at least one scenario or factor for the variable; creating edges with labels between the variables of the logical graph model, wherein the labeled edges correspond to influence relationships in the probabilistic graphical model, wherein the labels include “influences” and “influenced by” inverse properties; and creating additional index subclasses for the one or more variables of the logical graph model, wherein the additional index subclasses of the one or more variables are influenced by additional index subclasses of one or more other variables in the probabilistic graphical model; and automatically generating relationships between variables, wherein the back-end server component is configured to interact with a front-end user computing device, the front end user computing device configured to allow a user to employ the logical graph model to create, edit, and browse the assertions and inferences of the probabilistic graphical model.

7. The method of claim 1 further comprising automatically asserting value subclasses for each variable or the index subclass to represent the scenarios for the variable or the index subclass generated by probabilistic inference.

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15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: identifying an acoustic model, wherein the acoustic model is trained on native speech in a target dialect; and replacing a phoneme in the acoustic model with a modified phoneme, wherein the modified phoneme is a weighted sum of plausible phonemes in a lattice of plausible phonemes associated with a class of a speaker.

17. The computer-readable storage device of claim 15 , wherein the native speech represents the class of the speaker.

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12. A character recognition system comprising: a processing unit; memory coupled to the processing unit; a feature extraction module stored in the memory and executable by the processing unit to recognize a handwritten character by using a character recognition model and to extract features from ink data of the handwritten character, the ink data comprising time sequential ink data, and the features being extracted comprising at least one of a tangent feature, a curvature feature, a local length feature, a connection point feature, or an imaginary stroke feature; and an acquisition module that re-samples the time sequential ink data to convert the time sequential ink data into uniform sampled data, the sampled data enabling the character recognition model to perform character recognition independent of a speed of writing the handwritten character.

13. The system as recited in claim 12 , further comprising: an acquisition module that uniformly samples the ink data; and a frame module that analyzes the features of the ink data by breaking the ink data into a plurality of frames.

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1. A non-transitory computer-usable storage media having machine-readable instructions stored thereon to cause a processor to perform a method, the method comprising: generating a concatenated set of input relations, comprising: sorting each input relation of a set of input relations in order from a first input relation of the set of input relations to a last input relation of the set of input relations, wherein each input relation of the set of input relations comprises a group of tuples; and concatenating the input relations of the set of input relations such that all of the tuples of a second input relation of the set of input relations follow all of the tuples of the first input relation in the concatenated set of input relations, and all of the tuples of each subsequent input relation follow all of the tuples of all preceding input relations in the concatenated set of input relations; and querying the concatenated set of input relations, comprising: performing a query operation on the first input relation of the set of input relations; storing data of the first input relation in the query operation; resetting the query operation; and performing a second query operation on the second input relation of the set of input relations.

6. The non-transitory computer-usable storage media of claim 1 , wherein the machine-readable instructions stored thereon further cause a processor to store data of the first input relation in a cache.

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13. A server for determining a type of landing page to which to transfer web searchers that enter a particular query, each query related to a landing page that links from an advertisement, the server comprising: a landing page classifier to extract content of each of a plurality of landing pages to be classified, the content comprising words of the landing page; extract text from the content; establish a feature space based on the extracted text, representing the extracted landing page; reduce the feature space by applying a supervised attribute selection technique; and conduct classification training with a computer under a machine learning model using a learning algorithm; and classify a target landing page as one of a plurality of landing page classes; a query classifier coupled with the landing page classifier to determine characteristics of one or more query such that the one or more query is associated with the target landing page based on the class of the landing page being related to the characteristics of the one or more query; and a processor coupled with the landing page and query classifiers to choose whether to retain or to change classification of the target landing page associated with the one or more query based on relative average conversion rates of advertisements on a plurality of previously-classified landing pages when associated with the characteristics of the one or more query, wherein the previously-classified landing pages are different than the landing page, and wherein relative average conversion rates comprise average conversion rates that result for respective classified type of landing page over a period of time.

15. The server of claim 13 , wherein the processor observes particular characteristics on the target landing page to distinguish among the plurality of landing page classes, the server further comprising: an extractor to extract particular words within the text of each target landing page to be correlated as features with the plurality of landing page classes.

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38. The storage medium of claim 33 , wherein the interface mechanism is an Application Program Interface (API) running in the external environment.

39. The storage medium of claim 38 , wherein a function in the late bound environment is called from within the external program environment using the API.

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6. The system of claim 1 , the node summary function allows a user or system to sort a sequence of selected nodes or sort sequences of sub-nodes.

1. A programming language system, comprising a processor that executes the following computer-executable components: a query component to interact with hierarchical node-based data collections; and a language extension component to augment the query component to facilitate interactions with the node-based data collections, the language extension component supplies functions to filter the data collections at a granular level, re-shape the data collections, sort the data collections, and extend the data collections with computed nodes, wherein the functions include an extended sub-node predicate function, an advanced projection function, a computed node function, a node grouping function, a node summary function, and a result sorting function.

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8. An apparatus for validating a data structure, comprising: a processor comprising a central processing unit; a mapping component that executes operations on the processor for identifying an equivalent data structure in a second programming language, in response to the mapping component identifying a data structure in a first programming language; a comparing component for comparing a data definition of the data structure with a data definition of the equivalent data structure; a determining component for determining whether there is an incompatibility between a compared data definition of the data structure and a compared data definition of the equivalent data structure by analyzing characteristics of all data fields in a generated assembler data structure of the first programming language corresponding to the data structure in the first programming language and corresponding data fields in a generated assembler data structure of the second programming language corresponding to the equivalent data structure in the second programming language, wherein the generated assembler data structures of the first and the second programming languages are allocated in memory; responsive to determining an incompatibility between the generated assembler data structure of the first programming language and the generated assembler data structure of the second programming language, generating an alert and communicating the alert to a mitigation component to identify a rule which defines an action to be taken in order to correct the incompatibility, wherein a messaging component and a rendering component reports the action to a user via a graphical user interface; and responsive to determining a compatibility between the generated assembler data structure of the first programming language and the generated assembler data structure of the second programming language, generating a message that the data structure in the first programming language and the equivalent data structure in the second programming language are synchronized, and communicating the message to the messaging component to display via the graphical user interface.

10. An apparatus as claimed in claim 8 , wherein the mapping component identifies whether the equivalent data structure performs an equivalent function as the identified data structure.

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5. The method of claim 1 , wherein the computing subset of the identified sequences comprises: for each of the identified sequences, defining the identified sequence as a series of nodes, each node representing a state of the sequence for a page of a plurality of consecutive pages, each node comprising a term or a hole, wherein a hole identifies the page as lacking a term of the sequence; selecting a subset of identified sequences based on assigned scores of nodes of the subset of identified sequences which cover at best the entire document, the assigned score of each node of the selected sequences being a function of at least one of: whether the node comprises a hole or a term, a number of terms in the sequence, and a coverage of the sequence.

1. A method for detection of page numbers in a document comprising: identifying a plurality of text fragments associated with a plurality of pages of a single document; from the identified text fragments, identifying at least one sequence, each identified sequence comprising a plurality of terms, each term derived from a text fragment selected from the plurality text fragments, the terms of a sequence complying with at least one predefined numbering scheme which defines a form and an incremental state of the terms in a sequence, the at least one numbering scheme excluding terms from a sequence which do not comply with an incremental state in which terms on each two consecutive pages vary by a constant value, the identifying of the at least one sequence comprising, for each page of a plurality of pages of the document in sequence: identifying text fragments which comprise a term that complies with the form of the predefined numbering scheme; for each of the identified fragments, determining if the term of the identified fragment complies with an incremental state accepted by an existing sequence and if so, adding the term to that sequence, the existing sequence comprising at least one term derived from a text fragment of a previous page of the document; and for each of the terms which do not comply with an incremental state accepted by an existing sequence, considering the term as a potential start of a new sequence; with a computer processor, computing a subset of the identified sequences which cover at least some of the pages of the document, wherein the computing of the set of sequences comprises applying a Viterbi algorithm to the identified sequences to identify a subset of the identified sequences; and construing of at least some of the terms of the subset of the identified sequences as page numbers of pages of the document.

