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1. A computer-implemented method comprising: building an event model by identifying, from user data of one or more applications associated with a user, events related to the user; receiving a voice input from the user that includes a command to perform a specific action, the action having a plurality of parameters, and each parameter specifying information necessary to perform the action; determining whether the voice input includes sufficient information to perform the action; in response to determining that the voice input does not include sufficient information to perform the action, identifying one or more missing parameters from the voice input that are required to perform the action; identifying, using the event model, one or more current or future events related to the user that are relevant to the action, wherein each current or future event either is (i) currently occurring relative to a time when the voice input was received or (ii) will occur in the future relative to the time when the voice input was received; customizing the action based on the one or more current or future events, comprising assigning values to one or more of the identified missing parameters of the action based on data associated with the one or more current or future events; and performing the customized action in response to the voice input.

5. The method of claim 1 , wherein: identifying, using the event model, one or more current or future events related to the user that are relevant to the action comprises: identifying user data from the event model that is potentially relevant to the action; determining a level of confidence for an association of one or more potentially relevant current or future events from the identified user data and the context of the voice input; and identifying one or more current or future events related to the user that are relevant to the action from the potentially relevant events based on the determined level of confidence.

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5. A method according to claim 4, further comprising the step of: creating an entry in a stack for the predetermined hierarchical level and the first subsequent hierarchical level of the document, each entry in the stack including a reference to a set of references corresponding to structure of a corresponding hierarchical level and used during processing of the corresponding hierarchical level, and including a reference to a set of references corresponding to content of a corresponding hierarchical level and used during processing of a content portion of the corresponding hierarchical level.

4. A computer implemented method for processing a hierarchically structured document, comprising the steps of: creating a first state variable table having a first set of state variables; creating a first reference to the first state variable table, said first reference to the first state variable table being associated with a structure portion of a predetermined hierarchical level of the document; creating, for said predetermined hierarchical level of the document when a content portion of said predetermined hierarchical level is processed, a second state variable table and copying the first set of state variables to a second set of state variables of the second state variable table; processing a structure portion of a subsequent hierarchical level, wherein said subsequent hierarchical level is lower in the hierarchical structure of the document than the predetermined hierarchical level; determining if processing of content of said predetermined hierarchical level is in process; copying the second reference to a third reference associated with structure of the subsequent hierarchical level, when said processing of content for said predetermined hierarchical level is determined to be in process; copying the first reference to the third reference associated with the structure of the subsequent hierarchical level, when said processing of content for said predetermined hierarchical level is determined not to be in process; creating, for said subsequent hierarchical level of the document when a content portion of said subsequent hierarchical level is processed, a third state variable table referenced by a fourth reference and copying the set of state variables referred to by the third reference to the third state variable table; processing said content portion of said subsequent hierarchical level using said fourth reference to the third state variable table; and continuing processing of said content portion of said predetermined hierarchical level after processing of said content portion of said subsequent hierarchical level is complete, using said second reference to said second state variable table, when said processing of content for said predetermined hierarchical level is determined to be in process.

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1. A computer-implemented method of conducting a search of electronically stored information, comprising: (a) providing a user with an interactive targeting rule editor to enable the user to formulate a targeting rule to identify desired search results, the targeting rule comprising a natural language text string, the interactive targeting rule editor allowing the user to change one or more designated editable portions of the natural language text string to one of a set of specified alternate portions to form a syntactically valid targeting rule in accordance with a targeting rule grammar, wherein at least one of the specified alternate portions includes one or more further designated editable portions that are changeable by the user to one of a further set of specified alternate portions to form the syntactically valid targeting rule; (b) receiving the text string or a representation thereof from the user; (c) translating the text string or a representation thereof into an executable query; and (d) executing the executable query against the electronically stored information to generate search results.

2. The method of claim 1 further comprising step (e) transmitting the search results to the user, storing the search results, or performing additional processing or analysis on the search results.

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1. A method for capturing video presentations, the method comprising: detecting, performed by one or more microprocessors, when a video presentation has begun by analyzing an incoming video stream; determining whether a presentation element in the video presentation is static or dynamic in response to detecting that the video presentation has begun; generating an image from the presentation element when the presentation element is static; generating a video clip from the presentation element when the presentation element is dynamic; extracting textual content of the presentation element from the image; associating a plurality of weights with a plurality of text of the textual content of the presentation element based on types of the plurality of text such that a first weight is associated with a first text of the plurality of text that is not a title of the presentation element and a second weight is associated with a second text of the plurality of text of the presentation element, the second weight being greater than the first weight and associated with the second text in response to determining that the second text is a title of the presentation element, the first text and the second text being weighted textual content; receiving supplemental content corresponding to the image or the video clip; storing the weighted textual content and the supplemental content in a searchable index; detecting when the video presentation has stopped by analyzing the incoming video stream; and stopping the generation of the video clip and the image in response to detecting that the video presentation has stopped, wherein in response to the extracted textual content associated with the image, stored in the searchable index, matching a search query: audio content is extracted from the generated video clip, and the audio content associated with the image is played and returned in response to the search query.

3. The method of claim 1 , wherein when at least one of the extracted textual content associated with the image, stored in the searchable index, matches a search query, the image is displayed and returned in response to the search query.

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11. A broadcast program retrieval method according to claim 10 , further comprising: processing and storing in the keyword database any changes made to said other information related to said plurality of broadcast programs.

10. A broadcast program retrieval method according to claim 8 , further comprising: configuring a keyword database in the data server, said keyword database including a plurality of keywords; and using said plurality of keywords to match said at least one content keyword received from the user server.

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1. A method of constructing a model of recognizing English pronunciation variations, applying to a computer connected to a non-transitory recording medium, for recognizing English pronunciations with intonations influenced by different non-English native languages, the method at least comprising: 1) providing a plurality of English expressions and at least one phonetic alphabet corresponding to each of the English expressions by the non-transitory recording medium, and collecting a plurality of corresponding sound information according to the phonetic alphabet of each of the English expression by the computer; 2) corresponding phonetic alphabets of the non-English native language and English to a plurality of international phonetic alphabets (IPAs) by the computer, so as to form a plurality of pronunciation models, wherein the computer forms each pronunciation models; 2-1) collecting a plurality of phonetic alphabet pronunciations directed to one of the IPAs, and converts each of the phonetic alphabet pronunciations into a corresponding characteristic value; 2-2) forming the characteristic values into a value group and calculates a grouping threshold value corresponding to the characteristic values; 2-3) calculating the computer calculates a mean value of the value group; 2-4) obtaining a first characteristic value from the value group which is away from the mean value by a maximum numerical distance; 2-5) calculating a second characteristic value in the value group which is away from the first characteristic value by a maximum numerical distance; 2-6) calculating numerical distances, wherein a first distance is calculated between each characteristic value and the first characteristic value and a second distance is calculated between each characteristic value and the second characteristic value, and forming value groups by the first distances and the second distances, one of the two value groups containing the characteristic values close to the first characteristic value and the other one of the two value groups containing the characteristic values close to the second characteristic value, respectively; 2-7) obtaining a within-group distance and a between-group distance of the two value groups, so as to calculate a grouping standard; and 2-8) determining whether the grouping standard is higher than the grouping threshold value through comparison, if yes, calculating each mean value of the two value groups and then, the step 2-4) to the step 2-8) are repeated for each one of the two value groups respectively, and if no, obtaining each value group of the pronunciation model that the computer want to form; 3) converting the sound information of each of the English expressions by using the pronunciation models, and constructing a pronunciation variation network corresponding to the English expression with reference to the phonetic alphabet of the English expression by the computer, so as to detect whether each of the English expressions has a pronunciation variation path; and 4) summarizing each of the pronunciation variation paths to form a plurality of pronunciation variation rules by the computer.

