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41. A memory medium for creating a prototype that includes motion control, machine vision, and Data Acquisition (DAQ) functionality, the memory medium comprising program instructions executable to: display a graphical user interface (GUI) that provides access to a set of operations, wherein the set of operations includes one or more motion control operations, one or more machine vision operations, and one or more DAQ operations; create a sequence of operations, wherein creating the sequence comprises including a plurality of operations in the sequence in response to user input selecting each operation in the plurality of operations from the GUI, wherein including the plurality of operations in the sequence in response to the user input selecting each operation in the plurality of operations from the GUI comprises including the plurality of operations in the sequence without receiving user input specifying program code for performing the plurality of operations; wherein the plurality of operations included in the sequence includes at least one motion control operation, at least one machine vision operation, and at least one DAQ operation, wherein at least one of the DAQ operations included in the sequence is operable to control a DAQ measurement device to acquire measurement data of a device under test; wherein the program instructions are further executable to store information representing the sequence of operations in a data structure, wherein the sequence of operations comprises the prototype.

47. The memory medium of claim 41 , wherein the plurality of operations included in the sequence includes a plurality of motion control operations; wherein the program instructions are further executable to interactively display a graph illustrating a spatial trajectory cumulatively performed by the plurality of motion control operations, wherein interactively displaying the graph comprises: for each motion control operation in the plurality of motion control operations included in the sequence, updating the graph in response to including the motion control operation in the sequence in order to visually indicate a change in the spatial trajectory, wherein the change in the spatial trajectory is caused by including the motion control operation in the sequence, wherein updating the graph provides interactive visual feedback to the user indicating the change caused by including the motion control operation in the sequence.

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23. The computer-readable storage medium of claim 14 , additionally comprising instructions which, when executed by the one or more processors, causes the one or more processors to perform: compiling registered XPaths into a tree that represents a structural hierarchy for the registered XPaths.

24. The computer-readable storage medium of claim 23 , wherein the tree that represents a structural hierarchy is a XPath dependency tree that consolidates common elements of registered XPaths.

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1. In a program development environment, a computer implemented method comprising: providing, via a programming language, a language processor with built-in support for a parse tree data structure written in a base language, said parse tree data structure represented as a class, said class being a basis for a plurality of parse tree objects, said parse tree objects including methods that retrieve values for base language objects; defining an assignment function, said assignment function taking a plurality of parse tree structures as arguments; defining said assignment function in more than one class, wherein said assignment function is used to identify in-place operations by examining a type of operator at a root of said parse tree structures; overloading said assignment function based on a context of said base language objects; and calling said assignment function from said language processor to determine a value of at least one assignment within at least one of said base language and a base language extension to said base language.

10. The method of claim 1 wherein said base language is one of C++, JAVA, System-C, VERILOG, Verilog, C#, IDL, MATLAB and a language based on the Net framework.

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5. The information processing apparatus of claim 4 , wherein the CPU is further configured to: determine a portion of the electronic document that includes the at least one selection, based on at least the document information; and obtain the text data corresponding to the at least one selection from within the portion of the electronic document, based on at least the information associated with the at least one selection.

4. The information processing apparatus of claim 3 , wherein: the document information comprises a location of the displayed content within the electronic document.

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2. The method of claim 1 , wherein the help content is help content for assisting a computer user in the use of a computer.

1. A method for providing a customized help service for each of a plurality of applications, comprising: (a) storing a library of selectable transforms; (b) receiving a help request from an application, said request identifying a help collection associated with the application, wherein the help collection comprises a first row group comprising a listing of transforms to execute, said transforms grouped into a plurality of phases comprising at least a structural phase and a presentation phase and a second row group comprising extensibility object information for objects associated with the collection; (c) initializing a help service using the identified help collection; (d) iterating over the plurality of phases, wherein for each of a current phase: (e) setting a current transform to a first transform in the current phase; (f) transforming a help content using the current transform and the extensibility object information, wherein if a transformation request to execute behavior based on a specified object is received, the extensibility object information is consulted to load and execute a corresponding object and return expected data based on a common application programming interface (“API”) defined for the help service; (g) setting the current transform to a next transform; (h) repeating (f)-(g) until all transforms within the current phase have been applied to generate a transformed help content; and (i) rendering the transformed help-content for presentation.

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2. The method of claim 1 , wherein the determining of whether the one or more character changes exist comprises: repeatedly analyzing the first code version and the second code version at increasing levels of granularity for the one or more character changes.

3. The method of claim 2 , wherein a first level of the levels of granularity is a code block, and wherein a second level of the levels of granularity is a code line.

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14. The system of claim 9 , wherein the custom dialog system engine includes an Automatic Speech Recognizer (ASR), a Natural Language Processing (NLP), a dialog manager, and an output renderer.

16. The system of claim 14 , wherein the ASR includes one or more of the following: a pattern-based speech recognizer, a free-dictation recognizer, an address book based recognizer, and a dynamically created recognizer.

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19. The computer-readable storage medium of claim 15 , wherein the instructions contained therein further cause generation of at least one additional aggregated cluster if the additional aggregated cluster satisfies the predetermined combining criterion, the aggregated cluster and the additional aggregated cluster being distinct from one another.

15. A computer-readable storage medium for use in identifying potentially misaligned speech segments from an ordered sequence of speech segments in order to create an accurate speech database for speech synthesis, the computer-readable storage medium encoded with computer instructions for: generating identifying a first cluster comprising at least one speech segment selected from the ordered sequence of speech segments if the at least one speech segment satisfies a predetermined filtering test for a misaligned segment; identifying a second cluster comprising at least one different speech segment selected from the ordered sequence of speech segments if the at least one different speech segment satisfies the predetermined filtering test and if there is at least one intervening speech segment occupying a sequential position between the at least one speech segment and the at least one different speech segment, the intervening speech segment failing to satisfy the predetermined filtering test; and combining the first and second clusters and the at least one intervening speech segment to generate an aggregated cluster if the aggregated cluster satisfies a predetermined combining criterion, the aggregated cluster replacing the first and second clusters.

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13. A method, comprising: analyzing, by a system comprising a processor, a plurality of segments of an audio signal based on a linguistic evaluation and an paralinguistic evaluation; determining, for each segment of the plurality of segments and by the system, an emotional state from among a plurality of emotional states and a confidence score of the emotional state based on the analyzing of the plurality of segments; tracking, by the system, a current emotional state of the audio signal for each of the plurality of segments; and determining, for a particular segment of the plurality of segments and by the system, whether the current emotional state of the audio signal changes to an other emotional state of the plurality of emotional states based on the emotional state of the particular segment and a comparison of the confidence score of the particular segment to a predetermined threshold.

14. The method according to claim 13 , further comprising determining, by the system, that the current emotional state of the audio signal changes to the other emotional state of the plurality of emotional states when the emotional state of the particular segment of the plurality of segments is the other emotional state with the confidence score of the emotional state of the one of the plurality of segments being greater than the predetermined threshold.

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32. The apparatus of claim 31 , wherein said scripts define program logic.

31. An apparatus for dynamically configuring client systems, comprising: a host server; a scripting language; wherein said ,host server compiles scripts written in said scripting language into executable bytecodes; wherein said host server, upon receipt of a request for specific up to date presentation components and/or executable bytecodes from a client system, checks if the client system's original presentation components and/or executable bytecodes have expired, wherein said host server separates response data into one or more raw data components, logic components, and presentation components and places said one or more raw data components into said universal data format; wherein only required elements of said client system in terms of: said one or more raw data components; said one or more logic components; and said one or more presentation components are sent independently by said server proxy client to said client system if the original presentation components and/or executable bytecodes on the client system have expired; wherein logic component updates comprise updates to a common code base that is shared between different client device types and which enables said server proxy client to control a feature set of said client system independently of an implementation supplied by native client code and without modifying said native client code; said apparatus further comprising a virtual machine on said client for interfacing at least said one or more logic components with said client system; wherein a client system executes presentation components and/or executable bytecodes in response to a user's input; wherein said client system maintains state information; and wherein said client system reuses at least a portion of said one or more raw data components for other display purposes.

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4. The method of claim 1 , wherein the processor compares the first set of code statements of the rule to the second set of code statements of the plurality of codes statements of the source code, concurrent with testing of a compiled version of the source code, and wherein a correspondence between a code statement of the compiled version of the source code and a code statement of the source code is determined by use of instrumentation of the plurality of code statements of the source code and instrumentation of the compiled version of the source code.

1. A method for indicating significance of tested code statements, the method comprising: a processor receiving a rule containing a first set of code statements; the processor comparing the first set of code statements of the rule to a plurality of code statements of a source code; the processor, in response to the first set of code statements of the rule matching a second set of code statements of the plurality of code statements of the source code, applying a weight modifier to the rule, wherein applying the weight modifier to the rule assigns a weighted value to the first set of code statements of the rule; the processor, in response to the first set of code statements of the rule matching a third set of code statements of the plurality of code statements of the source code, applying the weight modifier to the rule a second time, wherein the rule includes a first instance of the weighted value and the weight modifier assigns a second instance of the weighted value to the rule; the processor applying a cumulative weight value of the rule to the second set of code statements and the third set of codes statements of the plurality of code statements of the source code, wherein the cumulative weight value indicates a significance of the second set of code statements and the third set of code statements, and is based on accumulated applications of the weighted value to the rule, by the weight modifier; and the processor, in response to receiving a request for a test coverage report, displaying in the test coverage report, the cumulative weight value of the second set of code statements and the third set of code statements, of the plurality of code statements of the source code.

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21. A device as claimed in claim 15 , wherein the first input associated with the first discrete area is detected as finished when an initiation stage of the second input occurs in the second discrete area.

15. An electronic device comprising: a display having a plurality of discrete areas for entering a series of characters; a user input for entering characters via the plurality of discrete areas; a detector for detecting a first input associated with a first one of the plurality of discrete areas, the first input comprises an initiation stage and a composition stage, the composition stage comprising a plurality of drag actions; and a processor for recognizing the first input in the first one of the plurality of discrete areas as a first character input while the detector is operable to detect a second input, in a second one of the plurality of areas, for recognition as a second character input, the recognition of the second character input occurring separately to the recognition of the first character input, the processor further associating one of the plurality of discrete areas with the first input from the position of the initiation stage of the first input and continuing the association when the composition stage of the first input extends outside of the discrete area in which the initiation stage occurred so long as each of the plurality of drag actions is initiated within the discrete area.

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2. The method of claim 1 , wherein, for statements with conditional markers, parsing the partitions further includes skipping imperative statements following conditional markers.

1. A method, comprising: tokenizing, with one or more processing devices, input source text to form a token stream having a plurality of tokens, wherein the input source text is organized in two or more divisions and includes a plurality of statements in a compiled programming language and wherein each token has a location; partitioning, with the one or more processing devices, the token stream into partitions by division and by statement, wherein partitioning by statement includes storing an entry representing each partition in a partition table and wherein partitioning by statement further includes scanning the token stream in reverse starting at a statement end; parsing, with the one or more processing devices, two or more of the partitions in parallel, wherein parsing the partitions in parallel includes building, for each statement partition, an annotated syntax tree (AST) to represent the statement, storing, for each symbol, an entry in a common symbol dictionary, and generating error messages corresponding to syntax errors detected while parsing the partitions; and traversing, with the one or more processing devices, the common symbol dictionary to detect semantic errors; wherein scanning the token stream in reverse includes: determining, for each token, if the current token stream location is a conditional marker and, if the current token stream location is a conditional marker, setting a conditional marker flag; determining, for each token, if the current token stream location is an explicit statement terminator and, if the current token stream location is an explicit statement terminator, storing the current token stream location as a latest end statement location; and determining, for each token, if the current token stream location is a period token and, if the current token stream location is a period token, noting the end of a statement.