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5. The voice access system of claim 2 , wherein said voice recognition client is configured to convert voice waveform data into text data.

6. The voice access system of claim 5 , wherein said voice recognition client comprises a voice recognition server; and said voice recognition client is configured to submit voice waveform data to said voice recognition server, convert said voice waveform data into text data using said voice recognition server, and make said text data available to said voice recognition client.

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11. The display device of claim 10 , wherein the processor is configured to determine whether the at least one query word matches the query term based on at least one of pronunciation patterns of the user and context information of the media data.

12. The display device of claim 11 , wherein the context information comprises at least one of title information, genre information, character information, scene information, schedule information, audio related information, and image related information of the media data.

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23. The method of claim 22 , wherein the step of performing the third specified action comprises indicating that the message has a first quality, where the first quality indicates that the message is not estimated as valid and the message is not indicated as invalid.

22. The method of claim 17 , wherein the method further comprises the step of: when the reputation score is better than the first predefined threshold and worse than the second predefined threshold, performing a third specified action.

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1. A computer-implemented method comprising: receiving, from a user, an utterance that was spoken while focus is set on a field of a form; determining, from among one or more different field types, a field type associated with the field; determining, from among different, predefined levels of speech recognition accuracy and from among different, predefined levels of speech recognition latency, a predefined level of speech recognition accuracy and a predefined level of speech recognition latency that are indicated as acceptable for the field type; selecting, based at least on the predefined level of speech recognition accuracy and a predefined level of speech recognition latency that are indicated as acceptable for the field type, (i) one or more accent libraries that each include phonemes for different pronunciations for words of a language and (ii) a level of correction for a speech recognition system to apply to a transcription; obtaining, from the speech recognition system, the transcription of the utterance that is generated by the speech recognition system; and providing the transcription of the utterance in the field of the form.

5. The method of claim 1 , wherein the speech recognition system generates the transcription of the utterance without accessing a linguistic library.

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17. The system of claim 16 , wherein meta-model elements specifying a collaborative transaction type relative to a particular dimensionality each comprise one or more of the following: a structure of the transaction; data elements associated with the transaction; a state model describing a life cycle of the transaction; access that a role type has to data elements of the transaction relative to a state of the transaction; actions that a role type can execute on the transaction relative to a state of the transaction; and whether the transaction is a system of record or whether synchronization must occur with another system of record.

16. The system of claim 14 , wherein the meta-model elements within the negotiated meta-model comprise one or more of the following: one or more role types; one or more dimensions each comprising a supply chain element; one or more dimensionalities each comprising a combination of supply chain elements; access of one or more role types to one or more particular dimensionalities; one or more collaborative transaction types relative to one or more particular dimensionalities; one or more shared operations visible to the trading partners; and one or more temporal structures of collaborative transactions to be executed based on the negotiated meta-model.

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13. The machine readable storage device of claim 12 , further comprising a routine set of instructions for causing the machine to further perform the step of pre-processing said application input before forwarding said received application input to the designated external application.

12. A machine readable storage device having stored thereon a computer program for integrating dynamically produced application input and output into instant messaging/chat content in an established instant messaging/chat session, the computer program comprising a routine set of instructions which when executed by a machine cause the machine to perform the steps of: receiving application input from a remote instant messaging/chat client as a posting to the established instant messaging/chat session between instant messaging/chat clients, the application input is an application command distinguishable from conversational text; forwarding said received application input to a designated external application; receiving application output from said designated external application via a second remote instant messaging/chat client as content in said established instant messaging/chat session; determining in said established instant messaging/chat session which instant messaging/chat clients participating in said established instant messaging/chat session process said application output in a native data format and which of said instant messaging/chat clients process said application output only as a session processible textual representation; converting said application output to said session processible textual representation for said instant messaging/chat clients determined to process said application output only as a session processible textual representation, while forwarding said application output in said native data format to instant messaging/chat clients determined to process said application output in a native data format; and, posting said converted application output as content in said established instant messaging/chat session for instant message/chat clients determined to process said application output only as a session processible textual representation.

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16. The system of claim 10 , wherein the at least one processor is further configured to iteratively process the one or more groups until at least one of: each of the one or more undefined references is defined; and each of the one or more groups is used to identify the one or more undefined references and the one or more undefined references remains undefined.

10. A system for defining and processing hardware description language (HDL) groups for use with an electronic circuit design to be fabricated comprising: a computing device having at least one processor configured to map one or more tool-specific objects into a group graph having one or more groups arranged as nodes in the group graph, wherein the group graph is configured as a data structure, wherein each of the one or more groups includes at least one sub-group, library information, and HDL design information, generate a search order associated with each of the one or more groups within the group graph and wherein the search order is determined, based upon, at least in part, a command line structure, wherein the search order associated with each of the one or more groups is based upon, at least in part, a hierarchical design configuration of the group graph, identify one or more undefined references from within a first group of the one or more groups within the group graph, bind one or more defined references from within the first group to one or more electronic circuit design components, and identify the one or more undefined references from within a second group of the one or more groups within the group graph, wherein the second group is selected based upon, at least in part, the one or more undefined references and the search order associated with the first group of the one or more groups.

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12. The system of claim 10 , wherein the one or more computers are further configured to: for each given aspect of the one or more aspects of the identified region of interest, generate a physical vector representing that given aspect; and generate a new entry in the second storage system for the image based on the identified region of interest and any generated physical vector.

15. The system of claim 12 , wherein the one or more computers are further configured to: receive a search request identifying a true object from a user; query the second storage system to identify the new entry based on the search request; and after querying the second storage system, provide the image to the requesting user.

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11. A system comprising: a processor; and a memory, wherein the processor and the memory are configured to perform operations comprising: accepting a setting for a filter, the filter setting representing a type of information to be included in a list of object descriptions, the type corresponding to at least one of an end-user version of a software documentation or a technical version of the software documentation; accepting a setting for a flag of an object, the flag setting representing a category of documentation relevance for the object stored in a repository, the flag setting corresponding to at least one of a first indication that the object is relevant for the end-user version of the software documentation or a second indication that the object is relevant for the technical version of the software documentation, a third indication that the object is conditional upon the acceptance of another object for inclusion in the software documentation, and a fourth indication that the object is always relevant to generation of the software documentation; comparing the filter setting with the flag setting of the object to determine whether the object is to be included in the software documentation; extracting a description of the object from the repository, when the comparing indicates a match between the filter setting and the flag setting; and generating the list of object descriptions, the list including the description of the object; and generating the software documentation from the generated list of object description.

15. The system of claim 11 , wherein the accepting the setting for the filter further comprises: receiving, from a user interface, a selection of the filter setting.

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11. The device of claim 1 , wherein the domain-specific language model represents a user reject list of at least some of the first recognition results.

1. A communication device comprising: a language input device configured to detect a first language signal associated with a first language; and a recognition and interpretation engine coupled with the language input device and configured to: obtain the first language signal from the language input device; generate a first recognition result set from the first language signal according to at least one of a grammar and statistical language model of the first language, said language model comprising a mobile interference model; generate an improved recognition result set from the first recognition result set by rescoring the first recognition result set according to a domain-specific language model; generate at least one interpretation result from the improved recognition results set; map the at least one interpretation result to a second language representation of a second language; and cause an output device to present an output interpretation according to the second language derived from the second language representation.

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15. The computing device of claim 14 , wherein the second distance threshold is based on a determination of a longest head-modifier dependency distance observed in training data.

14. The computing device of claim 12 , wherein the operations further include pruning the outer arcs to exclude arcs representing possible head-modifier dependency between words in the sentence separated by a distance greater than a second distance threshold before pruning the index set based on the augmented vine parsing algorithm.

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26. One or more non-transitory computer readable storage media storing computer-executable instructions for performing a computer process, the computer process comprising: receiving a request by a client device to access a first content that is not available from a first Web domain; identifying at least one interest keyword based on a combination of keywords that yield search results including the first Web domain and a user's clickstream data responsive to the search results; classifying the first content that is not available based on the at least one interest keyword; identifying a second web domain based on historical relevance data and the classification of the first content that is not available, the historical relevance data including one or more previous attempts to access the first Web domain and session data representing activity performed with respect to the first Web domain; and providing the user access to second content similar to the first content from the second Web domain using the identified at least one keyword.