5. The method of constructing a model of recognizing English pronunciation variations as claimed in claim 1 , wherein the step of constructing a pronunciation variation network corresponding to the English expression comprises: setting the phonetic alphabet of the English expression as a reference; detecting whether an insertion pronunciation variation exists in each pronunciation of the phonetic alphabets of English; detecting whether a deletion pronunciation variation exists between each phonetic alphabet and its next phonetic alphabet; detecting a substitution pronunciation variation corresponding to each phonetic alphabet; and constructing the pronunciation variation network.

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18. The method of claim 16 , wherein additional programming languages are able to interface with the model based spreadsheet scripting language in the program.

16. A method of representing a spreadsheet, comprising the following steps: executing a program that defines a plurality of formulas, the program written in a model based spreadsheet scripting language whereby values of the plurality of formulas change repeatedly when a first variable in one of the plurality of formulas changes repeatedly, the program comprising a textual representation of at least a portion of the spreadsheet and the plurality of formulas contained in the spreadsheet, the spreadsheet comprising a first cell having a first value that is model-based and that is recalculated when the first variable changes, the model based spreadsheet language incorporating procedural elements for calculation of spreadsheet values and thereby enabling a second cell having a second value that is not model-based and that is recalculated in response to selection of a reset function; and implementing the procedural elements into the program to define order therein.

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21. The method of claim 13 wherein the personal electronic device is a cell phone.

13. A method of performing speech recognition comprising: receiving, by the kiosk from a personal electronic device, an identifier specifying a user of a kiosk; retrieving history information about the user using the identifier, wherein at least a portion of said history information is stored with said identifier on the personal electronic device; receiving speech input; recognizing said speech input in the context of a first recognition set, resulting in first recognition results; and modifying the first recognition results using the history information; wherein the kiosk writes history information to said personal electronic device after a transaction.

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4. The computer program product as recited in claim 1 , wherein said event or action logical construct comprises one or more of the following: default event input field, default event output field, action data input field and action data output field for subsequent manual instantiation of event logical construct data inputs and action logical construct data outputs.

1. A computer program product embodied in a computer readable storage medium for construction of rules for use in a complex event processing application program, the computer program product comprising the programming instructions for: providing a rule construction interface for constructing rules for a rule set of a complex event processing system, said rules comprising definitions of one or more detected events and corresponding actions, said interface being arranged to enable a user definition of new events or actions during a rule construction process; in response to an identification of a new event or action during said rule construction process via said rule construction interface, generating a corresponding event or action logical construct for representing said event or action in said complex event processing system; generating an intermediate logical construct arranged to provide a data connection for said event or action logical construct; and linking said event or action logical construct to a corresponding action or event logical construct via said intermediate logical construct.

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19. The non-transitory machine-readable storage media of claim 18 having additional instructions for requesting an ontology and vocabulary from an ontology-store component of the content-search-service system, using the category ID and date or date/time indication and requesting a transcript from an extracted-content-storage component of the content-search-service system using the received content ID.

18. The non-transitory machine-readable storage media of claim 17 having additional instructions for requesting a category ID and date or date/time indication that corresponds to the received content ID from a media-data-storage component of a content-search-service system.

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24. The computer program product of claim 22 , wherein the instructions for assigning the popularity score to each of the set of placed content includes instructions for multiplying the scaling factor, the respective click through rate and the respective bid value.

22. The computer program product of claim 19 , further including instructions for associating the similarity score with a scaling factor.

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13. A system according to claim 10 , wherein a device of the set is a local server.

10. A system comprising: a set of devices, at least one device of the system being arranged: to receive a real-world description in the form of an instruction set of a markup language, the real-world description including asset terms and effect terms, to request assets associated with the asset terms and effects associated with the effect terms according to the terms in the real-world description, and to modify at least one asset associated with an asset term in the real-world description according to at least one effect identified by associated with an effect term in the real-world description, the devices of the set being operated according to the at least one modified asset.

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13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving audio data corresponding to an utterance that is spoken by a user of a device and that includes a voice command trigger term and an entity name that is a proper noun; generating, by an automated speech recognizer, a first phonetic representation of a first portion of the utterance that is associated with the entity name that is a proper noun, wherein the first phonetic pronunciation does not phonetically correspond to a previously available phonetic pronunciation of the entity name; generating, by the automated speech recognizer, an initial transcription that (i) is based on the first phonetic representation of the first portion of the utterance, and (ii) includes a transcription of a term that is not a proper noun; in response to the generation of the initial transcription that includes a transcription of the term that is not a proper noun, prompting a user for feedback, wherein prompting the user for feedback comprises: providing, for output to the user on a graphical user interface of the device, a representation of the initial transcription that (i) is based on the first phonetic pronunciation of the first portion of the utterance, and (ii) includes the transcription of the term that is not a proper noun; providing, for output to the user on the graphical user interface, multiple entity names from a set of entity names stored in the pronunciation dictionary, wherein the multiple entity names that are provided for output on the graphical user interface include both (i) entity names that are phonetically close to the entity name included in the utterance, and (ii) entity names that are phonetically unrelated to the entity name included in the utterance; and receiving data corresponding to a selection by the user of a particular entity name of the multiple entity names; generating a different transcription based on the received data corresponding to the particular entity name selected by the user, wherein the different transcription includes an entity name that does not phonetically correspond to the first phonetic representation; updating the pronunciation dictionary to associate (i) the first phonetic representation of the first portion of the utterance that corresponds to the portion of the utterance that is associated with the entity name that is a proper noun with (ii) the entity name in the pronunciation dictionary corresponding to the different transcription that does not phonetically correspond to the first phonetic representation; receiving a subsequent utterance that includes the entity name; and transcribing the subsequent utterance based at least in part on the updated pronunciation dictionary.

14. The computer-readable medium of claim 13 , wherein updating a pronunciation dictionary further comprises: identifying a pronunciation dictionary entry that is associated with the entity name; deleting the portion of the entry that corresponds to a phonetic representation of the initial transcription; and storing, in the pronunciation dictionary entry that is associated with the entity name, the phonetic representation that is associated with the first phonetic representation.

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25. A recordable-type computer-readable storage medium storing computer-readable instructions that, when executed, implement the method recited in claim 1 .