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36. The system of claim 34 , wherein said execution module includes a state transition mechanism for synchronizing aggregation boundaries.

34. The system of claim 33 , wherein said execution module marshals said values at aggregation boundaries.

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1. A method for providing audible assistance via a hearing device, the method comprising: receiving data representing a speech signal obtained at a hearing device associated with a user, the speech signal representing an utterance of a speaker; identifying the speaker based on the data representing the speech signal; determining speaker-related information associated with the identified speaker; determining whether or not the user can name the speaker, by determining whether the user has named the speaker; and when it is determined that the user cannot name the speaker, informing the user of the speaker-related information via the hearing device, wherein the informing the user of the speaker-related information via the hearing device includes: informing the user of an identifier of the speaker.

43. The method of claim 1 , wherein the determining whether or not the user can name the speaker includes: when the user does not name the speaker within a predetermined time interval, determining that the user cannot name the speaker.

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8. A program product comprising a computer readable hardware mass storage device storing computer readable program code for implementing a method for launching a target application based on characteristics of a string of characters in a source application, said method comprising: identifying, by a computer processor, predefined data type previously associated with a regular expression matching the string; said processor identifying the target application previously associated with a combination of the identified data type and the source application; and said processor launching the target application with the string as a parameter, wherein said identifying the predefined data type comprises: determining that a first row of a parser table comprises a first regular expression formulating the string, wherein parser table comprises rows which are ordered from a more general regular expression to a more specific regular expression; setting the first regular expression as the regular expression matching the string; resetting the regular expression with a second regular expression upon determining that the second regular expression of a next row of the parser table formulates the string more specifically than the first regular expression; and selecting the predefined data type in the row of the regular expression as the predefined data type of the string, upon performing said resetting for all rows of the parser table.

10. The program product of claim 8 , wherein the identified data type, the source application, the target application, and a usage frequency of the target application are in a record in a launcher table, wherein the launcher table comprises at least one record including the record, each record of the at least one record comprising a respective data type, a respective source application in which a respective string matching the respective data type is selected by a respective user, a respective target application associated with a respective combination of the respective data type and the respective source application, and a respective usage frequency of the respective target application.

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13. A computer-readable storage device encoded with instructions for controlling a computer system to determine a score for a recognition alternative, by a method comprising: receiving a digital ink segment that makes up part of a word; adjusting a score based on output of a shape classifier for a recognition alternative of the digital ink segment; if the digital ink segment is the last segment in a letter, adjusting the score based on the probability that the letter ends in the digital ink segment; if there are more ink segments in the word, adjusting the score based on a bigram probability between the letter and a subsequent letter, the bigram probability selected according to the letter and the subsequent letter from among a set of bigram probabilities computed in advance from a corpora, wherein each bigram probability indicating a probability that two letters appear in succession in a word; and if the digital ink segment is the last segment in the word, providing the score for the recognition alternative by applying a weak-constrained language model that recognizes words not present in a dictionary of words of a currently selected language, the weak-constrained language model comprising probabilities that segments are last segments of letters.

14. The device of claim 13 wherein the method comprises a language model that exhaustively considers each possible letter in a target language.

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13. The system according to claim 12 , wherein, in producing the electronic annotated document, if a preset value is found in a pixel of the annotation object, then corresponding pixel information from the annotation object will be provided to the electronic annotated document.

12. The system according to claim 10 , wherein the embedded information in the annotation object comprises a preset value inserted into one or more separation planes of a pixel value that identifies that pixel as part of the annotation.

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5. The video surveillance system of claim 1 , wherein the processing system is further configured to automatically detect events that involve two or more agents in the video sequence.

1. A video surveillance system, comprising: at least a first video camera configured to capture at least a first video sequence including a plurality of video images; a processing system configured to automatically generate video image descriptive data based on the video images, and, based on the automatically generated video image descriptive data, to automatically detect events that involve at least one agent in the video sequence; a storage system configured to receive and store records of the automatically detected events and to associate the automatically detected events with at least a time associated with the first video sequence; and a text generator configured to automatically generate textual descriptions of the automatically detected events, wherein the storage system is further configured to store the automatically detected events with respective geographical locations in association with each other, the associated geographical location being at least in part based on GPS, Geographic Information Systems (GIS), or map data, and wherein the detected events are events that relate to map data and are based on rules that relate to the map data, such that the text generator generates text that combines the map data with the detected events into a report.

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9. A computer-readable medium having stored thereon instructions that when executed by a processor cause the processor to perform a method, the method comprising: identifying a set of candidate documents from a set of indexed documents by comparing a first set of grams to a second set of grams, the first set of grams being related to a query for documents, the second set of grams being related to indexed documents; selecting a subset of the set of candidate documents to partially reconstruct based on a similarity score; selectively producing a partially reconstructed document from the subset of candidate documents; selectively computing an edit distance between a first string related to the first set of grams and a second string related to the partially reconstructed document; and providing data corresponding to the edit distance.

17. The computer-readable medium of claim 9 , the method comprising: receiving a document to be indexed; computing a set of grams for the document; populating an inverted index with a document identifier and data corresponding to the members of the set of grams; receiving a query; computing the first set of grams from the query; selecting one of a plurality of overlapping matching grams for grams appearing in both the first set of grams and the second set of grams; manipulating one or more of, the first string, and the second string, the manipulating comprising one or more of, aligning the first string and the second string, padding a string, eliminating a character from a string, and replacing a character in a string; producing a ranking of the subset of candidate documents, the ranking being based on a document relevance to the query; and providing data corresponding to the ranking; and where selecting the candidate documents includes searching an inverted index organized with a gram-based key field, where the searching is performed on the gram-based key field using a query gram from the first set of grams, where the inverted index relates grams to documents from which the grams were computed, where the similarity score is computed from one or more of, a number of matches between the first set of grams and the second set of grams, a percentage of matches between the first set of grams and the second set of grams, and a normalized score based on a number of matches between the first set of grams and the second set of grams, and where a gram may include one or more of, a skipping character, a substitution character, and a delimiter character.

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1. A method for matching a test string to a plurality of documents the steps of: converting each of the plurality of documents to a character shape code representation by mapping each character of said documents to one of a plurality of character shape codes, wherein each code of said plurality of said character shape codes represents a partial collection of all characters of said documents, wherein each character of said partial collection shares spatial features related to the x-line and baseline of all characters of said documents; converting the character shape code representation to a reduced binary data string for each of the plurality of documents, wherein the reduced binary data string is less than a binary data string corresponding to the characters of the documents; storing the reduced binary data string for each of the plurality of documents to a database; inputting a test string; converting the test string to the character shape code representation; converting the character shape code representation of the test string to the reduced binary data string; matching the reduced binary data string of the test string to the reduced binary data string of each of the plurality of documents; and outputting a list of matching documents.

2. The document matching method of claim 1, wherein the test string is one of a text string and a text document.

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1. A computer implemented method for reviewing media files within a media file review application, the method comprising: accessing a media file that includes an audio track; analyzing the media file with automated analysis software on one or more computers, wherein the automated analysis software creates one or more automatically-generated annotations related to content in the media file; storing the one or more automatically-generated annotations in a database; presenting the media file for manual review within a media file review application, wherein presenting the media file includes: extracting at least one of the one or more automatically-generated annotations from the database; loading the media file into the media file review application; determining temporal locations of the at least one of the one or more automatically-generated annotations; displaying a vertical time bar in a user interface provided by the media file review and annotation application, the vertical time bar being a temporal representation of the media file and including a time marker indicating a current playback position within the audio track of the media file and further including one or more comment marks representing the temporal locations of at least one of the one or more automatically-generated annotations displayed along the length of the vertical time bar, wherein the positions of the one or more comment marks correspond to the respective temporal locations; displaying, in the user interface, one or more controls that allow a user to add, edit, or remove annotations associated with the media file; and providing one or more navigation controls that allow the user to manipulate a temporal location within the media file, wherein the time marker is linked to the navigation controls; selecting a temporal position within the media file using one of the navigation controls to provide a selected temporal position; determining the one or more comment marks in temporal proximity with the selected temporal position; synchronizing annotations displayed within a comment control window to correspond with the comment marks determined to be in temporal proximity with the selected temporal position; editing an annotation associated with the media file at the selected temporal position to provide an annotation edit; and saving the annotation edit in the database.

4. The method of claim 1 , wherein editing further comprises: receiving an instruction provided by the user to delete an existing annotation of the media file from the media review file; receiving a confirmation to delete the existing annotation; and removing the existing annotation from the media review file.

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12. The method of claim 8 , wherein the keywords comprise words relate to declared interests of the users.

8. A computer-implemented method comprising: obtaining keywords from first user profiles of a first group of users of a social networking system who previously responded positively to an invitation; obtaining keywords from second user profiles of a second group of users of a social networking system who previously responded negatively to the invitation; determining an occurrence of a set of keywords in the first user profiles corresponding to the first group of users; determining an occurrence of the set of keywords in the second user profiles corresponding to the second group of users; selecting one or more of the keywords from the set of keywords based on a comparison of the occurrence of the keywords in the first group of user profiles versus the occurrence of the keyword in the second group of user profiles; and for a subject user of the social networking system not included in the first group of users or the second group of users, predicting a response to the invitation by the subject user based at least in part on whether the selected keywords occur in the user's user profile.

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15. The system of claim 10 , wherein the defining module is further configured for defining one or more intent meta-models corresponding to the at least one requirement, each intent meta-model describing the corresponding at least one requirement.

10. A system for developing a meta-model schema, the meta-model schema being developed for generating one or more software artifacts, the one or more software artifacts being generated for one or more requirements associated with an enterprise process, the system comprising: a. a microprocessor; b. a defining module, the defining module configured for enabling a user to define a plurality of sets of meta-models, each of the sets of meta-models corresponding to at least one requirement and defined based on a predefined ontology, the predefined ontology comprising rules for defining and inter-relating meta-models, and at least one meta-model of a set of meta-models of the plurality of sets of meta-models being defined based on at least one other meta-model of the same set of meta-models, wherein each of the plurality of sets of meta-models comprises (i) one or more intent meta-models, each intent meta-model describing the corresponding requirement, wherein each intent meta-model is defined by a user, (ii) one or more inference meta-models for each intent meta-model, each inference meta-model describing business and technical requirements required for generating at least one software artifact of the one or more software artifacts, the business and technical requirements being determined based on the at least one requirement, each inference meta-model being defined by the user, (iii) a composer meta-model corresponding to the one or more inference meta-models, the composer meta-model defining the relation between the intent meta-model and the corresponding one or more inference meta-models, each composer meta-model being defined by the user, and (iv) a set of abstract meta-models, each abstract meta-model of the set of abstract meta-models being inherited from a predefined set of abstract meta-models while defining at least one of the one or more intent meta-models, at least one of the one or more inference meta-models and at least one composer meta-model; c. a building module, the building module configured for enabling the user to build the meta-model schema by connecting at least one set of meta-models from among the plurality of sets of meta-models to at least one other set of meta-models from among the plurality of sets of meta-models, the connection being based on the relation between the corresponding requirements; and d. calculating a completeness of the meta-model schema, the completeness of the meta-model schema being a function of: (i) a number of intent meta-models defined for the one or more requirements, (ii) a number of inference meta-models defined for each intent meta- model, (iii) a number of composer meta-models defined corresponding to the inference meta-models, and (iv) a number of meta-models of the one or more sets of meta-models that have a reference to at least one other meta-model of the set of meta-models, each reference being defined by the user, wherein the completeness of the meta-model schema is additionally a function of a number of quantifiable requirements among the one or more requirements, and wherein the completeness of the meta-model schema is calculated according to the following formula: SC=(Na/Nb)*(Nc/Nd)*((Ne+Nf−Ng)/(Ne+Nf)), wherein SC is the completeness of the meta-model schema, Na is a number of intent meta-models, Nb is the number of quantifiable requirements, Nc is a number of intent meta-models from which inference meta-models have been defined, Nd is a total number of intent meta-models, Ne is a number of inference meta-models, Nf is a number of composer meta-models, and Ng is a number of meta-models without a reference to other meta-models.