28. The one or more computer readable storage media of claim 26 , wherein the second content of the second Web domain includes an advertisement that is determined to be relevant to the at least one interest keyword.

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16. The method according to claim 10 , wherein said two-dimensional query language is Language integrated Query (“LINQ”), said multi-dimensional query language is Multi-Dimensional eXpressions (“MDX”) and wherein said converting comprises: placing a Measure Property from a SELECT clause of said two-dimensional query into an ON COLUMNS axis of said multi-dimensional query and associating said Measure Property with a position of said Measure Property in said SELECT clause; and, placing a Dimensional Property from said SELECT clause into an ON ROWS axis of said multi-dimensional query and associating said Dimensional Property with a position of said Dimensional Property in said SELECT clause.

17. The method according to claim 16 further comprising: placing a plurality of Measure Properties from said SELECT clause of said two-dimensional query into said ON COLUMNS axis of said multi-dimensional query and associating said plurality of Measure Properties with a plurality of respective positions of said plurality of Measure Properties in said SELECT clause; and, placing a plurality of Dimensional Properties from said SELECT clause of said two-dimensional query into said ON ROWS axis of said multi-dimensional query and associating said plurality of Dimensional Properties with a plurality of respective positions of said plurality of Dimensional Properties in said SELECT clause.

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3. The method of claim 2 , wherein the XML encoded escape sequence is “&” and the corresponding escaped character for “&” is “&”.

2. The method of claim 1 , wherein the non-URL escape sequence comprises an XML encoded escape sequence.

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12. The computer-usable medium of claim 7 wherein the first computer language is C, and the exportable representation is an XML document.

7. A computer-usable storage medium having computer-readable program code embodied therein configured to cause a computer system to: extract, with a preprocessor in the computer system, macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define a proper CLI syntax for CLI commands input to a CLI prompt and include parse nodes used by the CLI parser to analyze whether one or more CLI commands input to the CLI prompt have proper CLI syntax, and wherein the macroinstructions are written according to a first computer system language; convert, with the preprocessor, the macroinstructions into at least one parse graph having an Extensible Markup Language (XML) format, wherein the computer system is configured to convert the macroinstructions by encapsulating the parse nodes of the macroinstructions with XML tags and by stitching together the encapsulated parse nodes of the macroinstructions to generate the parse graph, and wherein the first computer system language is different than an Extensible Markup Language (XML) language associated with the parse graph; and generate, with the preprocessor, an exportable representation of the at least one parse graph and output the exportable representation of the at least one parse graph from the computer system.

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20. The method of claim 17 further comprising comparing the probabilities of the first and second particular transitions with a third particular transition in a third reading order.

17. The method of claim 7 comprising: wherein applying the decision combiner includes: scoring a first particular transition between an N body text region in a first reading order alternative and a hypothetical sequential M body text region in the first reading order alternative based on the text flow analysis in terms of probability; scoring a second particular transition between the N body text region in a second reading order alternative and a hypothetical sequential P body text region in the second reading order alternative based on the text flow analysis in terms of probability; comparing probabilities of the first and second particular transitions; and choosing and storing the particular transition with a higher probability score as part of a determined reading order in an article of the document.

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7. The method of claim 1 , wherein the electronic signature is integrated into the at least one preliminarily compiled electronic document and comprises a handwritten signature.

1. A method, implemented at least in party by a computer system, of facilitating a closing of a real estate transaction, comprising: receiving first real estate transaction information for a first real estate transaction; wherein the first real estate transaction information comprises information identifying a first party to the transaction and information identifying a property of the first real estate transaction; storing the first real estate transaction information in a memory; preliminarily compiling one or more electronic documents with at least some of the first real estate transaction information; outputting for review by the first party, the one or more preliminarily compiled electronic documents; receiving an electronic signature indicating approval of at least one of the preliminarily compiled electronic documents by the first party; maintaining one or more financing terms associated with a loan to be obtained at the closing of the first real estate transaction; receiving a digital image of at least one ancillary document; and outputting electronic closing documents for the first real estate transaction that comprise: said digital image of at least one ancillary document; said at least one preliminary compiled electronic document with an electronic signature; and one or more documents sufficient to contractually bind the first party to the first real estate transaction.

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2. The method of claim 1 , further comprising: storing, by the computing device, a service pack in a service pack store, the service pack including at least one route and at least one service worker module; and deploying, by the computing device, the service pack by distributing the at least one service worker module to multiple locations to form the plurality of service worker modules, each at a respective one of the locations, and storing the routes within at least one router, wherein the request is distributed based on the routes to the service worker modules at the multiple locations.

1. A computer-based method of processing data, comprising: receiving, by a computing device, a plurality of requests; distributing, by the computing device, each request to a plurality of service worker modules; determining, by the computing device, a plurality of answers, each answer being determined by the service worker module based on the request; receiving, by the computing device, the answers from the service worker module; providing, by the computing device, an output that that is based on at least one of the answers; collecting, by the computing device, observed cluster resources; determining, by the computing device, a load due to the plurality of requests based at least in part on the observed cluster resources; calculating, by the computing device, an optimal cluster layout; and adjusting, by the computing device, a number of service worker module, the number being adjusted based on the optimal cluster layout; wherein the determination of the load includes: recording, by the computing device, statistics of processing of the requests; determining, by the computing device, a distributed node status from a distributed node status store; and collecting, by the computing device, cluster resources based on the statistics and distributed node status and wherein the calculation of the optimal cluster layout includes: calculating, by the computing device, an optimal cluster layout based on the cluster resources; and updating, by the computing device, a distributed configuration store with new instance counts for services based on the optimal cluster layout in, the number of service worker modules being adjusted based on the new instance counts for services.

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15. The method of claim 14 , wherein the activity associated with the listing is selected from a group of activities consisting of voting for the listing, voting against the listing, posting a comment for the listing, bidding on the item described by the listing, buying the item described by the listing, submitting a winning bid for the listing, and posting the listing to the first network-based marketplace.

14. The method of claim 11 , wherein the activity comprises an activity associated with a listing that describes an item for sale on the first network-based marketplace and wherein the listing is selected from a group of listings consisting of a listing for a good and a listing for a service.

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13. A non-transitory computer readable medium comprising computer readable program code embodied therein for converting an original file to a page description language (PDL) format, the computer readable program code: obtains an original file comprising a graphics object delimited by a tag, wherein the tag specifies a type of the graphics object and a formatting attribute of the graphics object; translates the graphics object in the original file into an image based on the type and formatting attribute in the tag; generates object composition metadata for the graphics object based on a composition rule corresponding to the tag, wherein the object composition metadata comprises a description of the graphics object in the original file; adds the image to a visible layer of the PDL file; adds the object composition metadata comprising the description to an invisible layer of PDL file, wherein the image in the visible layer and the description in the invisible layer overlap, wherein the object composition metadata is searchable in the PDL file but is not visible when the PDL file is displayed, and wherein the PDL file does not have the tag; receives a search request specifying the description of the graphics object; identifies, in response to the search request, a location of the description in the invisible layer of the PDL file; and displays a portion of the visible layer comprising the image in response to the portion of the visible layer overlapping the location.

16. The non-transitory computer readable medium of claim 13 , wherein the invisible layer comprising the object composition metadata is above the visible layer comprising the image.

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4. A method of processing as defined in claim 1 which comprises utilizing a natural language speech recognition processor which provides alternate natural language speech recognitions to provide electronically encoded data which is representative of said natural language.

1. A method of processing natural language in an apparatus, which comprises steps: providing natural language which is processed by said apparatus to provide electronically encoded data which is representative of said natural language, providing a dictionary data base in memory associated with said apparatus wherein said dictionary data base contains a plurality of entries which are comprised of one or more of syntax usage data, associated word sense numbers with associated state representation data, and/or function codes, lexically processing said electronically encoded data to access said dictionary data base with said apparatus, providing a natural language plausibility and expectedness processor in said apparatus, utilizing said natural language plausibility and expectedness processor to initiate accessing entries of said dictionary data base which are associated with words of said natural language.

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8. The system of claim 1 , the set of query clauses is not required to include an explicit termination query clause.