1. In a system including a television and a video transmission medium, wherein interactive broadcast data text descriptions such as electronic program guide information, news headlines, sports scores, or other similar kinds of periodically updated information that can be displayed as text simultaneously with other programming is transmitted across the video transmission medium, and wherein the system also includes a management system having a digital processor for processing one or more unique digital signatures that correspond to the interactive broadcast data, and an input device for inputting other digital data that corresponds to user instructions input by a user when searching for particular interactive broadcast data, a method for efficiently searching the interactive broadcast data in response to a string of text input by a user in order to identify the particular interactive broadcast data desired by the user, the method comprising: receiving interactive broadcast data at the management system, said interactive broadcast data having unique binary signatures, each unique binary signature generated for an electronic program guide entry using programming information from a plurality of information fields of the electronic program guide entry, wherein each of the unique binary signatures is created prior to transmission across the video transmission medium using a first function adapted to convert alphanumeric text in fields of the electronic program guide entries into unique binary signatures having a fixed number of bytes, wherein at least one of the unique binary signatures includes a plurality of distinct four bit binary representations corresponding to a plurality of distinct terms found within a single electronic program guide entry, with each of the distinct four bit binary representations in the unique binary signature corresponding to a distinct term, and with all of the distinct four bit binary representations being concatenated into a single binary signature comprising the fixed number of bytes, storing the unique binary signatures at the management system; receiving a first user-entered text string; using a second function to convert the first user-entered text string into a unique binary signature; retrieving and comparing the stored unique binary signatures corresponding to the interactive broadcast data text descriptions to the unique binary signature of the user-entered text string; and based on the comparison, the management system identifying at least one item of interactive broadcast data that matches the user-entered text string.

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19. The machine-implemented system of claim 14 , wherein the encrypted search and the encrypted search return instructions are both originally produced by the principal.

20. The machine-implemented system of claim 19 , wherein decrypted version of the encrypted search and the encrypted search return instructions are extensible markup language (XML) encoded documents.

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1. A method to identify regions, the method comprising: receiving an image of a scene of real world; creating a plurality of sets of positions automatically, by at least performing comparisons using multiple pluralities of pixels hereinafter compared pixels that are located in the image at corresponding positions comprised in the plurality of sets of positions; wherein a first set in the plurality of sets of positions is created without using in any comparison, a plurality of pixels hereinafter skipped pixels that are located in the image at additional positions comprised in the first set; wherein a first region identified by the first set is contiguous in the image, the first region comprising the compared pixels and the skipped pixels identified respectively by the corresponding positions and the additional positions; wherein a second region is contiguous in the image, the second region being identified by positions in a second set, in the plurality of sets of positions created by the creating; checking automatically, whether a test is satisfied by a first attribute of the first region and a second attribute of the second region; preparing automatically, a merged set comprising the positions in the first set and the positions in the second set, based on at least an outcome of said test; and storing automatically, in one or more memories, the merged set; wherein the receiving, the creating, the checking, the preparing and the storing are performed by one or more processors coupled to the one or more memories.

6. The method of claim 1 wherein: comparisons performed by said performing are between an intensity i used as a threshold and the intensity of each pixel included in a region Qi among the first region and the second region; said region Qi comprises a local extrema in said image; and said region Qi is maximally stable relative to changes in a range i−Δ to i+Δ, with a local minima in ratio [Qi−Δ−Qi+Δ]/Qi occurring at the intensity i.

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24. A computer-implementable method for reconciling names, of enterprise computer resources, in a Configuration Management Database (CMDB), said computer-implementable method comprising: creating a resource that belongs to a class of resources that comprises multiple prioritized naming rules; in response to determining that more than one set of naming attributes is provided by the multiple prioritized naming rules, creating a set of valid names, in a validity priority order, for the resource, where the validity priority order is based upon the prioritized naming rule used to create each valid name; and correlating different names for the resource by, in accordance with the validity priority order, assigning one name for the resource to be a master name and assigning all other names for the resource to be alias names.

28. The computer-implementable method of claim 24 , further comprising: in response to determining that a duplicate name instance was a superior naming context of another resource stored in a CMDB table, constructing a valid name for said other resource using a newly selected master name.

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1. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one non-signature information field of the document, comparing, using the computer system, handwriting in the non-signature information field to at least two handwriting profile representations from at least one non-signature information field of at least one other document, wherein writing in at least one of the information fields of the document comprises at least two examples of a type of handwritten information, and further comprising comparing at least two of the examples to assess whether two or more of the examples approximately match.

16. The method of claim 1 , wherein the handwriting comprises at least one image.

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54. The apparatus of claim 52 , wherein the returned web page includes results returned from the query submitted to the search engine.

52. An apparatus comprising: means for receiving, through a hardware input device, text input within an integrated search field of a web browser application; means for determining, based on characteristics of the text input, whether the text input triggers an automatic submission of a query to a search engine; means for determining, based on characteristics of the text input, whether to delay the trigger for automatic submission, wherein the query is automatically submitted to the search engine if the text input satisfies a temporal trigger, wherein the temporal trigger is based upon a connection speed to the search engine; means for automatically submitting the query to the search engine, the query based on the received search input; means for displaying, within the web browser application, a web page returned from the search engine based on the query; and means for automatically maintaining a focus within the integrated search field after the returned web page is displayed, the focus designating where the text input is directed.

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1. A computer-implemented method for assessing a traumatic brain injury (TBI) in a patient, the method comprising: obtaining diffusion magnetic resonance imaging (dMRI) data from the patient; obtaining resting-state functional magnetic resonance imaging (rs-fMRI) data from the patient; extracting connectivity features between different regions of a brain of the patient, the connectivity features extracted from the rs-fMRI data obtained from the patient and/or from the diffusion magnetic resonance imaging (dMRI) data obtained from the patient; extracting network features from the connectivity features; and determining a TBI diagnosis for the patient based on at least the network features and the connectivity features using a trained classifier.

4. The computer-implemented method of claim 1 , wherein the determining is further based on phenotypic features of the patient, genetic features of the patient, medical history of the patient, or combinations thereof.

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12. A system, comprising: one or more computers; and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: storing, in a translation repository, translation data representing changes to translations during a time interval between a first time and a second time, the translation data identifying text messages in a first language, respective identifiers for each of the text messages, and corresponding translations of a plurality of the text messages into a second language, including one or more of the respective identifiers in a source code project; building the source code project into a reference application in the second language, comprising: replacing the identifier of each text message in the source code project with a translation of the text message in the second language made at the second time, and for a text message whose translation has changed during the time interval, inserting the identifier of the text message whose translation has changed as hidden information associated with the translation of the text message, wherein the identifier for a text message whose translation has not changed during the time window is not inserted as hidden information associated with the translation of the text message in the reference application; and rendering the reference application for presentation to a user for translation checking, including highlighting the text messages that have an associated hidden identifier.

14. The system of claim 12 , the operations further comprising generating message change data that identifies, for a particular text message, a translation of the particular text message in the second language made at the first time and a translation of the particular text message in the second language made at the second time.