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15. A non-transitory computer-readable medium, comprising instructions executable on a processor, the instructions causing the processor to perform steps of: receiving a request from a client device for a preview of a native document, the preview representing the native document in a file format other than the file format of the native document; inserting, by a document mapping module in the native document prior to rendering a preview, a set of unique links comprising a uniform resource locator (URL) and each unique link associated with a different word in the native document, the native object comprising a renderable portion of the native document; rendering, by a document rendering module, the native document into a preview of the native document and thereby generating a bounding area for each of the unique links in the set of unique links, the bounding area mapping a page and pixel location on the preview to the native object associated with the unique link; and providing the preview to the client device for display.

18. The non-transitory computer-readable medium of claim 15 , wherein the unique links are hyperlinks.

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4. The method of claim 1 , wherein the search comprises an instant search.

1. A computer-implemented method comprising: receiving, by a search system, (i) a pixel map corresponding to one or more characters that have been drawn on a display of a client device and (ii) data identifying one or more other characters that were previously recognized by the search system using one or more other pixel maps; recognizing, by the search system, the one or more characters that correspond to the pixel map based on the received pixel map and the one or more other characters; formulating, by the search system, a search that includes the one or more characters and the one or more other characters as a query term; and communicating, by the search system, (i) one or more search results for the search, (ii) data identifying the one or more characters that correspond to the received pixel map, and (iii) data identifying the one or more other characters to the client device that were previously recognized by the search system using the one or more other pixel maps.

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5. The server according to claim 1 , wherein said databases and modules further comprise a personal emotional code database, said personal emotional code database configured for storing a plurality of the personal emotional codes for a plurality of users; each said personal emotional code corresponding to the emotional code assigned to the cluster to which said user belongs.

1. An emotional profiling server comprising a non-transitory computer-readable storage medium encoded with databases and modules configured to cause a Central Processor Unit (CPU) to execute predetermined steps, wherein said databases and modules further comprise: a) a media survey module configured to deliver at least one multi-media survey form to a plurality of users and to collect at least one answer from each user; said answer reflecting the emotional reflex of the user; b) a survey result database to store a plurality of survey results, each of said survey result comprising said at least one answer; c) a cluster analysis module configured to perform cluster analysis on said survey result database and produce at least one cluster; d) an emotional profile database that stores at least one emotional profile record wherein said media survey module collects and aggregates a plurality of answers from a plurality of users and stores said answers as survey results to said survey result database; wherein said cluster analysis module: i) performs cluster analysis on said aggregated answer to segregate said plurality of users into clusters, each cluster being a user segment, ii assigns an emotional code to said cluster, and iii)) stores said emotional code and other relevant cluster information as an emotional profile record in said emotional profile database.

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5. The speech synthesis system according to claim 4 , wherein: the speech element requesting unit is configured to rearrange the speech element identification information so that the speech element identification information is received by the server device in a different order from the order of arrangement of the speech elements in the speech corresponding to the text, and transmit the rearranged speech element identification information as the speech element request to the server device; the speech element information transmitting unit is configured to transmit speech element information stored in association with the received speech element identification information, in an order of reception of the speech element identification information; the client device further includes a rearrangement-order information storing unit configured to store rearrangement-order information representing a relation between an order of arrangement of the speech element identification information before the speech element identification information is rearranged and an order of arrangement of the speech element identification information after the speech element identification information is rearranged; and the speech synthesizing unit is configured to rearrange the received speech element information based on the stored rearrangement-order information.

4. The speech synthesis system according to claim 1 , wherein: the speech element information storing unit is configured to store the speech element information and speech element identification information for identifying the speech element information in association with each other; the speech element requesting unit is configured to transmit the speech element identification information as the speech element request to the server device; and the speech element information transmitting unit is configured to transmit speech element information stored in association with the received speech element identification information.

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12. The one or more devices of claim 11 , where the one or more processors are further to: identify, based on processing the query, one or more documents based on the query; and determine a respective score for each of the one or more documents, where a first document, of the one or more documents, that includes the optional term is associated with a first score that is greater than a second score of a second document, of the one or more documents, that does not include the optional term.

11. The one or more devices of claim 8 , where, when identifying the extra term as a term that is not significant, the one or more processors are further to: identify the extra term as an optional term; associate, based on identifying the extra term as the optional term, a first weight with the extra term; associate a second weight with one or more other terms in the query, the second weight being different than the first weight; and process the query, including the extra term and the one or more other terms, based on the associated first weight and the associated second weight.

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18. The apparatus of claim 17 , wherein said performing fuzzy clustering on the graph comprises performing Fuzzy C-Means clustering on the vertices of the graph, wherein a similarity measure between two vertices is equal to a shortest path distance between the two vertices in the graph.

17. The apparatus of claim 16 , wherein said representing the netlist as the graph further comprises assigning a weight to each edge, wherein the weight is inversely proportional to the number of interconnections between the pair of cells that correspond to the pair of vertices between which the edge exists.

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13. The non-transitory computer readable storage medium of claim 11 , wherein identifying pairs of first and second command inputs from respective user device sessions for which the first and second operation data are indicative of and first operation failure and a second operation success comprises: for each pair of first and second command inputs: determining that the first command input included a parameter value specified by a user, the parameter value being of a parameter type; and determining that the second command input included the same parameter value specified by the user; and grouping the pairs of first and second command inputs according to corresponding parameter types of the parameter values specified by the pairs, each group corresponding to a particular parameter type.

11. A non-transitory computer readable storage medium storing instructions executable by a data processing apparatus and that upon such execution causes the data processing apparatus to perform operations comprising: accessing command input logs storing data defining user device sessions; identifying, from the command input logs, user device sessions that each respectively store: a sequence of two or more command inputs, each command input specifying one or more parameter values, and each command input having a respective ordinal position in the sequence, and wherein the sequence includes at least one pair of a first command input that precedes a second command input in ordinal position in the sequence; first operation data indicating a first operation performed on data from a first resource property in response to the first command input; second operation data indicating a second operation performed on data from a second resource property in response to the second command input; identifying pairs of first and second command inputs from respective user device sessions for which the first and second operation data are indicative of a first operation failure and a second operation success; and determining, from the identified pairs of first and second command inputs, command inputs for which a parsing rule that is associated with the second operation is to be generated.

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3. A method according to claim 1 , further comprising: matching the security credentials with a data source template.

1. A method, comprising: authenticating a user to a secure federated search environment; obtaining individual security attributes used by each of a plurality of secure data sources to determine whether to allow the user access, wherein each secure data source has its own identity management system; obtaining security credentials, a user ID, and a password from the user; translating the user ID and password into user identities for each of the identity management systems; filtering the security credentials of the user with the security attributes for each identity management system to create sets of security values corresponding to the security attributes for each identity management system; subscribing the user to at least one of a plurality of secure data source templates, the plurality of secure data sources templates defining the location of a repository and a set of instructions on how to crawl the repository; automatically launching a crawl of the at least one secure data source in response to the subscribing, wherein each secure data source crawled is indexed and has a portion stored locally by the federated search environment; receiving a query from the user; appending, to the query, the user identities and security values required by the identity management systems for each of the plurality of secure data sources, wherein the query has the user identities and security values embedded in the query; propagating the appended query to the plurality of secure data sources using the embedded user identities and security values to access the plurality of secure data sources; and consolidating query results received from the plurality of secure data sources, removing at least one duplicate result from the query results, and displaying the consolidated query results to the user in response to the query.

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1. A comment categorization system that categorizes comments received in response to open-ended questions, said comment categorization system comprising: a respondent client computing device comprising a processor, a memory, a display screen, and a non-transitory computer readable storage medium storing a respondent client program which when executed by the processor provides comments to open-ended questions for categorization, said respondent client program comprising sets of instructions for: displaying an open-ended question on the display screen; receiving a comment related to the open-ended question; providing the comment for category evaluation; receiving a set of category identifiers associated with a set of categories identified as likely to match the comment related to the open-ended question; receiving a selection of a particular category identifier from the set of category identifiers; and providing the particular category identifier for categorization of the comment; and a server computing device comprising a server processor, a server memory, and a non-transitory computer readable medium storing a comment categorization program which when executed by the server processor performs a comment categorization service, said comment categorization program comprising sets of instructions for: receiving, from the respondent client computing device, the comment for category evaluation; identifying a set of categorized comments related to the received comment; retrieving a set of category identifiers from the set of categorized comments related to the received comment; identifying, from a pool of categories, the set of categories likely to match the received comment, wherein each category in the identified set of categories comprises a category identifier, wherein the identified set of categories likely to match the received comment comprises categories of the retrieved set of category identifiers; providing the category identifiers of the identified set of categories to the respondent client computing device; receiving, from the respondent client computing device, the particular category identifier for categorization of the received comment; and categorizing the received comment in a particular category associated with the particular category identifier.

2. The comment categorization system of claim 1 further comprising an administrative researcher computing device comprising an admin processor, an admin memory, an admin display screen, and a non-transitory computer readable storage medium storing an admin program which when executed by the admin processor provides an administrative researcher user interface for preparing a comment categorization program to categorize comments received in response to open-ended questions, said admin program comprising a set of instructions for entering a set of categories to start the pool of categories.

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23. The system of claim 22 , wherein the shadowing system is configured to cause the engine to reference a first unapplied log file of the delta data, wherein the first unapplied log file is a first log file unapplied to the copy.

22. The system of claim 16 , wherein the applying includes invoking an engine of the one or more servers.

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18. A method for determining an end of a sentence of speech data, the method comprising: acquiring, by an automatic speech recognition device, speech data; recognizing, by the automatic speech recognition device and based on the speech data, phonemes of the speech data; recognizing, by the automatic speech recognition device and based on the phonemes, words of the speech data; parsing, by the automatic speech recognition device and based on the words, the speech data to determine a syntactic coherence of the speech data; determine, by the automatic speech recognition device and based on the words, a word statistics end-of-sentence score; determining, by the automatic speech recognition device and based on the syntactic coherence and the word statistics end-of-sentence score, an end of a sentence of the speech data; determining, by the automatic speech recognition device and based on the determined end of the sentence, a speech recognition result.