1. A computer-implemented system that facilitates query comprehensions, comprising: a processor; and a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions configured to implement the query comprehension system including: a comprehension component that manages a scope of a control variable; and a transformation component that receives from a user a query that includes initialization data and a set of query clauses in a sequence characterized by a query expression, wherein the user can perform at least the following: input new control variables into the received user-inputted query, the control variables comprising unique local variables that are configured to represent a property or column of an individual data row in a collection as the user-inputted query evaluates, hide existing control variables in the user-inputted query that are determined to be out of scope when the hidden variables are no longer part of the user-inputted query, reveal hidden variables that are determined to be in scope when the previously hidden variables are now part of the user-inputted query and implement the existing control variables in a different syntactical order than that in which the new control variables were inputted in the user-inputted query, wherein the control variable of the user inputted query have no syntactical order restriction, and wherein: the initialization data includes a control variable and at least one of a collection or an expression; the transformation component resolves values of the control variable in scope for each query clause, and based upon a type of each query clause, respectively; the transformation component operates on each query clause in a manner that is independent of an ordering of the sequence; and the transformation component outputs the results of the transformation performed on the collection or expression based upon the query expression and based on the number of control variables in scope, wherein the format in which the results are output is variable depending on the number of control variables in scope.

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1. A user interface for providing orientation information about a topic, the user interface comprising: color-based indicators arranged on a display, a color of each of the color-based indicators reflecting a measure of a respective orientation derived from a corresponding block of text about the topic, wherein different colors reflect different measures of orientation; and a selecting device for selecting one of the color-based indicators to cause display of at least a portion of the corresponding block of text.

5. A personal digital assistant comprising a user interface according to claim 1 .

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3. The method of claim 1 , further comprising instantiating sentences based on data from the domain according to the sentence template.

7. The method of claim 3 , further comprising indexing the instantiated sentences to enable contextual searches.

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8. The method of claim 2 , further comprising: optimizing the generated code.

2. The method of claim 1 , wherein generating the representation code comprises: for each page in the report, and for each respective object in the page, generating instructions of the different language that describe the respective object.

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7. The method of claim 1 further comprising: identifying a particular Internet domain name as a legitimate Internet domain name based on its being historically observed to be safe.

1. A method comprising: identifying by a network node a particular Internet domain name as a legitimate Internet domain name based on its being tested as safe; determining by the network node, using a first regular expression for identifying the legitimate Internet domain name, whether a domain name of a uniform resource locator associated with network traffic matches a legitimate Internet domain name of a target organization; classifying network traffic containing the uniform resource locator as legitimate if the uniform resource locator's domain name matches the legitimate Internet domain name; adding the domain name of the uniform resource locator associated with network traffic to a set of legitimate Internet domain names; if the uniform resource locator is not classified as legitimate, quantifying by the network node how closely the uniform resource locator matches a second regular expression for identifying an unacceptable uniform resource locator of the target organization, the second regular expression different from the first regular expression; and performing a function when network traffic that is not classified as legitimate matches the second regular expression for identifying an unacceptable uniform resource locator with a matching score greater than a first predetermined threshold, the function comprising delaying the network traffic from reaching its destination and transmitting an indication that the network traffic contains a uniform resource locator which may be an unacceptable uniform resource locator, wherein the particular Internet domain name is tested by the network node as being safe by analyzing a structure of a web page associated with the particular Internet domain name, the structure of the web page analyzed by analyzing a domain that is pointed to by a uniform resource locator embedded in the web page, and wherein the particular Internet domain name comprises a domain name registered to an approved advertising organization designated as approved by a representative of the target organization and an end user.

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20. The computer system of claim 16 , wherein identifying within each document of a plurality of open documents, by a computing device, content corresponding to a particular subject matter category includes searching one or both of text and graphical elements of the additional document for content.

16. A computer system for identifying content in a document, the computer system comprising: one or more computer processors; a computer readable storage medium that is not a signal; the computer readable storage medium including program instructions that when executed by the one or more computer processors cause the computer system to carry out the steps of: identifying within each document of a plurality of open documents, by a computing device, content corresponding to a particular subject matter category; in response to the computing device opening an additional document, identifying within the additional document, by the computer device, additional content corresponding to the particular subject matter category; providing, within the additional document, an indicator that visually distinguishes the identified additional content from the other content within the additional document; in response to the computing device opening a second additional document and content of the second additional document not corresponding to the particular subject matter category, determining a new subject matter category corresponding to the content of the second additional document; determining a majority of the plurality of open documents of the computing device relate to similar subject matter, wherein the particular subject matter category relates to the similar subject matter; in response to determining that the majority of the plurality of open documents of the computing device relate to the similar subject matter, assigning a weight to the similar subject matter and the new subject matter category, wherein the similar subject matter is more heavily weighted than the new subject matter category; and providing indicators that visually distinguish documents relating to the similar subject matter category from documents relating to the new subject matter category.

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5. The system as claimed in claim 3 , wherein to query said lexical knowledge database to obtain said at least one replacement term, said processor device is configured to apply a Generalized Frame Model to obtain said at least one replacement term.

3. The system as claimed in claim 1 , wherein said processor device is further configured to: substitute at least one of said replacement terms with a generalized type information term using a database of entity type knowledge.

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15. The method according to claim 2 , further comprising: in the aggregating step, aggregating annotations by category contexts such that an annotation corresponds to a category context if it contains the keywords of the category context; determining category contexts that have a predefined minimum number of unique user identifiers and a predefined minimum number of unique item identifiers in their aggregated annotations; and clustering items and users simultaneously by category context such that the unique user identifiers for a determined category context is identified as a cluster of users and the unique item identifiers for the same determined category context is identified as a cluster of items.

17. The method according to claim 15 , further comprising: associating an advertisement with a determined category context; and delivering the advertisement to at least one of the relevant users.

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60. The method of claim 59 , wherein the retrieved said unknown selection is represented by a code, and wherein said method further comprising inserting said code into said electronic document.

59. The method of claim 12 , wherein said menu of choices further comprising an unknown selection, and wherein said method further comprising retrieving said unknown selection where said unknown selection is selected, whereby said unknown selection establishes that a classification for said at least one informational portion is not known and will need further consideration at a later time.

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4. The method of claim 1 , wherein the query comprises a weight associated with at least one of the at least two key terms.

5. The method of claim 4 , wherein determining the relevance score comprises: determining at least one group of key terms, wherein a key term in the at least one group appears in the at least one interaction, and the key term is connected to another key term in the at least one group if the key term and the other key term appear in one constraint complied with by the interaction; determining a score for the at least one group as a function of weights associated with key terms that belong to the at least one group; and determining the relevance score as a maximal relevance score associated with any group of the at least one group.

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33. The method of claim 32 , wherein the ontology source further describes a relationship between concepts in the set of normalized concepts.

32. The method of claim 1 , wherein the ontology source describes a relationship between the keyword and the set of normalized concepts.

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7. A system for managing an object database for objects comprising: a computer system with at least one processor and memory; a query manager executing in the memory of the computer system for receiving an database path query expression comprising a main query expression and a treat-as query expression; a query translator executing in the memory of the computer system for forming an object query from the path query; a query engine executing in the memory of the computer system for querying the object database using the object query; and wherein the query translator comprises: node generator for breaking the path query into nodes; a node processor for examining each node to indicate main query objects from the main query expression and treat-as query objects from the trea-as query expression; a tracker for consolidating main query objects for selection into a SELECT clause and for consolidating main query objects from which selection is made into a FROM clause; a sub-tracker for consolidating sub-query objects for selection from each node into a SELECT clause and for consolidating sub-query objects from which selection is made into a FROM clause; and a query register and generator for forming the object query from the SELECT clause; from the FROM clause; and from a WHERE clause wherein the WHERE clause consists of the sub-SELECT clause and the sub-FROM clause and a sub-WHERE clause that links the scope of the sub-SELECT clause to the scope of the SELECT clause.

11. The system according to claim 7 wherein access control to objects within the object database is controlled by the object database.

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8. The computer storage medium of claim 6 , the operations further comprising: receiving, at the computing device, a selection of a link associated with the identification of one of the other users; and filtering the search results to include a subset of the search results based on the selected other user.

6. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at a computing device, a search query from a first user, the first user associated with a computer-implemented social graph that includes a plurality of members socially connected to the first user through the computer-implemented social graph; receiving, at the computing device, search results responsive to the search query, the search results each associated with a respective electronic document stored in one or more computer-readable storage media; determining that a particular electronic document is associated with a plurality of endorsements; identifying a subset of members of the plurality of members socially connected to the first user through the computer-implemented social graph, each member of the subset of members respectively associated with an endorsement of the plurality of endorsements; identifying an affinity of each member of the subset of the members with respect to the particular electronic document; selecting a subset of the plurality of endorsements based on the affinity of each member of the subset of the members with respect to the particular electronic document; and transmitting instructions to display the search results to the first user, the instructions comprising instructions to display one or more endorsement annotations associated with the subset of the plurality of endorsements proximate to the search result associated with the particular electronic document, the one or more endorsement annotations each including a text snippet describing the endorsement associated with the endorsement annotation, the text snippet including i) an identification of the respective member of the subset of members, ii) text indicating a service used by the respective member of the subset of members to generate the endorsement, and iii) a web-based link associated with the endorsement to direct the first user to the content of the endorsement within the service, wherein the text indicating the service used by the respective member of the subset of members to generate the endorsement is distinct from the web-based link.

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9. A computer implemented method comprising the following computer executable acts: employing a processor to execute computer executable instructions stored on a computer readable storage medium to implement the following acts: receiving a structured query language (SQL) statement, wherein the SQL statement includes actual grammar associated with the SQL statement and explicit user specified parameters; separating the explicit user specified parameters from the actual grammar associated with the SQL statement; and mitigating parsing errors by replacing the explicit user specified parameters with fuzz values created within an SQL server, wherein the fuzz values created within the SQL server maintain conformance to syntactically correct SQL statements.

10. The computer implemented method of claim 9 further comprising performing fuzzing at deeper levels than the network protocol layer.

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14. The schedule management method according to claim 12 , further comprising analyzing conversation to determine whether there is a schedule to be recommended to the user by the robot itself; and comparing a reasoning weight of the schedule to be recommended with a reference value to determine whether reasoning is performed based on the determination that the schedule to be recommended exists.

15. The schedule management method according to claim 14 , wherein the reasoning weight is updated using the information collected by the interactive robot.

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1. A printer for printing data comprising: a. a memory; and b. at least one processor executing a plurality of programmatic instructions wherein, upon execution, said programmatic instructions: i. perform a first analysis of said data to identify a page description language; and ii. if no page description language is identified by said first analysis, perform a plurality of additional processing activities and wherein said plurality of additional processing activities is performed concurrent with a second analysis of said data to identify a page description language.

4. The printer of claim 1 wherein if the page description language is identified by said first analysis, said second analysis is not performed.

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11. The non-transitory, computer-readable medium of claim 8 , wherein the pairing token is generated by the remote service and is used to identify a thread of communications.

13. The non-transitory, computer-readable medium of claim 11 , the instructions executable by the processor to configure the joining device to: receive a successful pair message from the remote service, the successful pair message indicating that: the joining device has been authenticated to the remote service within an expected period of time; and the remote service has added the joining device to a list of devices paired with an account that is associated with a structure in which the joining device is to be added.

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4. A logic analyzer according to claim 1 further comprising a central processing unit and firmware stored in a read-only memory coupled to said memory circuits, said word recognizers, and said counter for controlling said first and second logic analyzer sections.

1. A multi-speed logic analyzer, comprising: first and second logic analyzer sections each including a memory circuit to store input data and a word recognizer to detect a predetermined word from said input data for controlling said memory circuit; and a counter to count a clock signal in accordance with the outputs from said word recognizers of said first and second logic analyzer sections, wherein said counter starts to count when said word recognizer of said first logic analyzer section detects a first predetermined word and stops counting when said word recognizer of said second logic analyzer section detects a second predetermined word; wherein clock signals for said first and second logic analyzer sections are different from each other.

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1. A computer implemented method for a voice-enabled computing environment comprising: receiving a voice command related to an abstraction at at least one computer of the voice-enabled computing environment, wherein the voice command specifies an abstraction type; determining, from the voice command, which of a plurality of abstraction types supported by the voice-enabled computing environment is the abstraction type specified by the voice command, wherein each of the plurality of abstraction types is associated with an indication of whether any particular sequencing and/or timing is to be imposed; and responsive to the voice command, performing at least one programmatic action related to the abstraction, wherein the programmatic action is specific to the abstraction type specified by the voice command.

2. The method of claim 1 , wherein the voice command is a record command for recording a new abstraction, wherein abstraction types able to be specified by the voice command comprise a script, a macro, and a collection, wherein a script is an abstraction including timing data for at least one included action that indicates an amount of time before the at least one included action is performed, wherein a macro is an abstraction having sequentially ordered actions, and wherein a collection is an abstraction in which no order or timing of included actions is defined.

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18. The system of claim 16 , wherein the document index is configured to store keyword-based classification information about the search results.

16. The system of claim 13 , wherein the search server is in communication with a document index, and the document index associates search results in the document index having a known subject-version association with a subject-version tag indicative of the subject-version of the search result.

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6. The method for enhanced tuning of search engine parameters to obtain optimal search result of claim 1 , wherein presenting the search result is based on the adjusted relevancy score of each of the result objects and the weighting factor associated with each of the tunable knobs such that the most significant result objects are presented at the top of the search result.

1. A method for enhanced tuning of search engine parameters to obtain at least one optimal search result, comprising: receiving a search parameter at a search engine equipped with a plurality of tunable knobs set at an initial setting; generating a search result for the search parameter based on the received search parameter and the initial setting of the plurality of tunable knobs, the search result including a plurality of result objects, each of the plurality of tunable knobs associated with a weighting factor; associating a relevancy score for each of the plurality of result objects generated by the search engine, the relevancy score associated with a tunable knob setting; presenting the result objects from the search result; identifying one or more of the presented result objects not selected over time, the non-selection of the result objects identifying the associated tunable knob settings; dynamically adjusting the relevancy score of the identified one or more result objects not selected over time; tuning the plurality of tunable knobs using one or more search algorithms to obtain an optimal search result, the tuning allowing adjustment of the tunable knobs based on the adjusted relevancy score and the non-selected result objects over time, wherein the relevancy score and the non-selected result objects identify the one or more tunable knob settings to be adjusted for obtaining an optimal search result; and further dynamically adjusting the previously dynamically adjusted one or more result objects not selected.

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16. The method of claim 10 , comprising: presenting a user interface including the sub-scenes in ark order in which they were produced; receiving a discard selection from a user for a sub-scene; and discarding the sub-scene from a video summarization.

10. A method of automatic summarization carry out by machine: obtaining a video; generating a semantic model of the video from frames of the video; assigning respective relevancy scores to the frames; initializing the semantic model with the respective relevancy scores including constructing a graph in which nodes correspond to the frames, node values correspond to respective relevancy scores of the frames, and edges are weighted by the inverse distance between frames established in the semantic model: and iteratively processing the semantic model to produce a set of sub-scenes, each iteration comprising: converging the semantic model following initialization; selecting a sequence of frames with a highest relevancy score after converging; and re-initializing the semantic model by fixing the relevancy scores for the selected sequence of frames.