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13. A non-transitory computer-readable memory having stored thereon a sequence of instructions which, when executed by a processor, cause the processor to: access a data source to obtain data about a suspicious activity; obtain, by downloading, using a master computer, the data from the data source, the data about the suspicious activity; ascertain, by parsing the obtained data, a uniform resource locator that relates to the suspicious activity, wherein the uniform resource locator is associated with an anchor, the anchor comprising a displayed address; ascertain the displayed address indicated by the anchor associated with the uniform resource locator; ascertain an actual address associated with a server referenced by the uniform resource locator; compare the displayed address with the actual address associated with the server referenced by the uniform resource locator, wherein the displayed address comprises at least one of a first domain and a first interne protocol (IP) address, and wherein the actual address associated with the server referenced by the uniform resource locator comprises at least one of a second domain and a second IP address, and further wherein the instructions cause the processor to determine whether the displayed address is different than the actual address associated with the server referenced by the uniform resource locator by performing at least one of a comparison between the first domain and the second domain, and between the first IP address and the second IP address; obtain, using the master computer, domain information about the displayed address; obtain, using the master computer, WHOIS ownership information about the displayed address; compare the obtained domain information about the a displayed address with the WHOIS ownership information about the displayed address; and determine, based on the comparison of the obtained domain information about the address configured to be displayed with the WHOIS ownership information about the displayed address and the comparison of the displayed address with the actual address associated with the server referenced by the uniform resource locator, whether the uniform resource locator is fraudulent.

24. A computer-readable memory as recited in claim 13 , wherein the WHOIS ownership information about the displayed address comprises information about an owner of the displayed address.

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9. The system of claim 8 further comprising: the matching function that generates the match, wherein the match is generated in response to a search request.

8. A computer-implemented people matching system comprising one or more processor-based devices configured to execute: a computer-implemented function that assesses a first location associated with a first user and a non-temporal environmental condition local to the first user; a computer-implemented function that assesses a second location associated with a second user; and a matching function generates a match between the first user and the second user based, at least in part on the first location, the second location, and the environmental condition.

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7. The computer-implemented method of claim 6 , further comprising sorting the common candidate word and the geographic-related language candidate word based on a sorting factor of a candidate word.

9. The computer-implemented method of claim 7 , wherein the sorting factor further includes an association degree of application program environment information and a geographic position.

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1. A computer-implemented speech recognition method for selecting a combination of list elements via a speech input having a first portion and a second portion, wherein a first list element of the combination is part of a first set of list elements and a second list element of the combination is part of a second set of list elements, the method comprising: receiving at a processor the speech input; comparing within the processor each list element of the first set of list elements with the first portion of the speech input to obtain a first candidate list of best matching list elements; processing the second set of list elements using the first candidate list to obtain a subset of the second set of list elements; comparing each list element of the subset of the second set of list elements with the second portion of the speech input to obtain a second candidate list of best matching list elements; and selecting a combination of list elements using the first and the second candidate lists wherein selecting a combination of list elements comprises: determining combinations of a list element of the first candidate list with a related list element of the second candidate list; scoring each determined combination by combining the score of the list element of the first candidate list and the score of the related list element of the second candidate list; determining a result list wherein the result list comprises best matching combinations of a list element of the first set of list elements and a list element of the second set of list elements; and comparing each combination of the result list with the speech input to determine a score for each combination, thereby obtaining a pruned result list, wherein the first candidate list, the second candidate list, the result list and the pruned result list comprise a maximum number of list elements, in particular wherein the maximum number of list elements of the first candidate list, the second candidate list, the result list and the pruned result list are determined based on the length of the speech input.

6. The method according to claim 1 , wherein the first set and the second set correspond to different categories, in particular, wherein each list element of the first set corresponds to a first category and each list element of the second set corresponds to a second category.

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8. The computer storage medium of claim 5 , wherein the context data includes at least one of application specific data, environmental data, or user status data.

10. The computer storage medium of claim 8 , wherein the user status data includes data collected from personal web services used by the user that provide implicit or explicit clues regarding the emotional state of the user.

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5. The method of claim 4 wherein implementing the model transformation capabilities of IBM Rational Software Architect™ further comprises configuring a plurality of rule classes; and executing one of the plurality of rule classes when a different type of Unified Modeling Language element is encountered.

4. The method of claim 3 wherein implementing the model transformation capabilities of IBM Rational Software Architect™ further comprises executing a visitor-like pattern for iterating over all of the Unified Modeling Language elements in the Unified Modeling Language diagram.

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1. A method operable on an electronic device, comprising: during media playback, detecting an event; initiating output of a first indication of the event, wherein the first indication is a first audio overlay on top of the media playback and indicates that speech recognition is available for a predefined period of time; determining an event type from a plurality of event types, wherein each of the plurality of event types is associated with a set of speech commands; determining a set of speech commands associated with the event type; executing a speech recognition application to process speech commands associated with the event and to provide options to the user for controlling the electronic device, wherein executing the speech recognition application includes initiating a speech recognition engine using the set of speech commands associated with the event type; initiating output of a second indication of a state of readiness to process speech commands in association with the event, wherein the second indication is an audio overlay on top of the media playback; identifying a recognized speech command from a set of expected speech commands using custom speech recognition grammar based on the event; and in response to identifying the recognized speech command: pausing the media playback; and executing the recognized speech command.

11. The method of claim 1 , wherein the event comprises at least one of an incoming message, an incoming call, a user-initiated event, a calendar event, or a reminder.

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3. The method of claim 1 , further including: receiving a location from the portable device; and using at least the location and the identified sampled audio content to target the portable device for advertising or offers.

1. A method of identifying an audio content sample that originates from an actual broadcast, including: monitoring a plurality of broadcast stations, fingerprinting and saving the fingerprints of broadcast audio content in a database of unidentified broadcast content as it is received; accessing playlists, comprising portions of identified broadcast audio content from the plurality of monitored broadcast stations, and fingerprints corresponding to the identified broadcast audio content; receiving data representing sampled audio content from a portable device and searching for a match between fingerprints of the sampled audio content and the fingerprints corresponding to at least parts of multiple playlists, further including: upon finding a fingerprint match against the fingerprints corresponding to a particular playlist for a particular monitored broadcast station, reporting the particular monitored broadcast station as a source of the broadcast audio content, and a description of the broadcast audio content back to the portable device; and upon not finding a fingerprint match against the fingerprints corresponding to any of the multiple playlists, further searching for a match of the fingerprints of the sampled audio content, against at least one of: parts of the database of unidentified broadcast content from the monitored broadcast stations, to identify a source of the broadcast audio content; and a reference database of identified audio content not associated with a particular broadcast station, to identify the sampled audio content; and reporting back to the portable device at least one of the source of the broadcast audio content and the identity of the sampled audio content.