21. The method of claim 18 , further comprising: determining, by the automatic speech recognition device, a syntactic coherence end-of-sentence score based on the syntactic parse, and determining, by the automatic speech recognition device, an acoustic end-of-sentence score based on the phonemes, wherein determining the end of the sentence comprises determining the end of the sentence based on the syntactic coherence end-of-sentence score and the acoustic end-of-sentence score.

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1. An electronic device, comprising: a display for presenting paginated digital content to a user; and a user interface including an annotation mode, the annotation mode including multiple different note types for paginated digital content, the note types comprising: i) a sticky note that can be created in response to a tap or mouse click or selection made on the paginated digital content when the annotation mode is invoked, wherein the sticky note is represented by a movable graphic and selection of the graphic causes contents of the sticky note to be presented; and ii) a margin note that can be created by converting a previously created sticky note to a margin note, such that the margin note replaces the previously created sticky note and includes content from the previously created sticky note, wherein contents of the margin note are always presented and the margin note is configured to be placed anywhere on the paginated digital content.

12. The device of claim 1 wherein the annotation mode can be invoked through a graphic presented on the paginated digital content.

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22. A communication network with a business listing management interface, comprising: a location-based services system connected to a plurality of consumer remote terminals, said consumer remote terminals operable by subscriber consumers who are registered subscribers of said location-based services system; a profile data file included in said location-based services system, said profile data file comprising information specific to each of said subscriber consumers comprising a consumer identification, a password, and a subscriber consumer preference; an advertiser portal server computer connected to said location-based services system; a business listing interface application included in said advertiser portal server computer, said business listing interface application operable to create a business listing data entry form; said business listing data entry form configured for use by a business remote terminal connected to said advertiser portal server computer, said business remote terminal operable by a subscriber business that is a registered subscriber of said location-based services system to generate a business listing that is descriptive of said subscriber business, and delivery conditions under which said business listing is selectively directed towards said subscriber consumers of said consumer remote terminals, said business listing and said delivery conditions generated with said business remote terminal in response to receipt of business listing data descriptive of said subscriber business and data delivery restrictions into said business listing data entry form; and a business profile database included in said location-based services system, said business profile database configured to store said business listing in association with information specific to said subscriber business; and said location-based services system operable to identify and provide said business listing to one of said consumer remote terminals in response to a specific purchase request or a specific service request received by said location-based services system from a subscriber consumer of said one of said consumer remote terminals, said business listing identified by said location-based services system from said business profile database based on said specific purchase request or said specific service request and an identifier of said one of said consumer remote terminals received by said location-based services system with said specific purchase request or said specific service request, said location-based services system further operable to determine said subscriber consumer preference and said data delivery restrictions are being met by said information included in said profile data file that is specific to said subscriber consumer identified using said identifier.

23. The communication network of claim 22 , wherein said business remote terminal is a wireless communication device.

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28. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU, said apparatus comprising: an initialization mechanism configured to generate a plurality of candidate phrases responsive to a first open-site network search for a category term; an external scoring mechanism configured to determine an external score responsive to a second open-site network search for at least one of said plurality of candidate phrases; a targeted-site determination mechanism configured to determine at least one targeted-site expected to be associated with each of said plurality of candidate phrases; an internal scoring mechanism configured to determine an internal score for said at least one of said plurality of candidate phrases responsive to at least one targeted-site network search of said at least one targeted-site for said category term, wherein said targeted-site determination mechanism includes a filter mechanism configured to: construct a site query for each one of said plurality of candidate phrases responsive to the one of said plurality of candidate phrases and receiving at least one site query result responsive to the site query; discard each site query result for which the one of said plurality of candidate phrases is not contained in at least one of a site address and a site name of the site query result; extract at least one probable web host name from the remaining of the at least one site query result; construct a second mode query responsive to said category term and said at least one probable web host and submit at least one targeted-site network search using said second mode query; receive at least one third search result responsive to said at least one targeted-site network search using said second mode query; repeat said constructing a site query, said discarding, said extracting at least one probable web host name, said constructing a second mode query, and said receiving at least one third search result for each remaining of said plurality of candidate phrases; and determine said internal score responsive to said at least one third search result; a final scoring mechanism configured to determine a final score for said at least one of said plurality of candidate phrases responsive to said internal score and said external score; and a presentation mechanism configured to present said at least one of said plurality of candidate phrases.

35. The apparatus of claim 28 , wherein said category term is a generic term for a product or service and said plurality of candidate phrases contain one or more brands of said product or service.

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15. A computer-implemented method comprising: receiving a set of target search terms for a search; using a microprocessor of a computer, selecting a plurality of candidate terms, each candidate term selected to reduce an ontology space of the document due to the candidate term having a higher affinity with a target tag and a lower affinity with the other candidate terms; sending the candidate terms to a user of the computer via a user interface of the computer to recommend the candidate terms as search terms; receiving, via the user interface of the computer, a selection by the user of one or more terms of the candidate terms and identifying one or more terms of the candidate terms that were not selected by the user; using the microprocessor of the computer, determining a plurality of next terms that have both (i) an affinity with the one or more terms selected by the user that is above a first affinity threshold and (ii) an affinity with the one or more terms that were not selected by the user that is below a second affinity threshold; and sending the next terms to the user via the user interface of the computer to recommend the next terms as search terms.

17. The method of claim 15 , further comprising: establishing a source of each target search term of the set of target search terms; retrieving a plurality of search results, a search result associated with a target search term; and ranking the search results according to the sources of the target search terms.

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19. The memory device of claim 18 , further comprising: one or more instructions to cause the processing logic to use a dictionary to identify the possible translations of the terms into the second language.

18. The memory device of claim 16 , further comprising: one or more instructions to cause the processing logic to perform an initial translation of the terms of the search query into the second language to generate possible translations of the search query; one or more instructions to cause the processing logic to identify possible translations of the terms of the search query; and one or more instructions to cause the processing logic to disambiguate among the possible translations of the terms of the search query, using the content included in the one or more documents in the second language, to identify one of the possible translations as a likely translation of the search query.

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6. The system of claim 4 , wherein the logic that ranks the plurality of scenes based at least in part upon the analysis of text from the closed captioning data further comprises logic that ranks the plurality of scenes based at least in part upon an amount of dialog occurring within individual ones of the plurality of scenes.

4. A system, comprising: at least one computing device; and a video content analysis application executable in the at least one computing device, the video content analysis application comprising: logic that extracts closed captioning data from a video content feature; logic that performs an analysis of text from the closed captioning data; and logic that ranks a plurality of scenes of the video content feature based at least in part upon the analysis of text from the closed captioning data.

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2. The system of claim 1 , wherein the plurality of creativity measures comprise a fluency measure, a flexibility measure, an originality measure, and an elaboration measure.

5. The system of claim 2 , wherein the at least one first semantic characteristic comprises a measure of a statistical infrequency of each response to the first creativity test in the first user input, and wherein the originality measure is associated with the measure.

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7. The method of claim 1 , wherein each aspect term is a word or sequence of words which names a particular aspect of a target entity in a domain of interest.

1. A method for aspect categorization comprising: receiving an input text sequence; providing for identifying aspect terms in the input text sequence; providing for identifying sentiment phrases in the input text sequence; for an identified aspect term: providing for identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and from a dependency graph of the input text sequence, the dependency graph comprising a sequence of nodes, providing for identifying pseudo-dependencies in which a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term; extracting features from at least one of identified sentiment dependencies and identified pseudo-dependencies; with a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features; and outputting information based on the classification.

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4. The method of claim 1 , wherein the first part of the cue metadata defines a starting time and an ending time of a particular cue of the plurality of cues and the second part of the cue metadata includes information pertaining to one or more assignees of the particular cue.

5. The method of claim 4 , wherein the information pertaining to the one or more assignees includes one or more of: one or more names of one or more rights holders, one or more societies to which the one or more rights holders belong, or payment information for the one or more rights holders.

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10. Non-transitory media encoded in logic that includes instructions for execution that when executed by a processor, is operable to perform operations comprising: intercepting, at a client during execution of an application at a browser on the client, a JavaScript call, wherein a source code of the application indicates a timed sequence of execution of JavaScript files, wherein the JavaScript files comprise a first JavaScript file loaded into the client's memory element simultaneously with loading the application, a second JavaScript file having a dependency on the first JavaScript file and called during the timed sequence after the first JavaScript file is called, and a third JavaScript file not called after a certain duration of the timed sequence; accessing, by the client, a map file stored at a server upon intercepting the JavaScript call, wherein the map file is generated automatically at the server before execution of the application on the client, wherein the map file includes a dependency tree comprising the JavaScript files used in the source code, wherein the first JavaScript file is specified in an exclusion file, wherein the map file maps the second JavaScript file for lazy loading, wherein the map file maps Cascading Style Sheets (CSS) files with related map for class names to be used on the application; reverse mapping from the map file, at the client during runtime of the application, particular JavaScript files corresponding to the JavaScript call, wherein the reverse mapping comprises checking the JavaScript call for dependency resolution according to the map file, wherein a resolution scope of lazily loaded files ends with first-level dependencies of such files, wherein the particular JavaScript files are selected for loading according to the dependency resolution; loading the particular JavaScript files from the server into the client's memory element according to the exclusion file and the map file, wherein the loading comprises loading the first JavaScript file according to the exclusion file, lazy loading the second JavaScript file asynchronously with timestamp according to the map file, and reverse mapping relevant CSS files in the loaded files using related class names from the map file; and deleting, during application execution, the third JavaScript file from the client's memory element after the certain duration of the timed sequence.

12. The media of claim 10 , wherein the map file comprises a JSON file, wherein the JSON file is generated by parsing each JavaScript file and CSS file for methods and class names, respectively.

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6. The method of claim 1 , further comprising: generating an additional search query derived from terms associated with the label for the particular object category; identifying one or more videos identified in response to submission of the additional search query; and merging the plurality of candidate videos and the one or more videos identified in response to submission of the additional search query to generate a second plurality of candidate videos.

1. A method of generating labeled images of objects belonging to a particular object category, the method comprising: obtaining data identifying the particular object category; identifying database images of the objects belonging to the particular object category, comprising: generating a search query derived from a label for the particular object category; selecting a plurality of candidate videos from videos identified in response to submission of the search query; selecting one or more initial frames from each of the candidate videos; detecting one or more initial images of objects belonging to the particular object category in the one or more initial frames; for each initial frame including an initial image of an object belonging to the particular object category, tracking the object through surrounding frames to identify one or more additional images of the object; and selecting one or more images from the one or more initial images and one or more additional images as the database images of objects belonging to the particular object category; and storing the database images as images of objects belong to the particular object category.

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11. The system of claim 9 wherein the operations further comprise deleting at least one query suggestion based on a predetermined probability that selection of the query suggestion would result in returning a null search results page.

9. A system comprising at least one hardware processor coupled to computer storage to perform operations comprising: receiving a low frequency query from a client machine; analyzing a query log of user query sessions to identify a plurality of ordered sequences of low frequency queries including the low frequency query; generating a set of transition scores for the plurality of ordered sequences of low frequency queries based at least in part on a maximum number of transitions between a first query of an ordered pair of the plurality of ordered sequences of low frequency queries and a second query of the ordered pair to a purchase-related event, wherein an individual transition score comprises an accumulation of a popularity score and an accumulation of a purchase efficiency score; determining a normalized set of transition scores based on a frequency of the first query of each of the plurality of ordered sequences of low frequency queries; building a set of query suggestions for the low frequency query from the normalized set of transition scores; computing a set of similarity metrics for members of the set of query suggestions; determining whether one or more similarity metrics for individual suggestions of the set of query suggestions meet a predetermined similarity; and providing to the client machine a list of the individual suggestions whose similarity metrics meet the predetermined similarity.