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8. A system comprising: one or more computers operable to interact to perform operations comprising: receiving an input string having a plurality of terms, the input string being in a first form, wherein a given sequence of the plurality of terms refers to a geographic feature, wherein the given sequence is annotated with a geographic-feature type selected from a plurality of geographic-feature types each indicating a characteristic of an entity in the physical world corresponding to the geographic feature, and wherein the given sequence is stored in an annotated format with the geographic-feature type in a database of geographic labels prior to receiving the input string; transforming the input string from the first form to a second form, the transforming including: applying one or more rules to the input string to identify one or more terms for translation, the one or more identified terms being fewer than the plurality of terms, wherein at least some of the rules are applied in response to a match between a feature type of the respective rule and the geographic-feature type with which the given sequence is annotated to indicate the characteristic of the corresponding entity in the physical world, translating the identified one or more terms to one or more translated terms in the second form, and transliterating at least some of the remaining terms of the plurality of terms into transliterated terms in the second form, including selecting one or more transliteration rules for application in accordance with the indicated characteristic of the entity, wherein when the given sequence of the plurality of terms is annotated with a first geographic-feature type of the plurality of geographic-feature, a first rule of the one or more rules identifies a specific term in the input string for translation in response to a match between a first feature type of the first rule and the first geographic-feature type, and when the given sequence of the plurality of terms is annotated with a second geographic-feature type of the plurality of geographic-feature types, a second rule of the one or more rules identifies the same specific term in the input string for transliteration in response to a match between a second feature type of the second rule and the second geographic-feature type, wherein the specific term is translated or transliterated to a term having the same grammatical form as the specific term; concatenating at least the translated and transliterated terms to form a hybrid output string in the second form; and storing the hybrid output string in the database of geographic labels; and when map data for a geographic region including the entity is requested for display: (i) retrieving the hybrid output string from the database and (ii) providing, via a network interface, the hybrid output string along with the requested map data for display at a client device.

12. The system of claim 8 , wherein each rule includes a number of respective rule outputs for respective output forms, the respective rule outputs including translated forms of terms identified by the respective rules.

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1. A method comprising: determining, by a computing device, potential members associated with a user based on an electronic mailbox associated with the user; determining a plurality of conversion rates respectively for a plurality of invitations based on a respective number of persons that joined a contact information sharing network after being sent a respective one of the plurality of invitations to join the contact information sharing network; determining, based on the plurality of conversion rates, a highest conversion rate invitation of the plurality of invitations; and sending, to at least a subset of the potential members, the highest conversion rate invitation.

7. The method of claim 1 , wherein the determining the plurality of conversion rates is based on tracking each invitation for a period of time.

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16. The non-transitory computer readable medium according to claim 15 , wherein the instruction of extracting the face data further comprises: weighting the first user attribute recognition result and the second user attribute recognition result to obtain a final user attribute recognition result; and performing a corresponding operation according to the final user attribute recognition result and the content recognition result.

17. The non-transitory computer readable medium according to claim 16 , wherein the instruction of performing the corresponding operation further comprises: determining vocabulary content corresponding to the final user attribute recognition result; and performing a corresponding operation according to the content recognition result and the vocabulary content corresponding to the final user attribute recognition result.

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3. The method of claim 1 , further comprising: detecting as the textual input an incomplete input; and outputting the identified first or second representation of the textual object as both a proposed transliteration of the textual input and a proposed completion of the textual input.

1. A method of enabling text input on a mobile electronic device, the method comprising: detecting on the mobile electronic device an initial input of a textual object comprising a number of characters, each character being of a first type, of a second type, or of both types, the types pertaining to character types; determining whether all of the characters are of the first type, of the second type, or of both types; storing, if it is determined that all of the characters are of the first type, a first representation of the textual object from the initial input as a new entry in a first data source; storing, if it is determined that all of the characters are of the second type, a second representation of the textual object from the initial input as a new entry in a second data source different from the first data source; storing, if it is determined that all of the characters are of both the first type and the second type, the first representation of the textual object in the first data source as a new entry and the second representation of the textual object in the second data source as a new entry; detecting a textual input in one of a first alphabet that can be transliterated into characters of at least the first type and a second alphabet that can be transliterated into characters of at least the second type; when the textual input is in the first alphabet, comparing the textual input with the first data source to identify the first representation of the textual object; when the textual input is in the second alphabet, comparing the textual input with the second data source to identify the second representation of the textual object; and outputting the identified first or second representation of the textual object as a proposed transliteration of the textual input.

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1. A method implemented by a server having a processor executing instructions stored in a computer-readable storage media, the method comprising: receiving, by the server, a request from a mobile device for accessing first content in a first-markup language; determining capabilities of the mobile device for receiving and viewing the first content; processing the first content, by the server, based on the determined capabilities of the mobile device by: identifying certain types of markup tags and scripts in the first content as not meeting a predetermined safety criteria threshold; correcting the first content by removing from the first content the certain types of markup tags and scripts that do not meet the predetermined safety criteria threshold prior to transcoding; transcoding the first content from the first-markup language into a second-markup language that is supported by the determined capabilities of the mobile device; identifying in the first content an original uniform resource locator (URL) reference to second content stored at an external content source, the external content source comprising an external content provider in communication with the server via a network; rewriting the original URL reference in the first content to be directed to a proxy URL of the server to enable the server to act as a proxy to the second content at the external content source; replacing the original URL reference with a proxy URL reference that references the proxy URL in the first content transcoded into the second-markup language; and providing, to the mobile device, the first content transcoded into the second-markup language having the proxy URL reference, so that when the mobile device attempts to access the second content, the mobile device is directed to the server instead of the external content provider.

3. The method as described in claim 1 , further comprising: subsequently receiving, by the server, a request from the mobile device for access to the proxy URL by selection of the proxy URL in the first content; accessing, by the server, the external content source based on the original URL to download the second content from the external content source; and transcoding the second content to the second-markup language for providing transcoded second content to the mobile device.

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12. The method of claim 1 , further comprising receiving the token instances and a baseline value for the user; and generating the samples from the token instances and the baseline value for the user.

1. A method comprising: receiving samples comprising temporal windows of token instances to which a user was exposed; the token instances spread over at least a day, and a subset of the token instances originating from a same source and having overlapping instantiation periods; receiving target values representing affective response annotations of the user in response to the temporal windows of token instances; and training an emotional response predictor on input data comprising: the samples, the corresponding target values, and values indicative of the number of token instances in the temporal windows of token instances; wherein the emotional response predictor utilizes the values indicative of the number of the token instances to compensate for non-linear effects resulting from saturation of the user due to the user being exposed to the token instances in the temporal windows of token instances including the token instances originating from the same source and having overlapping instantiation periods.

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11. The computer system of claim 10 , said performing the first search comprising: sending a first search request for the service description associated with the received service name to the service registry program product; and receiving a null from the service registry program product in response to the first search request, wherein the service registry program product returns the null upon failing to find the service description associated with the received service name.

10. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said computer readable memory unit containing instructions that when executed by the processor implement a method for searching a web service registry system by use of a search controller, said method comprising: said processor performing a first search of a service registry program product with a service name received by the search controller from a user of the web service registry system, wherein the web service registry system comprises a search module and the service registry program product, wherein the search module comprises the search controller, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; after said performing the first search, said processor determining that the received service name does not have a service description associated with the received service name in the service registry program product; said processor coordinating a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and said processor discovering that the service description is associated with the candidate service name within the service registry program product and subsequently returning the discovered service description to the user, said coordinating comprising: determining, from the received service name, a component word list that includes all words constituting the received service name; determining, from the component word list, a respective synonym list for each word in the component word list, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; determining, from the respective synonym list for each word in the component word list, the candidate service name; and sending a second search request for the service description associated with the candidate service name to the service registry program product and subsequently receiving the service description in response to the second search request.

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5. The method of claim 1 , further comprising: creating a new message for further routing based on the result; routing the new message to a destination point, wherein the destination point comprises another topic queue.

1. A method for context based routing of messages, comprising: receiving a message for routing by a message switch implemented in a hardware processor; parsing the message to identify a topic and a data payload of the message; identifying a topic queue to which to route the message based on the topic and the data payload; routing the message to the topic queue; executing automatically a template integration process subscribing to the topic queue, in response to the message being routed to the topic queue, the template integration process comprising a configurable and executable template that provides a service, the template integration process invoking an application service for providing the service, with a request comprising data extracted from the message for the application service to handle the request, the template integration process receiving a result of handling of the service from the application service.

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19. The method of claim 18 , wherein the term vector includes at least 10 terms.

18. The method of claim 16 , wherein the first and second documents have respective first and second document signature data structures, with each document signature data structure including: a temporal component based on a date of publication associated with the document; a length component based on a word count associated with the document; and a term vector based on a fixed number of (top-ranked) inverse-document frequency terms for the document.