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14. A computerized system comprising: one or more processors; and a non-transitory computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive a search query from a user input via an interconnected computing network of the computing system; identify an ambiguous term in the search query by utilizing lists of categories from semi-structured data containing the ambiguous term; infer categories of the ambiguous term via extraction on the semi-structured data; for each of the categories inferred for the ambiguous term, compute an amount of network traffic, wherein computing includes calculating a number of webpage views representing each category and a dwell time for each of the webpage views; compute a total amount of network traffic to all of the webpages representing the categories inferred; determine a probability for each category of the ambiguous term based on the amount of network traffic computed for each of the categories and the total amount of network traffic computed for all categories inferred of the ambiguous entity; identify a most probable category of the ambiguous term, wherein the most probable category has a highest probability compared to remaining categories of the ambiguous term; and return search results representing the most probable category of the ambiguous term to a user via a graphical user interface of the computing system based on the probability calculated for each category of the ambiguous term from the amount of network traffic computed for each of the categories and the total amount of network traffic computed for all categories inferred of the ambiguous entity.

19. The system of claim 14 , wherein the non-transitory computer storage media further causes the one or more processors to: omit content for categories inferred having a probability below a minimum probability threshold level.

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12. The model file of claim 11 , wherein the controller refers to one of the multiple groups in the model file.

11. A model file stored on a non-transitory computer readable medium for managing data, the model file comprising: descriptions of the data formatted as a collection of dictionaries, wherein the descriptions of the data are divided into multiple groups that are associated with multiple hierarchical pages in at least two levels, wherein the multiple groups associated with the multiple hierarchical pages are listed in a flat structure, wherein a first entry in a first of the multiple hierarchical pages shares an identifier with a second entry in a second of the multiple hierarchical pages, and wherein, when interpreted by a controller at runtime, the model file causes the controller to: present the data in the multiple hierarchical pages to a user, interpret the multiple groups in the descriptions of the data for the multiple hierarchical pages in the at least two levels, and retrieve data associated with the second entry and display at least a portion of the data associated with the second entry on the first of the multiple hierarchical pages.

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13. The method of claim 10 , wherein the frequency that each of the characters occurs at each position is determined based on a study of a sample of existing passwords.

10. A computer implemented method comprising: under control of one or more processors configured with executable instructions: identifying a language usable for a password; identifying permissible characters that may be used in the password; identifying a maximum character position permissible for the password; determining, for each character position up to the maximum character position, a frequency at which each of the permissible characters is used at the respective character position in words of the identified language; for each position, arranging the permissible characters into character strings based on the determined frequency at which each character is used at the respective position in words of the identified language, such that each character string begins with a permissible character most frequently used at the respective position and ends with a permissible character least frequently used at the respective position; storing the character strings in memory; generating words, one after another, the words having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from the respective character strings stored in memory for that position and in an order based at least in part on a character string, beginning with the character that is most frequently used at the respective position in the words of the identified language; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined.

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5. The energy harvesting communication device of claim 1 , wherein said communication apparatus further disposed with at least one of: a computer apparatus; a signal booster apparatus, said signal booster apparatus further comprises at least one of: a device selected from the group consisting of at least a signal booster that increases signal reception capabilities of the receiver; an amplifier device operable for amplifying signals received by the receiver; a device that improves at least one of signal strength, data transmission speed, download speed, media communications, signal clarity.

1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform.

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1. A computing device configured to identify a concept of a good or service for an unmet market potential, the device comprising: a hardware processor; a non-transitory storage device; a program stored in the storage device; wherein execution of the program by the processor configures the computing device to perform functions, including functions to: read a Global User Search Data (GUSD) comprising information related to a search object; determine an un-successfulness of the search object; assign a first score based on the unsuccessfulness; wherein a higher first score is assigned the more un-successful the search object is; determine from the GUSD one or more locations from which similar search objects originated; assign a second score based on a geographic dispersion of the one or more searcher locations, wherein a higher second score is assigned the higher the geographic dispersion of the one or more locations: identify a morpheme combination in the search object from the GUSD; compare the morpheme combination to a first set of pre-existing terms; assign a third score to the search object based on the comparison, wherein a higher third score is assigned if the morpheme combination is not found in the first set of pre-existing terms; compare an aggregate of the first score, reflecting the un-successfulness of the search object, the second score, reflecting the geographic disparity of the one or more locations from which the similar search objects originated, and the third score, reflecting the likelihood that the morpheme combination is not found in the first set of pre-existing terms, for a search term to a predetermined threshold; and identify the search term as indicative of the concept of good or service for an unmet market potential if the aggregate of the first score, the second score, and the third score is above the predetermined threshold.

6. The computing device of claim 1 wherein execution of the program further configures the computing device to perform functions to: Compare the location to a set of predetermined locations; and Assign a seventh score if the location is found in the set of predetermined locations.

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3. The method of claim 1 , wherein a post on the online social network comprises at least one of: a plurality of posts associated with a conversation on the online social network, a plurality of posts associated with a subset of a conversation on the online social network, a sequence of posts on the online social network, a message posted to the online social network by a user of the online social network, a message posted to the online social network by a third-party application, and an experience that is embedded into the online social network by a third-party application.

1. A method for facilitating handling of a post to an online social network, the method comprising: receiving, by one or more processors, a first post to an online social network from a first user; identifying, by one or more processors, keywords associated with the first post; identifying, by one or more processors, one or more posts similar to the first post based on at least the identified keywords, wherein the identified one or more posts were previously posted to the online social network, wherein identifying one or more posts similar to the first post based on the identified keywords further comprises: utilizing, by one or more processors, Natural Language Processing (NLP) to analyze content, and associated metadata of posts that have been previously posted to the online social network; determining, by one or more processors, one or more posts, of the identified one or more posts, that are: (i) within a predetermined threshold of similarity to the first post, based on at least a comparison between the identified one or more posts and the first post, and (ii) are associated with a response received in the online social network; and determining, by one or more processors, at least one recommendation of an action to perform in the online social network based at least on actions associated with the determined posts that are within the predetermined threshold of similarity and are associated with the determined posts that have received a received response in the online social network, wherein the recommended action is a next action for the first user to perform, subsequent to posting the first post, in the online social network to solicit a response to the first post.

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13. The method according to claim 8 , wherein the extracted information identifies a topic of the input query.

8. A method for generating answers to questions, comprising: receiving an input query; extracting specified information about the input query; obtaining, from an unstructured data source, a plurality of candidate answers to the input query; producing a first score for each of the candidate answers; sending the input query to a model selection module; using the model selection module to use said extracted specified information about the input query to select one of a plurality of scoring models; sending each of the candidate answers to the selected one of the scoring models; using the selected one of the scoring models for weighting the first scores for the candidate answers to determine an answer score for each of the candidate answers; and generating at least one answer to the input query based on the answer scores.

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27. A speech synthesis system as set forth in claim 18, wherein said sound units are allophones.

18. A speech synthesis system as set forth in claim 17, wherein said digital speech data representative of sound units stored in said memory means comprises digital speech formants; said speech synthesizer means being a linear predictive coding speech synthesizer; and further including parameter look-up means interposed between said voice characteristics conversion means and said linear predictive coding speech synthesizer for converting the modified digital speech formants output from said voice characteristics conversion means to digital speech data including digital speech parameters representative of reflection coefficients for input to said linear predictive coding speech synthesizer.