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17. The system of claim 12 , wherein the indicator component module is further configured to determine the probability that the person class of the subset of facial components is the first person by: determining a first conditional probability, that a class is the first person, of a facial component of the subset of facial components at a first viewpoint; determining a first posterior probability, that a class is the first person, by multiplying the conditional probability at the first viewpoint by a prior probability, that a class is the first person; determining a second conditional probability, that a class is the first person, of a facial component of the subset of facial components at an additional viewpoint; and determining a second posterior probability, that a class is the first person, by multiplying the second conditional probability by the first posterior probability.

12. A system for recognizing faces of persons, comprising: a training module configured to train a facial component recognition system to recognize a facial component; a population module configured to populate a first knowledge base with facial components and, for each facial component, the facial component's body part classification, wherein the facial components in the first knowledge base include a first set of facial components extracted from facial identification training image data of a face of a first person at a first set of viewpoints; a computer readable storage medium storing an indicator component module configured to: determine a first set of body part classifications associated with the first set of facial components; for each body part classification in the first set of body part classifications: determine, from the first set of facial components, a subset of facial components that are associated with the body part classification, wherein the facial components in the subset represent a same body part classification of a same person at multiple viewpoints; and determine a probability that a person class of the subset of facial components is the first person; and determine a first body part classification in the first set of body part classifications that maximizes the probability; and a processor configured to execute the indicator component module stored by the computer readable storage medium.

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2. A computer-implemented method, comprising: receiving, at a computing device including one or more processors, a first input from a user, the first input including one or more characters of an alphabet-based language, wherein the alphabet-based language that is a transliteration of a non-alphabet-based language, the non-alphabet-based language being one of a logogram-based language and a syllabogram-based language, wherein the first input is to be communicated to a recipient; determining, at the computing device, a coefficient indicative of a gender of the recipient; based on the first input and the coefficient, determining, at the computing device, a first plurality of characters in the non-alphabet-based language, each of the first plurality of characters representing a potential translation of the first input; displaying, at the computing device, the first plurality of characters; obtaining, at the computing device, a first selected character by receiving a selection by the user of one of the first plurality of characters; obtaining, at the computing device, a modified coefficient by adjusting the coefficient based on the first selected character; receiving, at the computing device, a second input from the user, the second input including one or more characters of the alphabet-based language, wherein the second input is also to be communicated to the recipient; based on the second input and the modified coefficient, determining, at the computing device, a second plurality of characters in the non-alphabet-based language, each of the second plurality of characters representing a potential translation of the second input; displaying, at the computing device, the second plurality of characters; obtaining, at the computing device, a second selected character by receiving a selection by the user of one of the second plurality of characters; constructing, by the computing device, an electronic message comprising the first and second selected characters; and transmitting, from the computing device to a computing device associated with the recipient, the constructed electronic message.

3. The computer-implemented method of claim 2 , wherein the determining of the coefficient indicative of the gender of the recipient includes retrieving, based on information associated with the recipient, a base coefficient.

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5. The method of claim 4 , further comprising: providing for display, via the user interface, the model with the block connected to the particular block.

4. The method of claim 3 , further comprising: receiving selection of a particular ranked identifier from the at least one of the ranked one or more first identifiers; and connecting a particular block, associated with the particular ranked identifier, to the block.

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6. An apparatus comprising: a port interface unit configured to interface to a memory controller; an image processor; a translation unit coupled to the image processor and configured to cache translations for the image processor, wherein the translation unit is configured to cache each translation for a period of time that is dependent on how frequently the translation is accessed relative to other translations cached by the translation unit, wherein the translation unit is coupled to receive memory operations from the image processor and to translate virtual addresses in the memory operations, and wherein the translation unit is configured to transmit the memory operations with the translated addresses to the port interface unit; and a display pipe coupled to the port interface unit to fetch image data for display, wherein the display pipe includes one or more streaming translation units configured to prefetch translations for a plurality of virtual pages storing image data, wherein the streaming translation units are configured to discard translations of virtual pages that the display pipe has completed responsive to an indication from the display pipe that the fetch of image data from the virtual pages is completed and to prefetch one or more additional translations, wherein the display pipe is coupled to the port interface unit to transmit the fetch requests for the image data and requests to read translation data, and wherein the streaming translation units are configured to detect that fetching from the image data is being initiated, and wherein the fetch/memory management unit is configured to clear all translations and prefetch the translations for at least the first two rows of tiles in the image.

10. The apparatus as recited in claim 6 wherein the image data is arranged as tiles of image data, and wherein each virtual page of the plurality of virtual pages stores one tile.

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12. A method for forming a pronounceable security password according to claim 11, further comprising the step of determining if consecutive characters of said substitute portion of the password correspond to a first word segment portion, within said plurality of first word segment portions, and if the transition number of said corresponding first word segment portion is less than said second threshold transition number.

11. A method for forming a pronounceable security password according to claim 9, further comprising the steps: discarding said second pronounceable word segment if the transition number of said corresponding word segment is less than said second threshold transition number; selecting a third one of said plurality of first word segment portions, wherein selection of any one of said plurality of first word segment portions is of substantially equal probability; selecting a third one of said plurality of second word segment portions from the set of second word segment portions associated with said third selected first word segment portion, wherein selection of any one of said second word segment portions within said associated set of second word segment portions is of substantially equal probability; combining said third selected first word segment portion and said third selected second word segment portion to form a substitute second pronounceable word segment; and combining said first pronounceable word segment and said substitute second pronounceable word segment to form a substitute portion of the password; wherein said generated pronounceable security password includes said substitute second pronounceable word segment only if consecutive characters of said substitute password portion fail to correspond to those of said plurality of first word segment portions having a transition number less than said second threshold transition number.

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15. An article of manufacture for processing electronic documents, the article of manufacture comprising: at least one non-transitory processor readable storage medium; and instructions stored on the at least one medium; wherein the instructions are configured to be readable from the at least one medium by at least one processor and thereby cause the at least one processor to operate so as to: obtain an electronic document being sent over a network toward a destination; analyze text content of the electronic documents to identify whether the electronic document matches any of a plurality of predefined document templates, wherein the electronic document conforms to a structure of at least one of the plurality of predefined document templates, and wherein the analyzing comprises executing at least one machine learning algorithm, the at least one machine learning algorithm trained using at least one sample electronic document having a predefined template; obtain a document loss prevention (DLP) policy based on the at least one predefined document template associated with the electronic document, wherein the DLP policy defines at least one rule to block sending of at least one of the electronic documents if the at least one of the electronic documents matches any of the plurality of predefined document templates; and selectively allow the electronic document to continue toward the destination based on the DLP policy.

20. The article of manufacture of claim 15 , wherein the DLP policy defines a set of destinations associated with the at least one predefined document template, and wherein the electronic document is not allowed to continue to any destination in the set of destinations.

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5. A natural language based service selection system for complementing incomplete queries, comprising: a semantic analyzing device which analyzes an incomplete query from a user semantically; a service selecting device which complements the incomplete query based on a semantically-analyzed query to complete the incomplete query, and selects a corresponding selected service from among a plurality of services based on a complete query; a retrieving device which retrieves an answer according to the corresponding selected service; and at least one processor coupled to the semantic analyzing device, the service selecting device and the retrieving device, wherein the service selecting device comprises an automatic service selecting section which searches lost content in a current query by using a service mapping rule base and complements the lost content through searching a current user query history base, wherein the automatic service selecting section comprises: a lost content searching unit which matches the semantically-analyzed query with a service mapping rule in the service mapping rule base, and extracts a service type to which the current query belongs and a lost parameter in the current query; a latest query detecting unit which searches a latest query contained the lost parameter in the current query from the current user query history base, and extracts the parameter value corresponding to the lost parameter in the current query; and a query complementing unit which adds the service type, the lost parameter and the parameter value into the semantically-analyzed query to form the complete query.

8. The natural language based service selection system according to claim 5 , wherein the lost content searching unit retrieves the service mapping rule meeting the following conditions as a matched service mapping rule from the service mapping rule base: a requirement in the service mapping rule is identical to a requirement of the semantically-analyzed query; and a service parameter in the service mapping rule contains a parameter of the semantically-analyzed query.

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78. The computer-readable memory device of claim 77 , further comprising: one or more instructions to determine that a score for another one of the plurality of links is less than a particular threshold; one or more instructions to delete the other one of the plurality of links from the identified document when the score for the other one of the plurality of links is less than the particular threshold; and one or more instructions to provide, to a user, the identified document without the deleted link.

77. A computer-readable memory device storing instructions executable by at least one processor, the computer-readable memory device comprising: one or more instructions to identify a document based on an address associated with the document, the document including links that point to linked documents; one or more instructions to determine scores for a plurality of the links in the identified document; one or more instructions to compare the determined scores to a threshold; one or more instructions to determine that a score for one of the plurality of links is greater than the threshold; one or more instructions to determine additional information regarding the linked document pointed to by the one of the plurality of links; and one or more instructions to provide the identified document with the additional information to a user.

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10. A method for defining a content relevance model for a particular category, the method comprising: identifying a set of key word sets for the particular category based on an analysis of (i) a first set of content segments previously defined as relevant to the particular category and (ii) a second set of content segments previously defined as not relevant to the particular category; identifying (i) a set of pairs of word sets that each comprise a key word set and a word set that appears in a defined context of the key word set and (ii) a score for each of the word set pairs, the score for a particular word set pair quantifying a likelihood that a content segment containing the particular word set pair is relevant to the particular category, wherein appearances of the particular word set pair in the first set of content segments increase the score for the particular word set pair and appearances of the particular word set pair in the second set of content segments decrease the score for the particular word set pair; and defining a content relevance model for the particular category, the content relevance model comprising (i) a context definition that indicates when a second word set appears within a context of a key word set and (ii) the set of word set pairs and corresponding scores.

15. The method of claim 10 , wherein determining a score for the particular word set pair comprises comparing a function calculated for the particular word set pair in the first set of content segments to the same function calculated for the particular word set pair in the second set of content segments.

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23. The computer program product of claim 22 further comprising: said owner selectively incorporating said edits stored in the secondary data files into said document of the master data file.

22. The computer program product of claim 21 , wherein said document is created by at least one owner and said at least one owner designates at least one of said reviewers.

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9. The system of claim 6 , where the one or more computers, when parsing the second string into the one or more tokens, are to selectively formulate each token, of the one or more tokens, as one or more consecutive natural-language words of the second string.