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5. The touch-typable device as claimed in claim 3 , wherein said textual input choices chosen from said set of likely and valid input choices are superimposed on said movable keymask based on one or more of physical access of said user to said plurality of cells of said movable keymask, persistence of said textual input choice on said movable keymask, assignment of most likely textual input choices on previously accessed cell, layout of said textual input choices on said text input keypad of said touch-typable device, and nearness to last key used.

3. The touch-typable device as claimed in claim 1 , wherein said touch-typable device includes said display that is a touch-screen, and wherein said desired textual input choices are directly accessible through and dynamically assignable to said plurality of touch-screen enabled cells of said movable keymask.

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

22. The computer-readable medium of claim 18 , wherein the message store is configured to provide for at least one of data insertion and data querying for at least one of entities, concepts, relationships, and metadata associated with the one or more messages.

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19. A method, performed at least partially on a computer, for facilitating on-line communication among multiple instant messaging identities, the method comprising: detecting presence of a target instant messaging identity in a chat room that is accessible over a network of computers to instant messaging identities and who desires interaction with other instant messaging identities who are presently on-line in the chat room; presenting questions to the target instant messaging identity, at least one of the questions including selectable responses associated with the question; receiving, from the target instant messaging identity, responses to the questions; accessing, from computer-accessible memory, stored responses to the questions, at least one of the stored response having been received from another instant messaging identity and being associated with the other instant messaging identity who provided the response; comparing responses received from the target instant messaging identity to the accessed stored responses; identifying, based at least in part on results of the comparison, a group of less than all of instant messaging identities who are currently on-line; and using an instant messaging identity representing an instant messaging robot to introduce the identified group of instant messaging identities who are currently on-line to the target instant messaging identity and to introduce the target instant messaging identity to the identified group of instant messaging identities who are currently on-line.

30. The method of claim 19 further comprising: receiving, from the target instant messaging identity in a later communications session, an indication of an instant messaging identity to be invited to the chat room; enabling transmission of an invitation to the invited instant message participant, wherein the invitation includes a suggested meeting time and a revise control operable to enable the invited instant messaging identity to indicate a different meeting time; receiving an indication of a different meeting time; and communicating the different meeting time to the target instant messaging identity.

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3. The method of claim 1 , further comprising: creating a preferences profile that defines preferred words or phrases for use in prioritizing the one or more candidate words; and prioritizing the one or more candidate words based on the preferences profile.

1. A method of identifying type-ahead candidates, comprising: determining a context of a plurality of past non-threaded emails or documents of a user by analyzing the plurality of past non-threaded emails or documents for words or phrases, wherein the plurality of past non-threaded emails or documents are associated with a software application; generating a context index associating the plurality of the past non-threaded emails or documents of the determined context with corresponding repeatable values within the plurality of past non-threaded emails or documents; receiving one or more characters in a current email or document of the software application; determining a context of the current email or document by analyzing the current email or document for current words or phrases in the current email or document, wherein the context of the current email or document corresponds to the context of past non-threaded emails or documents; determining matches between the current words or phrases and words or phrases of the plurality of past non-threaded emails or documents of the context index; identifying, based on the determined matches, one or more of the corresponding repeatable values; matching the identified corresponding repeatable values with the one or more received characters to identify one or more candidate words; and presenting the one or more candidate words to a user on a computer as type-ahead choices for inclusion in the current email or document.

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20. The non-transitory computer readable storage medium of claim 16 , wherein the transforming comprises: transforming contents of an entity data model extensible markup language (EDMX) file into a first common object model; parsing the first common object model by the graphical model to generate a graphical object model; and based on an execution of the graphical object model, generate an entity-relationship model including the one or more attribute values modified via the text editor interface and the relationships between the modified one or more attribute values, the one or more attributes, and the one or more elements.

16. A non-transitory computer readable storage medium tangibly storing instructions, which when executed by a computer, cause the computer to execute operations, comprising: display contents of a data file as a text-based data object via a text editor interface of an integrated development environment (IDE), the displayed text-based data object including text values of one or more elements, one or more attributes, and one or more attribute values; and in response to detecting an input modifying the one or more attribute values of the text-based data object via the text editor interface, transform the text-based data object into a graphical model including the one or more attributes modified via the text editor interface and visually representing relationships between the modified one or more attribute values, the one or more attributes, and the one or more elements, based on the inputs received in the text editor interface, and displaying the graphical model via a graphical editor interface of the IDE, wherein the displaying of the graphical model comprises simultaneously displaying the graphical editor interface and the text editor interface within a window of the IDE.

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12. A non-transitory computer readable storage medium and one or more computer programs embedded therein the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to: receive a plurality of messages directed to a particular user, each message having a unique message identifier; determining a respective conversation for each of the plurality of messages, each conversation having a respective conversation identifier; wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria; send to a client system for display a first list of conversations including the respective conversation in an order determined in accordance with second predefined criteria, as a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, the sender list configured by the computer system to include only identifiers of senders of messages in the conversation corresponding to the row; enable the particular user to identify one or more conversations in the first list of conversations, and to mark the identified one or more conversations as belonging to a particular category while continuing to display the first list of conversations, which includes the identified one or more conversations; update attributes of the identified one or more conversations to indicate that the identified one or more conversations belong to the particular category; and send to the client system for display a second list of conversations, the second list comprising only conversations marked as belonging to the particular category, wherein a plurality of the conversations listed in the second list each have a plurality of messages, and wherein the second list includes only a single row for each distinct conversation listed in the second list.

14. The non-transitory computer readable storage medium of claim 12 , wherein the second list of conversations is produced by executing a corresponding search query.

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1. A text input method, comprising: predicting candidate words for text input in accordance with a text context; causing a first set of predicted candidate words to be displayed in a spatial arrangement which reflects the selectable directions of a navigational input device, the first set of predicted candidate words comprising at least four candidate words arranged in four different directions reflecting respective selectable directions of the navigational input device, the navigational input device being one of a rocker, a D-Pad or cursor keys; receiving user input in response to actuation, of the navigational input device; and directly selecting a displayed candidate word by toggling the navigational input device in one of the four different directions reflecting the respective selectable directions of the navigational input device.

6. The method of claim 1 , wherein the candidate words are arranged in the spatial arrangement in accordance with their respective prediction relevance for the current text context.

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17. The system of claim 14 , wherein classifying is based upon, at least in part, non-intrusive classification of speech quality.

14. A voicemail to text system configured to perform non-intrusive speech quality detection without a reference signal comprising: one or more processors configured to receive a first speech signal associated with a particular user, the one or more processors further configured to extract one or more short-term features from the first speech signal wherein extracting short-term features includes extracting a time frame of between 10-50 ms, wherein the one or more short term features include a Hilbert envelope based feature and a linear predictive coding residual, the one or more processors further configured to determine one or more statistics of each of the one or more short-term features from the first speech signal, the one or more processors further configured to classify the one or more statistics as belonging to one of a set of quality classes, wherein classifying the one or more statistics includes modeling a speech quality class using a binary tree classifier, the one or more processors further configured to automatically generate at least one training database, based upon, at least in part, the first speech signal and an intrusive speech quality algorithm, wherein the intrusive speech quality algorithm is not used during the receiving, extracting, determining, and classifying operations.

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7. The computer-implemented method of claim 1 , wherein the readable object comprises a document structure or a text document.

8. The computer-implemented method of claim 7 , wherein document attributes are associated to the document structure.

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1. A document management system, the system comprising: a physical-document monitoring device comprising: a document coupling device, a sensor coupled to the document coupling device, the sensor operable to sense a state of a document and to generate a signal representative thereof, and a computer coupled to the sensor and the document coupling device, the computer operable to determine a document state based on the signal.

18. The system of claim 1 , wherein the monitoring device further comprises a user input device coupled to the computer.

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1. A method comprising: entering a source digitized text into a memory of an information technology system; delineating the source digitized text into a plurality of segments by a user; associating a first selection of the segments by the user with a first tag; individually assigning by the user a unique sequence number to each segment of the first selection, whereby each segment of the first selection is associated with a unique sequence number within the first selection; associating a second selection of the segments by the user with a second tag; individually assigning by the user a unique sequence number to each segment of the second selection, whereby each segment of the second selection is associated with a unique sequence number within the second selection; receiving a user command to proceed to thereafter sequentially render segments associated with the first tag; generating a first node record and associating the segments associated with the first tag with the first node record; associating the first node record with at least one other selected segment associated with the second tag when at least one of the segments associated with the first node record shares the second tag; sequentially rendering each segment associated with the first tag node record in accordance with the order of each individually assigned sequence number of each segment of the first selection until the associated selected segment is rendered; receiving a user command to sequentially render segments associated with the second tag; generating a second node record and associating segments associated with the second tag with the second node record; sequentially rendering segments associated with the second node record in accordance with the order of each individually assigned sequence number of each segment of the second selection.