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8. A non-transitory computer-readable medium having stored thereon a sequence of instructions that when executed by a computing system causes, the computing system to perform the steps comprising: obtaining a digital audio file; splitting the digital audio file into a plurality of frames; segmenting the digital audio file into entropy segments based upon an entropy of each frame; performing a blind diarization to identify a first speaker audio file and a second speaker audio file by clustering the entropy segments into the first speaker audio file and the second speaker audio file, wherein the first speaker audio file only contains audio attributed to the first speaker and the second speaker audio file only contains audio attributed to the second speaker; and identifying one of the first speaker audio file and second speaker audio file as an agent audio file and another of the first speaker audio file and the second speaker audio file as a customer audio file; and transcribing the agent audio file and the customer audio file to produce a diarized transcript.

13. The non-transitory computer-readable medium of claim 8 : wherein transcribing the digital audio file comprises applying an agent model to the digital audio file; and wherein identifying one of the first speaker audio file and the second speaker audio file as the agent audio file, comprises comparing the first speaker audio file and the second speaker audio file to the agent model.

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1. A processor-based system to manage template updates by: receiving an update request based in part on an update time, wherein the update request includes a request for one or more links associated with one or more document libraries having one or more templates, wherein the one or more links are targeted to an associated user and point to targets that include the one or more document libraries and associated templates used in part to maintain locally stored templates for the associated user; generating markup data for the one or more templates associated with the one or more links, wherein the markup data includes template parameters, a description, and other information associated with the one or more templates of the one or more document libraries; setting a template synchronization flag to identify a document library to use as part of an update process including associating a first group of users with a first set of document libraries and a second group of users with a second set of document libraries; determining whether to replace a local template with an associated template targeted by a link including comparing a first template parameter of the local template with a second parameter of the associated template of the document library including comparing local template attribute values of the local template with attribute values of the associated template of the document library associated with the link; maintaining the locally stored templates to correspond with new and updated templates associated with the one or more document libraries including determining which parts of a locally stored template require updating based in part on updated aspects of the associated template, including automatically updating the local template based in part on the comparison of the first and second template parameters; and storing template schemas and associated metadata locally with a client as part of the updating.

5. The system of claim 1 , further configured to manage template updates by receiving a client-initiated web service call that includes a request for one or more uniform resource locators (URLs) associated with the one or more document libraries having the one or more templates.

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1. A method for providing input functionality for a speech recognition interaction module, comprising: receiving an indication of a touch anywhere on a touch screen interface of a mobile computing device; upon reception of the indication of the touch anywhere on the touch screen interface, activating a listening mechanism of a speech recognition module; and displaying dynamic visual feedback of a measured sound level of a spoken utterance received by the speech recognition module, wherein the displayed dynamic visual feedback is rendered as centered around an area on the touch screen at which the touch is received.

2. The method of claim 1 , further comprising generating an acknowledgment in response to receiving the indication of the touch anywhere on the touch screen interface of the mobile computing device.

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1. A key-symbol dictionary for learning multi-radical words in a Chinese-character-based language having a set of Chinese radicals, comprising: key-symbol pages each respectively associated with a single Chinese radical within the set of Chinese radicals and having thereon: the single Chinese radical as a symbol; a single keyword corresponding to a given meaning of the single Chinese radical, the single keyword: being in a user's language and having letters in the user's alphabet; and including therein a bridge comprised of at least one of the letters; and a list of memory joggers, each memory jogger being a word in the user's language containing at least the bridge, the list of memory joggers being selected such that a multi-radical word having at least two of the Chinese radicals can be recognized with a mnemonic formed from one memory jogger from each page corresponding to each of the at least two of the Chinese radicals; and the key-symbol pages being ordered alphabetically based on a spelling of the bridge associated with each key-symbol page.

7. The key-symbol dictionary according to claim 1 , wherein each of the Chinese radicals is defined as a source having at least one icon associated therewith, the at least one icon being a Chinese character having a physical similarity to the source.

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11. A non-transitory computer readable storage medium storing code for executing on a computer system to perform the method according to claim 10 .

10. A computer-implemented method for identifying near duplicate documents, comprising steps of: obtaining a set of documents; dividing each document into segments and hashing each of the segments; generating for each hashed segment in each document tuples, each tuple comprising a document identification for the document associated with the segment, a hash code, and a sequence order based on an order in which the segment occurs in that document; comparing the hashed segments of the documents; and designating as near duplicates, two or more of the documents each comprising a different number of hashed segments when a portion of the hashed segments for one of the designated documents matches hashed segments of the other designated documents and the matching hashed segments of the two or more documents occur in a common sequential order; identifying one of the near duplicate documents having one such matching segment with a lower sequence order than the other near duplicate documents; and selecting as an original document the identified near duplicate document having the matching segment with the lower sequence order than the other near duplicate documents, wherein the steps are performed by a programmed computer.

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8. The method according to claim 7 , wherein the set of search terms are received via at least one of a networked search service and desktop search on local storage.

7. A method for generating attribute-based selectable search extensions, wherein a processor is provided to carry out the method comprising: receiving a set of search terms; accessing a set of initial search results based on the set of search terms; identifying at least one attribute of at least one result in the set of initial search results, wherein the at least one attribute identifies a type of file associated with the at least one result; and generating a set of attribute-based selectable search extensions associated with the set of initial search results that reflect outlying attributes within the set of initial search results, wherein generating comprises: (1) assigning the at least one attribute a point in attribute space, wherein the attribute space is defined by axes that are each associated with a respective attribute identified within the set of initial search results, and wherein at least one of the axes represents the type of file; (2) comparing the point associated with the at least one attribute of the at least one result in the set of initial results against an average of points, each associated with attributes identified within other results in the set of initial search results, along an axis of the axes within the attribute space to determine a distance from the average of points; (3) comparing the distance against a threshold; and (4) identifying the at least one attribute as one of the outlying attributes based on the comparison.

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12. A network management system employing at least one hardware processor comprising: a network manager including the at least one hardware processor; a storage device in which the network manager stores a set of design filters; a graphical user interface through which users interact with the network manager; and a network interface through which the network manager obtains information about network devices; the network manager configured to store the set of design filters in the storage device by providing at least one input screen via the graphical user interface; receiving a design filter script via the at least one input screen, wherein the design filter script includes primitives for searching lines and paragraphs in the network device configuration files having specified attributes; converting the design filter script into an executable design filter, the executable design filter configured to implement the searching when executed; and storing at least one of the design filter script or the executable design filter in the storage device; the network manager further configured to receive, via the graphical user interface, user input identifying a selected design filter from among the set of design filters and selecting a plurality of network device configuration files; the network manager further configured to apply the selected design filter to the plurality of selected network device configuration files to produce filtered results, including the filtered results for the plurality of network device configuration files; and the network manager further configured to provide the filtered results via the graphical user interface for display on a user display device, the filtered results provided via a screen having at least two windows arranged side-by-side within the screen, each window including the filtered results associated with one of the plurality of network device configuration files, the filtered results displayed as at least one of individual commands or command lines from the plurality of network device configuration files.