6. A system, comprising: one or more computers to: receive a first string corresponding to an interpretation of a natural-language user voice entry, the natural-language user voice entry provided by a user via a microphone of a computing device of the user; provide a representation of the first string as feedback to the natural-language user voice entry, the feedback for providing to the user via a graphical display or speaker of the computing device of the user; receive, based on the feedback to the natural-language user voice entry, a second string corresponding to a natural-language corrective user entry, the natural-language corrective user entry provided by the user via the computing device of the user and corresponding to a correction to the natural-language user voice entry; parse the second string into one or more tokens; determine at least one corrective instruction from the one or more tokens of the second string; generate, from at least a portion of each of the first string and the second string and based on the at least one corrective instruction, a plurality of candidate corrected user entries, a token of the one or more tokens being inserted at a plurality of locations in the first string while maintaining all other tokens of the first string, based on the at least one corrective instruction, to generate candidate corrected user entries of the plurality of candidate corrected user entries; select a corrected user entry from the plurality of candidate corrected user entries; output the selected corrected user entry; and obtain one or more search results from a search engine based on the selected corrected user entry for providing to the user via the graphical display or the speaker of the computing device of the user.

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5. The computer-implemented method of claim 4 , wherein the determined frequencies are further based on search logs for search queries received within a threshold amount of time from a current time.

4. The computer-implemented method of claim 1 , wherein the corpus further comprises search logs of search queries associated with the target language.

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14. The method of claim 1 , wherein analyzing the first dynamic value data and the second dynamic value data to identify candidate parameters for correlation within the base script comprises: generating a correlation log using the first dynamic value data and the second dynamic value data.

1. A method comprising: accessing, by a device from an electronic storage, a first response file generated during a first execution of a first recording of a base script on a system that includes at least one processor and at least one memory and a second response file generated during a second execution of a second recording of the base script on the system, the base script defining operations to be executed in testing performance of the system; determining, by the device, first dynamic value data that describes one or more first dynamic values stored in the first response file and second dynamic value data that describes one or more second dynamic values stored in the second response file; analyzing, by the device, the first dynamic value data and the second dynamic value data to identify candidate parameters for correlation within the base script; generating, by the device, a correlated script using the identified candidate parameters and the base script; and storing, by the device, the correlated script.

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20. The method of claim 19, wherein the step of determining the bounds of the paragraph comprise the step of referring to a paragraph file position table in the file used to store the characters in one of the pieces, said paragraph file position table reporting a limit file position for each paragraph delimiter used in the text stored in said file.

19. The method of claim 13, further comprising the steps of determining bounds of a paragraph containing a character to be displayed; and having identified an end of the paragraph, determining the number of characters in the paragraph delimiter used for said paragraph.

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13. The method of claim 11 wherein, for a set of query results, ranking comprises: identifying, by the at least one computing device, the number of times that each keyword candidate appears.

11. The method of claim 1 wherein selecting one of the keyword candidates as the representative keyword further comprises ranking, by the at least one computing device, the keyword candidates.

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4. The method of claim 1 , wherein extracting one or more features includes applying a moving median feature extraction process to the dataset.

5. The method of claim 4 , wherein the moving median feature extraction process calculates a global median, a mid-term performance median, and a current performance median.

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9. The computer program product of claim 3 , wherein the ontological graph comprises levels that extend beyond that of the parent term, and wherein the method further comprises: restricting a view of the ontological graph to nodes below the parent term, wherein said restricting the view is in accordance with instructions derived from the third expansion signal.

3. The computer program product of claim 2 , wherein the method further comprises: receiving a third expansion signal from the user; and expanding the dictionary to include a parent term of at least one of said terms from the ontological graph, wherein the parent term includes a term that describes the common trait, and wherein the dictionary is expanded to include the related terms in accordance with instructions derived from the third expansion signal.

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8. The system of claim 7 wherein a form document is created by the first communication terminal based upon the saved first text data, second text data, third text data, and fourth text data.

7. A communication system comprising: a first communication terminal; and at least one of a first communication device and a second communication terminal communicatively connectable to the first communication terminal for establishing a communication session in which audio data is transmitted between the first communication terminal and the at least one of the first communication device and the second communication terminal; and at least one of the first communication terminal, the first communication device, and the second communication terminal activating a speech to text translation mechanism, the speech to text translation mechanism translating the audio data into text data and saving the translated text data; wherein the first communication terminal provides a personal call agent service and wherein the first communication terminal activates the speech to text translation mechanism, the speech to text translation mechanism comprising an application stored in the first communication terminal that is executed by the first communication terminal, the first communication terminal translating the audio data into text data and saving the translated text data; wherein the communication session is established by the first communication terminal forming a connection with the first communication device or the second communication terminal, and wherein the first communication terminal translating of the audio data into text data and saving the translated text data comprises: the first communication terminal translating a first audio question into first text data and saving the first text data of the first audio question, the first communication terminal translating a first audio answer to the first audio question into second text data and saving the second text data such that the second text data is associated with the first audio question, the first communication terminal translating a second audio question into third text data and saving the third text data of the second audio question, and the first communication terminal translating a second audio answer to the second audio question into fourth text data and saving the fourth text data such that the fourth text data is associated with the second audio question; wherein the first communication terminal receives a third audio question from the second communication terminal that is sent to the first communication terminal and determines that the third audio question is a same question as the second audio question; in response to the determination that the third audio question is the same question as the second audio question, the first communication terminal suggesting a third answer to a user of the first communication terminal that is in at least one of audio format and text format, the third answer in audio format comprising the second audio answer and the third answer in text format comprising text of the fourth text data; and the first communication terminal sends the suggested third answer to the second communication terminal in at least one of audio format and text format upon receipt of input from the user authorizing the sending of the suggested third answer.

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1. A method for locating a genome pattern, comprising: creating, using a processor of a computer, one or more lexical annotators that each identify a sequence of nucleotides of nucleotide bases selected from A, C, G, and T; providing (1) the one or more lexical annotators, (2) one or more dictionary entries, (3) one or more previously-defined parsing rule annotators, and (4) one or more characters that each represent a nucleotide; creating a parsing rule annotator that identifies an order of and a combination of at least two elements selected from (1) the one or more lexical annotators, (2) the one or more dictionary entries, (3) the one or more previously-defined parsing rule annotators, and (4) the one or more characters that each represent a nucleotide; and creating an Unstructured Information Management Architecture (UIMA) pipeline to locate the genome pattern using the parsing rule annotator by: in a first stage of the UIMA pipeline, parsing a genetic sequence that is found in a Common Analysis Structure (CAS) to determine a language used and to generate tokens that are added to the CAS with a start position and an end position for each of the tokens; in a second stage of the UIMA pipeline, executing the one or more lexical annotators against the genetic sequence to identify one or more lexical annotations that are added to the CAS with a start position and an end position for each of the one or more lexical annotations; and in a third stage of the UIMA pipeline, using the start position and the end position for each of the tokens and the start position and the end position for each of the one or more lexical annotations to identify a match to the parsing rule annotation and to form a new annotation that is added to the CAS.

5. The method of claim 1 , wherein there are multiple occurrences of a same lexical annotation with different start positions and end positions.

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9. The computer-implemented method of claim 8 , further comprising: upon determining that the count of the plurality of individuals is equal to or greater than a predefined count of individuals characterizing the skill level of the first individual, generating output identifying the first individual and specifying the confirmed first characterization of the skill level of the first individual in the specified skill, without requesting any additional individual, including the second individual, to characterize the skill level of the first individual, wherein the output is returned to the requesting entity responsive to the request; wherein the plurality of individuals are distinct, wherein the first characterization of a skill level of the first individual in the specified skill is not determined based on any input from the first individual, wherein the first individual is not requested to characterize the skill level of the first individual in the specified skill.

10. The computer-implemented method of claim 9 , wherein the count of the plurality of individuals characterizing the skill level of the first individual is identified by accessing the data store, wherein the count is incremented upon receiving the second characterization from the second individual, wherein the count is not incremented upon determining that the plurality of individuals is, in number, equal to or greater than the predefined count of individuals characterizing the skill level of the first individual; wherein requesting at least the second individual to provide a second characterization comprises: requesting one or more individuals, including the second individual, to characterize the skill level of the first individual, such that: (i) a sum of: (A) a count of the one or more individuals and (B) the count of the plurality of individuals equals the predefined count of individuals; and (ii) a final characterization of the skill level of the first individual in the specified skill is programmatically determined, such that no individual beyond the predefined count of individuals is requested to characterize the skill level of the first individual and such that the final characterization is not subsequently modified based on input from any individual.

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1. A computer implemented method comprising: performing, by a processor, a first Xpath evaluation on a stream of Extensible Markup Language (XML) messages, the first Xpath evaluation based on a group of Xpath queries associated with a first user transaction; receiving, by a processor, a plurality of requests to modify the Xpath query group and combining the plurality of requests into a single atomic modification; and modifying, by a processor, the Xpath query group, in a persistent manner, without affecting the ongoing first Xpath evaluation on the XML messages, wherein modifying the Xpath query group comprises: generating a second data structure as a copy of portions of a first data structure, the first data structure comprising a hash table with branches, the branches derived from the group of Xpath queries prior to modification and only copying branches of the first data structure being modified; altering at least one branch of the second data structure in accordance with the modification request, wherein the single atomic modification modifies the second data structure to perform a subsequent Xpath evaluation corresponding to a subsequent modification request of the plurality of requests without generating an additional data structure; performing a second Xpath evaluation, associated with a second user transaction, using the second data structure in substantially real time with the first Xpath evaluation such that the first and second user transactions are overlapping; and deleting the first data structure upon completion of the first user transaction and using the second data structure for additional user transactions until modified.

2. The computer implemented method of claim 1 , wherein said modifying comprises: generating a current generation of Nondeterministic Finite Automaton (NFA) by compiling said Xpath query group, said current generation of NFA maintained as a data structure; identifying at least one branch of said data structure starting from the root node according to the modification request; creating a copy of the identified at least one branch of the data structure; modifying said copy to create a new generation of NFA further comprising modifying said at least one branch of the data structure starting from the root node; and using said new generation of NFA for subsequent Xpath evaluations.

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11. The method of claim 9 , wherein if the requested character index does not match any of said second character indices, then: determining if the requested character index matches any of said third character indices, if a match is found, then outputting the character within said third font that corresponding to the matched third character index; else determining if the requested character index matches any of said fourth character indices, if a match is found, then outputting the character within said fourth font that corresponding to the matched fourth character index.

9. The method of claim 7 , further comprising: (e) activating a fourth font from said font-storage memory by storing a fourth font location of said fourth font in a fourth font-access memory, said fourth font including a fourth plurality of characters each identified by a fourth corresponding character index, said fourth font being a fourth character set; wherein: said third character set is a sub-set of said fourth character set, and the third character index of each character within said third character set matches the fourth character index of its corresponding character within said fourth character set; said second character set is a sub-set of said fourth character set, and the second character index of each character within said second character set matches the fourth character index of its corresponding character within said fourth character set.

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5. The method of claim 3 , wherein the generic object comprises an indication of a number of the data objects represented by the generic object.

3. The method of claim 1 , wherein providing the second sentence for display comprises providing the second sentence for display with an object that is a generic object, the generic object representing a plurality of data objects.

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6. The computer readable medium of claim 1 wherein the report includes metadata identifying the recipient.

7. The computer readable medium of claim 6 wherein the metadata anonymously identifies the recipient.

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12. The method of claim 11 , wherein the multimedia objects are extracted from the multimedia content by steps further comprising: segmenting the content of each multimedia type in the multimedia object into segments within the multimedia object by media segmentation processing; and generating at least one feature description for at least one of the segments by feature extraction and annotation, wherein the generated media object descriptions comprise the at least one feature description for the at least one of the segments.