2. The method of claim 1 , wherein the source digitized text is previously generated.

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15. The method of claim 12 , further comprising adding a noise component to each segment in a deterministic way which leads to reduced visibility of the text in each frame, but identifiable by a human user when combined in a frameset and shown as a video CAPTCHA.

12. A method of user verification employing a processor operating to perform actions in response to executing computer program instructions, comprising: receiving an access request; generating, by a nontransitory computer readable medium having stored thereon instructions for generating, one or more video-based automated tests that are based on at least two properties of human vision comprising at least persistence of vision and simultaneous contrast wherein simultaneous contrast comprises enhancement or diminishment, relative to normal, of perception, cognition and related performance as a result of immediately previous or simultaneous exposure to a stimulus of lesser or greater value in the same dimension wherein generating the one or more video-based automated tests further comprises generating a video of a target image comprising text data of one or more of randomly selected letters or meaningful words, segmenting the target image into a grid of segments wherein each segment is of a predetermined size, generating a set of colors for inclusion into the target image in the video, and splitting the grid of segments across a plurality of framesets such that occurrence rates of the positive data comprising the target image or the text data and negative data including the whitespace data is the same; issuing the one or more tests; receiving a response to the one or more tests from the access requestors; and verifying that the access request originated from a human user based at least on the response.

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11. The computer program product as recited in claim 10 , wherein the at least one attribute of the set of attributes is a subsystem attribute.

14. The computer program product as recited in claim 11 , wherein the instruction for presenting further presents an input for a user-supplied attribute not otherwise provided.

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9. The system of claim 8 , wherein the storage format is a platform independent format.

10. The system of claim 9 , wherein the storage format is based at least in part upon extensible hypertext markup language (XHTML).

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1. A method comprising: associating speakers with respective segments of an audio speech file to yield associated speaker segments; generating, via a processor using automatic speech recognition of audio in the audio speech file, expertise vectors for one or more of the speakers, the expertise vectors comprising scores based on: (i) number of times the speakers have spoken about a topic in the audio speech file by searching the associated speaker segments for a term associated with the topic, and (ii) at least one of word classes, usages, styles, or behaviors of the speakers; and ranking the speakers as experts based on the expertise vectors; presenting, by the processor, the ranking of the speakers as experts based on the expertise vectors; tagging the associated speaker segments having the term with keyword tags; and matching a respective segment from the associated speaker segments with a speaker, the respective segment having a keyword tag.

2. The method of claim 1 , further comprising identifying the number of times the speakers have spoken about the topic in the audio speech file by searching the associated speaker segments for a set of terms associated with the topic, wherein terms in the set of terms are scored according to a probability that the terms indicate an expertise in the topic, and wherein a combined score associated with the set of terms indicates the expertise in the topic when a scoring threshold is reached.

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23. The system of claim 22, wherein the client terminal adds global existence nodes to the accessibility graph corresponding to each of the match-set and match nodes of the accessibility graph, connects the global existence nodes in the similar manner as the match-set and match nodes, sets a value of a first global existence node to the value of a corresponding local existence node that corresponds to a match node a match pattern corresponding to a highest level match-set node, sets a value of a second global existence node corresponding to the highest level match-set node to the value of ACC if any of the first global existence node has a value of ACC, sets values of all other global existence nodes to values of global existence nodes of a next higher level in the accessibility graph if a next higher level exists and setting values to NOT-ACC if the next higher level does not exists and the other global existence nodes does not correspond to the highest level match-set node, assigns an ACC value to a match-set node of the match-set nodes if the match-set node is connected to the highest level match-set node in the accessibility graph and if the corresponding global existence node has a value of ACC, otherwise assigning a NOT-ACC value to the match-set node, and assigns an ACC value to a match node or a match-set node that is connected below a match-set node or a match node, respectively that is assigned a value of ACC.

22. The method of claim 21, wherein the client terminal connects all accessibility graphs corresponding to each of the separated portions based on the match-set node graph, a connection being not made if a match node associated with an input node does not correspond to a match-set node associated with a corresponding output node, and if a match-set node associated with an input node does correspond to a match node associated with a corresponding output node.

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7. A non-transitory machine readable medium storing a program for providing navigation on an electronic device comprising a display screen, the program executable by at least one processing unit of the electronic device, the program comprising sets of instructions for: receiving a request to navigate to a destination; identifying a plurality of routes from a current location of the electronic device to the destination based on the received request; when the request is not a verbal request and the device is in an unlocked mode, (i) presenting the plurality of routes to a user to select one of the plurality of routes, (ii) receiving a selection of one of the routes, and (iii) providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route; and when the request is a verbal request and the device is in a locked mode, (i) automatically selecting a single route from the plurality of routes without user input, (ii) displaying a map on the display screen with an overview of the selected route on the map, and (iii) after a predetermined delay and without any additional user input, transitioning from displaying the overview of the selected route to providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route, wherein the route overview comprises the entire selected route from the current location of the device to the destination that is highlighted on the map.

10. The non-transitory machine readable medium of claim 7 , the program further comprising a set of instructions for recognizing verbal requests when a sound level of the verbal request is above a pre-determined threshold.

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15. The system of claim 13, wherein the types of notes comprise to do lists, appointments, reminders, calendar entries, FYIs, action items, or electronic mail messages.

13. The system of claim 10, wherein the key words comprise names of persons, names of projects, times, dates, types of notes.

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5. The method according to claim 1 , wherein the displaying the annotation form comprises the further step of: automatically presenting a GUI presentation consisting of any one of a multi-part form, a field, a widget, a user prompt or a color in the annotation form based on input information, the input information consisting of any one of results of a runtime task initiated by the selecting the annotation form step, content of other annotation fields or characteristics of the displayable electronic document being annotated.

1. A computer implemented method for annotating a displayable electronic document at a graphical user interface (GUI), the displayable electronic document comprising any one of a displayable image or text, the GUI comprising a GUI display, the method comprising the steps of: responsive to a first GUI action, selecting the displayable electronic document to be annotated, the displayable electronic document to be annotated selected from displayable electronic documents stored in a displayable electronic document database; and displaying the displayable electronic image at the GUI display; responsive to a second GUI action, selecting an annotation form from a plurality of annotation forms, the selection based on one or more predetermined parameters, the annotation form comprising one or more user prompts for annotation data; and displaying the selected annotation form at the GUI display, the displayed annotation form comprising one or more user prompts, the user prompts prompting a user for annotation data; responsive to a third user GUI action comprising moving a cursor to a position within the displayed electronic image, selecting the position of the cursor within the displayed image independent of content of the displayable electronic document, creating information associating the annotation form with the selected position of the selected displayable electronic document to be annotated; responsive to an event associated with the annotation form, performing by a computer program, an analytic action on the displayed electronic image by way of a first annotation runtime program, the analytic action analyzing characteristics of the displayed electronic image to produce an analytic result; receiving user provided annotation data associated with one of the one or more of said displayed user prompts; and storing in an annotation database each of the received annotation data, the selected position within the selected displayable electronic document and the produced analytic result; and responsive to a user fourth GUI action subsequent to said storing the annotation data, the user fourth GUI action selecting said position within the selected displayable electronic document, performing the steps comprising: finding in the annotation database, the annotation data; and displaying the found annotation data.

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4. The teaching method as set forth in claim 3 , comprising, after removing the image from the student's view and prior to having the student spell the spelling word without viewing the pictorial image, re-reading the sentence containing the use of the spelling word to the student.

3. The teaching method as set forth in claim 1 , comprising, after having the student spell the spelling word while viewing the image, removing the pictorial image from the student's view and having the student spell the spelling word without viewing the image.