20. A network management system according to claim 12 , wherein the user input selecting the plurality of network device configuration files includes selection of a network element from among a set of network elements presented via the graphical user interface.

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13. The method of claim 10 , further comprising training a classifier based on allograph data.

10. A computer-implementable method implemented by one or more processors executing processor-executable instructions stored in computer storage media to recognize a text, the method comprising: simultaneously comparing, by the one or more processors, (1) a text input to predefined groups of linked letters that are connected based on joining rules for language of the input text to recognize linked letters of the text input, and (2) the text input with one or more constituent letters which form the predefined groups of linked letters; labeling the linked letters of the text input based on relative horizontal overlaps between the linked letters; and extracting features from the text input to recognize the linked letters of the text input utilizing a first classifier to scale the text input to a fixed size grid while maintaining an aspect ratio of the text input and a second classifier based on directional codes associated with the linked letters.

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16. The apparatus of claim 15 , wherein the at least one description for each product comprises marketing information, corresponding to the product offerings, provided by the entity.

17. The apparatus of claim 16 , wherein the marketing information is available via a web page.

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15. The method of claim 14 , further a step of storing the multiple outputs in the parse tree.

14. The method of claim 13 , further comprising a step of creating a parse tree in which to store multiple outputs corresponding to the plurality of input strokes.

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11. The computer program product as claimed in claim 9 , wherein determining the ordered sequence of topical recommendations comprises determining one or more features associated with the structured topic drift using a prediction function in the sequential recommendation model; determining, using the sequential recommendation model, an initial internal state based on the one or more features, wherein the initial internal state is used to determine the ordered sequence of topical recommendations.

9. A computer program product stored on a non-transitory computer-readable medium that when executed by a processor, performs a method of providing a structured topic drift for a displayed set of user comments on an article, comprising: determining an ordered sequence of topical recommendations based on one or more properties of the displayed set of user comments and user characteristics using a sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the ordered sequence to produce a set of one or more user comments; appending, one by one, the one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments; and updating the sequential recommendation model based on a user response to the one or more user comments for each of the topical recommendations; determining a second ordered sequence of topical recommendations using the sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the second ordered sequence to produce a second set of one or more user comments; and appending, one by one, the second set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments.

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8. The machine system of claim 1 wherein: the first presentations include automatically presented invitations to information exchange forums which forums include or have further invited thereto, one or more persons who are topically contemporaneous strangers to the first user, where such topically contemporaneous strangers are persons not known to the first user to contemporaneously have substantially same topics of focus or of interest in their minds as a relatively current topic of focus or of interest that the first user is determined by the machine system to more likely than not have in mind, and the one or more topically contemporaneous strangers are predetermined by the machine system to contemporaneously and more likely than not have substantially same topics of focus or of interest in their minds as the relatively current topic of focus or of interest that the first user is predetermined by the machine system to likely have in his or her mind; wherein said likely topics of focus or of interest are determined by the machine system based on specific sub-portions of respective firstly presented content that the first user and the one or more persons respectively centered their attention upon.

9. The machine system of claim 8 wherein formation of said predeterminations of the likelihoods that the one or more topically contemporaneous strangers have or had substantially same topics of focus or interest in their minds as a relatively current topic of focus or interest that the first user is likely have in his or her mind is carried out by remote servers or by a cloud with which a local portion of the machine system, which is local to the first user, is cooperatively intertwined.

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1. A setting apparatus comprising a caption setting unit for setting a timing of displaying text of speech in synchronization with reproduction of said speech, the text of said speech being predetermined, said caption setting unit comprising: a scenario data obtaining unit for obtaining scenario data representing content of said speech; a speech recognition unit for dividing textual data resulting from recognition of said speech being reproduced to generate a plurality of pieces of recognition data; a character string detection unit for detecting in said scenario data a character string that matches each of said plurality of pieces of recognition data; a character detection unit for detecting a character string that matches the recognition data from said scenario data by detecting a character contained in the recognition data for each recognition data with which said character string detection unit has detected no matching characters string; a display setting unit for setting the display timing of displaying each of the character strings contained in said scenario data to the timing at which speech recognized as a piece of recognition data that matches said character string is reproduce; and a reliability calculating unit for calculating a reliability factor that represents a likelihood that each of the plurality of pieces of recognition data matches one character string, wherein said display setting unit generates a setting that, if the calculated reliability factor associated with a first character string to be displayed in two successive character strings among the plurality of character strings in the scenario data is higher than the calculated reliability factor associated with a second character string to be displayed in the two successive character strings, causes a concatenated character string comprising said first character string with said second character string appended to said first character string to be displayed at a time point at which said first character string should be displayed.

9. The setting apparatus according to claim 1 , wherein said speech recognition unit further generates a speech recognition certainty factor indicating a possibility that each of the plurality of pieces of recognition data resulting from speech recognition matches the content of speech being reproduced; and wherein the character string detection unit further performs in descending order of speech recognition certainty factor: finding in the scenario data a character string that matches a piece of recognition data; and, finding a character contained in the piece of recognition data after determining that it is necessary to detect a character that matches a piece of recognition data for which no matching character string was found; wherein the reliability calculating unit further calculates the reliability of each piece of recognition data, which is the likelihood that the piece of recognition data will match a character string.

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6. A non-transitory computer-readable storage device having computer executable instructions stored thereon, the computer-executable instructions configured to cause a processor to perform acts of: receiving an advertisement with Ad keywords associated with the advertisement; performing a semantic analysis to the plurality of phrases; segmenting content of the advertisement into a plurality of phrases; selecting top-ranked phrases from the plurality of phrases based on the semantic analysis to form a reduced subset of phrases; generating a query list having a plurality of queries by combining each phrase in the reduced subset of phrases that has less than a defined number of words with another independent phrase in the reduced subset of phrases to create queries comprising two or more words; for each query within the query list, performing an internet web search to identify a set of descriptions, each description describing a search result from the internet web search; analyzing the set of descriptions to select a second set of phrases denoted as a query expansion feature set for each query; ranking the second set of phrases within each query expansion feature set and a frequency over all query expansion feature sets; generating an expanded Ad index by selecting from the ranked second set of phrases a subset of phrases as an ad expanded feature set that is combined with the Ad keywords associated with the advertisement; and when receiving a second content for display at a client device, selecting an advertisement from a plurality of advertisements based on the expanded Ad index.

7. The non-transitory computer-readable storage medium of claim 6 , wherein conducting the semantic analysis comprises: grouping related words from the content of the advertisement to generate a phrase from the content of the advertisement; determining a pointwise mutual information (PMI) value for each generated phrase with each Ad keyword; rank ordering the determined PMI values based on a Term Frequency-Inverse Document Frequency (TF-IDF) score for each generated phrase; and selecting from the rank ordering a subset of phrases as the reduced subset of phrases for the advertisement.