17. The method of claim 12 , wherein generating media object hierarchy descriptions generates media object hierarchy descriptions of the media object descriptions based on relationships of media objects represented by the media object descriptions, and wherein the relationships are selected from the group comprising media feature relationships, semantic feature relationships, temporal feature relationships, and spatial feature relationships.

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1. A search method, comprising: A) causing a first information set to be generated, comprising a first plurality of items, wherein each item of the first plurality of items is associated with at least one characteristic; B) representing at least some of the first information set in a first presentation; C) receiving a first feedback based upon the first presentation from a user; D) applying an evolutionary algorithm to a plurality of characteristics associated with the first plurality of items to generate a first search query, wherein the evolutionary algorithm is based on the first feedback; E) causing the first search query to be executed to generate a second information set comprising a second plurality of items, wherein each item of the second plurality of items is associated with at least one characteristic; F) representing at least some of the second information set in a second presentation; G) in response to a user input, repeating step B and representing at least some of the first information set in the first presentation; H) receiving a second feedback based upon the second presentation from a user; I) applying an evolutionary algorithm to a plurality of characteristics associated with the second plurality of items to generate a second search query, wherein the evolutionary algorithm is based on the second feedback; J) causing the second search query to be executed to generate a third information set comprising a third plurality of items, wherein each item of the third plurality of items is associated with at least one characteristic; and K) representing at least some of the third information set in a third presentation; wherein at least one characteristic associated with each item is chosen from a group comprising: at least one descriptor made available by a search engine or web directory service; at least one tag; at least one keyword; at least one classification-oriented identifier; at least one categorization-oriented identifier; and at least one semantic web-oriented identifier; and wherein at least one characteristic associated with each item is not a word or phrase selected from text displayed as part of the item.

16. The method of claim 1 , wherein the at least one characteristic associated with at least one item of at least one plurality of items comprises: a keyword; a classification-oriented identifier; a categorization-oriented identifier; or a semantic web-oriented identifier.

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8. The method of claim 3 , further comprising: receiving contact event text correspondence data; and determining semantic characteristics of the contact event text correspondence data based on semantic analysis of the contact event text correspondence data.

3. The method of claim 1 , further comprising providing contact event data to an agent device associated with the selected service agent profile.

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45. The computer program product of claim 44 wherein the facet analysis component is configured to receive input information and discover the facets, facet attributes, and facet attribute hierarchies of the input information, said input information comprising at least one of information of the domain to be classified and said dimensional concept taxonomy information.

47. The computer program product of claim 45 wherein the facet analysis component is configured to define the facets, facet attributes, and facet attribute hierarchies using pattern augmentation and statistical analyses to identify patterns of facet attribute relationships in the input information, wherein said facet attribute relationships are determined from facet attributes in related concept definitions and concept relationships in the input information and in accordance with a prevalence of the facet attribute relationships derived from the input information.

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9. The system of claim 8 wherein the phonemes are Hidden Markov Models.

10. The system of claim 9 further including a recognition server to enable a user to request the services of a speech recognition unit for an application running on the processor or running on a different processor on the network.

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9. The improvement of claim 1 wherein the first spacer has opposed non-parallel load-bearing end surfaces.

10. The improvement of claim 9 wherein the first spacer has a curved load bearing surface.

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9. The method of claim 7 , wherein the semantic features are further defined by at least one feature description selected from the group comprising keywords, who, what object, what action, why, when, where, and text annotation.

7. The method of claim 5 , the multimedia objects are extracted from the multimedia content by steps further comprising selecting the at least one feature description from the group consisting of media, semantic, and temporal features.

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10. The computer-implemented method of claim 9 , wherein the latent event scores act as a bias on an output of the observation component.

9. The computer-implemented method 1 , wherein at least some of the plurality of features for one or more of the events are not hierarchically related and the graphical data structure is created such that the graphical data structure comprises an observation component including a plurality of variable nodes representing weights associated with the features that are not hierarchically related.

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10. The method of claim 1 , wherein the similarity score is based in part on a spelling similarity between the each of the plurality of non-matching entities and the at least one of the exact item matches.

1. A method performed by a computing device having a processor and a memory for identifying comparable item matches for search queries, the method comprising: receiving at least a portion of a search query inputted on a Web page associated with a search engine; accessing an entity data store comprising one or more entities, and one or more categories associated with the one or more entities, wherein the one or more entities are items having associated information and are associated with at least one of the one or more categories; using the entity data store, identifying a number of exact item matches for the at least a portion of the search query; determining that the number of exact item matches is below a predefined threshold; and upon determining that the number of exact item matches is below the predefined threshold, using the entity data store to identify comparable item matches for the at least a portion of the search query, wherein using the entity data store to identify the comparable item matches for the at least the portion of the search query comprises: (1) assigning a similarity score to each of a plurality of non-matching entities in the entity data store that indicates a relative similarity to at least one of the exact item matches, (2) comparing the similarity score to a predefined similarity score, (3) generating query formulation suggestions using a portion of the plurality of non-matching entities that have similarity scores greater than the predefined similarity score, the portion of the plurality of non-matching entities comprising comparable item matches, and (4) presenting at least a portion of the query formulation suggestions on the Web page associated with the search engine.

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34. The method of claim 20 , wherein the first endpoint comprises an Interactive Voice Response system prompt.

20. The method of claim 1 , wherein the first endpoint and a subsequent endpoint are part of the plurality of endpoints in the contact center operation system, and further comprising the step of: a. performing by the first endpoint, the language assignment of the inbound interaction based at least in part on at least one of the interaction's location of origin and the interaction's destination location, wherein the language assignment comprises the reference means.

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1. A method of processing an inductive learning model for a database containing a dataset of examples, said method comprising: dividing said dataset of examples into a plurality of subsets of data; and generating, using a processor on a computer, a learning model using examples of a first subset of data of said plurality of subsets of data, wherein: said learning model being generated for said first subset comprises an initial stage of an evolving aggregate learning model (ensemble model) for an entirety of said dataset, said ensemble model thereby providing an evolving estimated learning model for the entirety of said dataset if all said subsets were to be processed, and said generating said learning model using data from a subset includes calculating a value for at least one parameter that provides an objective indication of an adequacy of a current stage of said ensemble model.

11. The method of claim 1 , wherein said at least one parameter comprises an estimated training time to complete development of said ensemble model if all subsets of said plurality of subsets of data were to be processed.

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8. The method according to claim 7 where the generic language model is derived from one or more of a factory, site or user specific language model.

9. The method according to claim 8 further comprising an act of conducting speech recognition with said generic language model.

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15. The system of claim 14 , wherein at least some of the motion data is determined by an accelerometer of the device.

14. The system of claim 11 , wherein motion data associated with the first image and the second image is used in joining the first image with the second image.

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1. A method for training a topic model, comprising: for a document within a document corpus: receiving a document representation of the document and features of the document, the document representation comprising a frequency of word occurrences within the document; processing the document representation and the features using a topic model, the processing comprising: specifying a feature/topic parameter for a feature of the document, the feature/topic parameter specifying a probability of the feature being indicative of a first topic, the feature/topic parameter based upon a first uncertainty measure that is associated with a first determination of a first deviation of the feature/topic parameter from a current feature/topic parameter for the topic model; updating the first uncertainty measure based upon a first difference measure between the feature/topic parameter and one or more previously specified feature/topic parameters for the topic model, the first difference measure representing a first range of deviation for the first uncertainty measure; specifying a document/word/topic parameter for a word within the document, the document/word/topic parameter specifying a probability of the word being indicative of a second topic, the document/word/topic parameter based upon a second uncertainty measure that is associated with a second determination of a second deviation of the document/word/topic parameter from a current document/word/topic parameter for the topic model; and updating the second uncertainty measure based upon a second difference measure between the document/word/topic parameter and one or more previously specified document/word/topic parameters for the topic model, the second difference measure representing a second range of deviation for the second uncertainty measure; and training the topic model based upon the feature/topic parameter and the document/word/topic parameter.

2. The method of claim 1 , comprising: determining a word/topic distribution prediction for a second word within a second document based upon processing the second document using the topic model, the word/topic distribution prediction specifying a probability of the second word being indicative of a third topic.

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3. The system of claim 2 , wherein said requesting module configured to request for at least the portion of the objective occurrence data including the data indicating incidence of at least one objective occurrence from the user comprises: a selection request module configured to request for a selection to be made by the user of an objective occurrence from a plurality of indicated alternative objective occurrences.

2. The system of claim 1 , wherein said objective occurrence data solicitation module configured to solicit at least a portion of objective occurrence data including soliciting data indicating incidence of at least one objective occurrence, the solicitation being prompted based at least in part on a hypothesis linking one or more objective occurrences with one or more subjective user states and in response, at least in part, to an occurrence of at least one subjective user state associated with a user comprises: a requesting module configured to request for at least the portion of the objective occurrence data including the data indicating incidence of at least one objective occurrence from the user.

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58. The apparatus of claim 57 further comprising: means for merging the phoneme sub-strings for adjacent contexts when two phoneme sub-strings overlap.

57. The apparatus of claim 56 , wherein the means for selecting phoneme sub-strings further comprises: means for selecting phoneme strings in the pronunciation data neighborhood for each context within the out-of-vocabulary word; means for aligning the selected phoneme strings on common phoneme sub-strings; and means for selecting a phoneme sub-string for each context from the common phoneme sub-strings.

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1. A method of actively sharing an application configured to be executed on both an originating and destination computing device, the method comprising: binding the application executing on the originating computing device with one or more documents maintained in a data model, the one or more documents representing a state of the executing application; initiating a collaboration session between the originating and destination computing devices, in which the state of the application executing on the originating computing device is exported to the destination computing device, comprising: serializing the state of the application on the originating computing device; propagating a serialized representation of the application state generated on the originating computing device to a server computing device that is configured to manage data exchange between the originating and destination computing devices; and providing the destination computing device with rights to access resources associated with the application and the serialized representation of the application state generated by the originating computing device; in response to the occurrence of a state change to the application executing on the originating computing device: updating the one or more documents bound to the application executing on the originating computing to represent the state change; generating a transaction on the originating computing that provides a description of the state change; and transmitting the transaction that provides the description of the state change to the server computing device.

11. The method as recited in claim 1 , wherein to export the state of the executing application includes configuring an object that models a user interface component to identify the data that the object is bound from an Xbind.

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43. The computer-readable storage medium of claim 42 , wherein program code for identifying the event schema for the identified event responsive at least in part to an article type of the article comprises program code for: selecting the event schema for the event from among a plurality of schemas associated with a plurality of article types.

42. A computer readable storage medium on which is encoded executable program code for category based search, the program code comprising: program code for identifying an event comprising a user interaction with a web page responsive to monitoring user interactions with a client device; program code for identifying an event schema describing a format of the identified event responsive at least in part to an article type of the web page, the schema comprising fields describing the web page and fields that describe interactions with the web page; program code for identifying a plurality of attributes associated with the identified event based at least in part on one or more fields of the event schema, the plurality of attributes identified responsive to the web page and the monitored user interactions, wherein at least a first attribute is associated with a keyword; program code for searching a category-keyword data store for a category associated with the keyword; program code for receiving a category identifier from the category-keyword data store; program code for storing an association data record in a category-article data store, the association data record comprising a category-article pair identifier, the category-article pair identifier associating the category identifier and an identifier identifying the web page; program code for receiving an implicit search query; program code for causing the implicit search query to be executed on the category-article data store; program code for receiving the association data record from the category-article data store; and program code for causing the identifier identifying the web page and the category to be output.

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9. A method for retrieving information from databases, said databases being structured or unstructured, said databases being homogeneous or heterogeneous, wherein retrieval is performed through visual queries on dynamic taxonomies, said dynamic taxonomies being an organization of concepts that ranges from a most general concept to a most specific concept, said concepts and their organization being called an intension, items in said databases being classified under one or more concepts, said items and their classification being called an extension, said method comprising, given an initial current subset of interest: using a computer for providing a reduced taxonomy for the current subset of interest; using the computer for refining the current subset of interest of said reduced taxonomy with the combination of one or more taxonomy concepts through Boolean operations; and using the computer for iteratively repeating said steps of providing a reduced taxonomy for the current subset of interest to further refine said retrieval and of refining the current subset of interest, wherein: said initial subset of interest includes all the items in the extension of the dynamic taxonomy or a subset of them; said reduced taxonomy being derived from said taxonomy by using the computer for pruning concepts under which no item in said current subset of interest is classified; said step of pruning concepts includes eliminating from the taxonomy all the concepts under which no item in the current subset of interest is classified, or preventing said concepts from being displayed, or preventing said concepts from being selected in order to refine interest sets; said step of providing a reduced taxonomy either reports only the concepts belonging to the reduced taxonomy or, for each such concept also reports how many items in the current interest set are classified under the concept; said intension is organized as a hierarchy of concepts or as a directed acyclic graph of concepts, thereby allowing a concept to have multiple fathers; in said extension, there exists at least one item such that said item is classified under at least two different concepts such that each of said two concepts is neither an ancestor nor a descendant of the other concept in the intension.

20. The method of claim 9 , said method allowing the restriction of access to a predefined subset of interest for a specific user or a set of users by using said predefined subset of interest instead of the universe for all the interactions of said specific user or a set of users.

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9. The method of claim 1 , wherein the computing device is a portable user device, wherein no language has been set for the portable user device prior to the selecting, and wherein the identified available network is an unencrypted wireless network.

1. A method comprising: searching for an available network by a computing device, wherein a device language setting has not been selected by a user for the computing device; automatically sending, by the computing device, an access request message to an identified available network; receiving a response to the access request message from the identified available network, the response comprising a portal page that comprises a hypertext markup language (HTML) document to which a captive portal of the identified available wireless network redirects network access requests; and selecting, by the computing device, a language for the computing device based on words included in the portal page.

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3. A computer-implemented method for processing user entered query data as recited in claim 1 , wherein the normalizing is executed on each of the tagged intent terms, then on each of the tagged city terms, then on the tagged state terms, and then on a combination of the tagged city and tagged state terms.

1. A computer-implemented method for processing user entered query data to improve results of a search of pages using a local search database, when searching the internet, comprising: (a) receiving the user entered query data and parsing each word of the query data; (b) examining each word to determine if the word is associated with one of an intent name, a city name or a state name, the examining using a probabilistic dictionary to determine a likelihood that the word is one of the intent name, the city name or the state name, and associating the words that were determined to be, (i) the intent name with an intent name tag to create one or more tagged intent terms; (ii) the city name with a city name tag to create one or more tagged city terms; or (iii) the state name with a state name tag to create one or more tagged state terms; (c) normalizing each of the tagged intent terms, the tagged city terms and the tagged state terms, the normalizing including boosting information if found in the local search database and determining proximity between selected ones of the tagged intent, city or state terms; and (d) generating an optimized internal search query that incorporates constraints and ranking based on at least the boosting information and the determined proximity between the selected tagged intent, city or state terms, the optimized internal search query being applied to the internet to enable search results to be produced and displayed to the user in response to the entered query data, where operations defined by the computer-implemented method are executed by a processor.

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5. The method of claim 1 wherein the first event and the second event are from a recurring series of related events.

1. A method for managing computer-based documents, comprising: identifying, by a computing device using calendar information from a calendar program associated with a first participant, related events in the calendar program associated with the first participant, wherein the related events include a first event and a second event, wherein the first event is associated with a first time period on a specified day, wherein the first time period occurs in the present or in the future, wherein the second event is associated with a second time period, wherein the second time period occurred in the past, wherein the calendar program includes, for the first participant and for the specified day, first participant events including the first event, wherein the calendar information includes at least one of event title, event participant list, event tag, or event topic, and wherein the identification of the related events is made when at least some of the calendar information associated with the second event matches at least some of the calendar information associated with the first event; identifying a first document associated with the second event, wherein the first document was created, accessed, or modified by the first participant during the second time period, and wherein the first document is inaccessible by a second participant of the first event; creating, in a folder of a directory, a link to the first document, wherein the folder is a folder of the first participant and the folder is inaccessible to the second participant of the first event, wherein the folder is associated with the first event, and wherein the directory is part of a program other than the calendar program, is associated with the specified day, and includes respective folders for some of the first participant events including the folder associated with the first event; responsive to a selection of the specified day in the program, displaying the directory, the respective folders including the folder associated with the first event, and the link to the first document; and sharing, with a permission of the first participant, the folder and the link with the second participant of the first event.

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1. A computer-implemented method for time searching data, comprising: receiving time series data streams from an information processing environment that includes a plurality of servers; organizing the time series data stream for subsequent searching by performing actions, including: determining at least one domain that corresponds to data in the time series data streams, wherein data in the time series data streams is aggregated based on at least the one determined domain; time stamping the time series data streams to create at least one time stamped event that includes at least a portion of aggregated data from the time series data streams, wherein the time stamped event represents a statistic and a pattern of behavior; employing at least one feature of the included aggregated data to determine at least one boundary for each time stamped event; segmenting each time stamped event into a plurality of segments, wherein a segment is a substring of event text; time indexing the time stamped events to create time bucketed indices based on the time stamps and segments; and receiving a time series search request; and executing the time series search request at least in part by searching the time bucketed indices.

19. The method of claim 1 wherein the time series data streams comprise server logs.

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32. A device for recognizing an environmental sound, the device comprising: a client database configured to store a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; a sound sensor configured to capture an input environmental sound; a sound recognition unit configured to: generate an input sound model from the input environmental sound; determine similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; select a first label from one or more labels, of the plurality of labels, associated with the one or more sound models; and associate the first label with the input environmental sound based on a confidence level of the first label; and a communication unit configured to: if the confidence level is less than a confidence threshold, transmit the input sound model to a server; and receive a second label identifying the input environmental sound from the server.

39. The device of claim 32 , wherein the communication unit is further configured to receive, from the server, one or more server sound models similar to the input sound model, and further comprising: a database updating unit configured to update the client database based on the second label and the one or more server sound models.

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16. The non-transitory computer-readable medium of claim 13 , wherein evaluating a first record and a second record of the pair is at least partially based on information that is external to the first record and the second record of the pair.

13. A non-transitory computer-readable medium storing a set of instructions that are executable by one or more processors to cause the one or more processors to perform a method to associate related records across a first list and a second list to a common entity, the method comprising: obtaining a first list and a second list, wherein the first list and the second list both include a plurality of records, and wherein each of the plurality of records is associated with a respective entity and includes one or more fields; grouping a record of the plurality of records of the first list into one or more first groups based on one or more fields of the record; grouping a record of the plurality of records of the second list into one or more second groups based on one or more fields of the record; pairing a record of the first group with a record of the second group, wherein the record of the first group and the record of the second group were grouped respectively based on similar one or more fields; evaluating, one or more times, a pair; associating, with an entity, the records of a pair, wherein the association is based on assessing the one or more evaluations of the pair.

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15. A system for receiving and processing a claim file and authoring and electronically filing a legal document for a legal action in a court, comprising: an interface configured to electronically receive the claim file in electronic form wherein the claim file includes a plurality of data fields in a native format; a mapping module configured to be executed on an electronic processor, said mapping module being configured to map one or more of the fields of the claim file from the native format to a desired format different from the native format to form a modified claim file; a rules block configured to be executed on the processor and further configured to select a court based on data included in the modified claim file and predetermined court selection criteria; a legal document authoring block configured to be executed on the processor and configured to produce a legal document in electronic form configured for electronic filing in the selected court using the modified claim file and predetermined filing requirements data associated with the selected court; and a court filing block configured to be executed on the processor and configured to electronically file the generated legal document in the selected court.

16. The system of claim 15 further comprising: means for validating a legal claim based on at least the modified claim file and predetermined rules and documentation requirements associated with the selected court.

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10. A computer storage device storing computer-executable instructions that, when executed on one or more processors, perform operations comprising: segmenting an image into objects; assigning a value to each of the segmented objects, wherein the value is corresponds to a likelihood of an object being recognized by humans; identifying an object such that the image surrounding the object visually associates the object as being a part of the image; selecting the object for the object recognition; cropping the object from the image, wherein the object is expanded beyond a boundary of the image without conveying a contour of the object; filling a region on the image where the object has been cropped; and generating candidate objects that have similar low level features to the object cropped from the image, wherein the low level features are features that are determined to be recognizable by a computer.

12. The computer storage device of claim 10 , wherein segmenting the image into objects comprises: dividing the image into segments; merging neighboring segments that have low level features that are similar to the low level features of the segments; determining when the segment is smaller or larger than a predetermined size: in response to determining that the segment is smaller than the predetermined size and does not fit a shape requirement, merging the segment with a neighboring segment; or in response to determining that the segment is larger than the predetermined size, partitioning the segment into two separate segments by evaluating a shape and an area of resulting segment and to separate the segment along parts that are different in appearance; and classifying the segments into foreground segments and background segments, wherein the foreground segments are used as the objects for object recognition.

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1. A system configured to utilize semantic analysis to set a processing level for processing measurements of affective response, comprising: a semantic analyzer configured to: receive a first segment of content, analyze the first segment utilizing semantic analysis, and output a first indication that a first value related to a predicted emotional response to the first segment does not reach a first predetermined threshold; wherein the first segment comprises data representing text; and a hardware-based controller configured to select, based on the first indication, a first processing level for a processor to process measurements of affective response of a user to the first segment; wherein the semantic analyzer is further configured to: receive a second segment of content, analyze the second segment utilizing semantic analysis, and output a second indication that a second value related to a predicted emotional response to the second segment reaches a second predetermined threshold; wherein the second segment comprises data representing text; wherein the hardware-based controller is further configured to select, based on the second indication, a second processing level for a processor to process measurements of affective response of the user to the second segment; wherein, per volume unit of measurement data, the number of computation cycles utilized by the processor to process, at the first processing level, the measurements of the affective response of the user to the first segment, is at least 50% lower than the number of computation cycles utilized by the processor to process, at the second processing level, the measurements of the affective response of the user to the second segment.

10. The system of claim 1 , wherein the semantic analyzer evaluates the second segment shortly before the user is exposed to the second segment, whereby shortly is less than one minute.

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9. The method of claim 3 , further including routing said components to said reviewer, wherein each of said components is individually routed.

3. The method of claim 1 , further including: receiving, at a content management application, a request to create updated content for a content page within said company website, wherein said updated content comprises components; creating said components according to said request; storing each of said components within a markup language file globally accessible by a reviewer, wherein said components are decoupled from said content page; and, creating an updated content page when each of said components has been authorized, wherein said updated content page does not include said components and comprises said content mapping data.