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1. A method comprising: receiving, at an online system, a search phrase submitted in association with a user profile with the online system; identifying, by the online system, a first object with a first attribute that is connected to a second object in the online system with a second attribute from the search phrase; generating, by the online system, a structured query corresponding to the first object with the first attribute that is connected to the second object in the online system with the second attribute; performing, at a first time, a first search by the online system identifying a first set of objects with the first attribute that are each connected to another object in the online system having the second attribute; generating, for the structured query, a list of links to the first set of objects; performing, at a second time, a second search by the online system identifying a second set of objects with the first attribute that are each connected to another object having the second attribute; and updating the list of links for the structured query to include links to the second set of objects.

2. The method of claim 1 , further comprising: providing, after generating the list of links to include links to the first set of objects, the first set of objects to the user for display; and providing, after updating the list of links to include links to the second set of objects, the second set of objects to the user.

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8. An apparatus for enhancing the analysis of at least one test word extracted from a test audio source, the test audio source captured within an environment and having an acoustic environment, the apparatus comprising: a computing platform for enhancing the analysis by executing software components; a key phrase extraction component for extracting a training key phrase from at least one training word extracted from a training audio source, and a test key phrase from the at least one test word according to a linguistic rule, an extraction engine for extracting at least one feature from the test audio source or from a training audio source; a key phrase training component for receiving indications and generating a key phrase training model between the training key phrase and the at least one feature, and an indication; and a classification engine for applying the key phrase training model on the test key phrase and the at least one feature, thus obtaining an importance score for the test key phrase.

12. The apparatus of claim 8 wherein the at least one feature relates to a second audio source.

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8. The method of claim 1 , wherein a bookmark link is generated for the particular user in response to the viewing user requesting a page.

9. The method of claim 8 , wherein the requested page is at least one of a home page, a photo album, a message page, an application page, or a profile page.

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12. The system of claim 9 , wherein the signature module further scans the database to create at least one additional behavioral signature by: identifying each behavior exhibited by at least one of the known malicious files maintained in the database; identifying each possible combination of behaviors whose number of behaviors exceeds a behavior threshold.

9. A system for creating behavioral signatures used to detect malware, the system comprising: a database module, stored in memory, that maintains a database that identifies: known malicious files and behaviors exhibited by the known malicious files; known non-malicious files and behaviors exhibited by the known non-malicious files; a signature module, stored in memory, that creates a behavioral signature used to detect malware by: determining a combination of behaviors exhibited by at least one of the known malicious files identified within the database; identifying the number of known malicious files that exhibit each behavior within the combination of behaviors; identifying the number of known non-malicious files that exhibit each behavior within the combination of behaviors; determining that the number of known malicious files that exhibit each behavior within the combination exceeds the number of known non-malicious files that exhibit each behavior within the combination by a certain threshold; incorporating representations of each behavior within the combination of behaviors into the behavioral signature; at least one physical processor configured to execute the database module and the signature module.

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15. The system of claim 13 , wherein the controller processor device further generates task suggestion based on task descriptions, wherein a task description comprises task external description, task properties, task functionalities and task actions.

32. The system of claim 15 , wherein task properties express information useful about the task.

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10. The process of claim 9 , further comprising identifying the preferred entries by applying predetermined criteria as to historical use.

9. The process of claim 2 , further comprising: presenting a collection buffer including, for each segment into which the sequence of key presses has been allocated, a preferred one of said recognized entries spelled out by the key presses of said segment; only for a first one of the segments in order of the sequence, performing operations comprising: presenting a selection list including some alternative dictionary entries spelled out by key presses of the first segment; presenting a list of some logographic Chinese text items phonetically represented by the preferred recognized entry corresponding to the first segment; responsive to receiving user selection of one of the presented logographic Chinese text items, entering the selected item into a displayed output buffer and removing from the collection buffer the letters corresponding to the first segment; responsive to receiving user selection of an entry from the selection list, revising the collection buffer to remove the preferred recognized entry for the first segment and to add the selected entry, and revising the list of logographic Chinese text items to present logographic Chinese text items representing the selected entry.

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10. The product of claim 6 , wherein removing from consideration sub-sequences that do not satify the first set of criteria includes removing sub-sequences that include any combination of: a close tag of a first type without including a preceding open tag of the first type; an open tag of the first type without including a succeeding close tag of the first type; only one tag or more than 200 tags; another sub-sequence that is approximately repeated only once in tandem within the sub-sequence being considered; another sub-sequence that is exactly repeated in tandem at least once within the sub-sequence being considered; and a portion of source code that represents webpage content and, furthermore, is less than 20 characters.

6. A computer program product, tangibly embodied in a machine-readable storage device, for identifying webpage content, the computer program product including instructions to cause data processing apparatus to: receive a string of HTML source code that includes tags; determine the sequence in which the tags occur in the string; use the sequence to identify one or more sub-sequences in which the tags occur in the string, each sub-sequence being associated with a portion of the string that starts with the first tag of the sub-sequence and ends with the last tag of the sub-sequence; determine whether the identified sub-sequences define webpage content constituting an entire webpage listing, the determining including; applying a first set of criteria to filter the identified sub-sequences, the first set of criteria including a requirement that an identified sub-sequence be repeated in tandem, either exactly or approximately, in the string; remove removing from further consideration sub-sequences that do not satisfy the first set of criteria; grouping the remaining sub-sequences into groups, wherein sub-sequences are grouped together in a group when they do not overlap and are similar, as determined by a measure based on edit distance; calculating a score for each group, the score for a group being associated with each sub-sequence in the group, the score being indicative of the likelihood that sub-sequences in the group define webpage content constituting entire webpage listings; identifying overlapping sub-sequences between different groups, wherein identifying includes selecting each sub-sequence in a group and comparing the selected sub-sequence against sub-sequences of other groups for one or more overlapping word tokens; removing from further consideration all identified overlapping sub-sequences between different groups except sub-sequences from the group having a highest associated score among sub-sequences currently selected; and returning and storing the sub-sequences that were not removed from further consideration.

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15. The system of claim 13 , wherein to collate the intent determination responses, the central device is further configured to: receive the intent determination responses from the one or more secondary devices in an interleaved manner; and arbitrate among the interleaved intent determination responses received from the one or more secondary devices and the determined preliminary intent to generate the intent hypothesis associated with the multi-modal natural language input.

13. A system to provide an integrated, multi-modal, natural language voice services environment having an input device, one or more secondary devices, and a central device configured to: receive a multi-modal natural language input from the input device, wherein the input device initially received the multi-modal natural language input; maintain a constellation model and distribute the constellation model to the input device and the one or more secondary devices, wherein the constellation model describes natural language resources, dynamic states, and intent determination capabilities associated with the input device, the central device, and the one or more secondary devices; aggregate the natural language resources, the dynamic states, and the intent determination capabilities associated with the input device and the one or more secondary devices to converge the natural language resources, the dynamic states, and the intent determination capabilities held across the natural language voice services environment; use the converged natural language resources, dynamic states, and intent determination capabilities held across the natural language voice services environment to determine a preliminary intent associated with the multi-modal natural language input; send the multi-modal natural language input to the one or more secondary devices to invoke the intent determination capabilities associated with the one or more secondary devices; collate intent determination responses received from the one or more secondary devices with the determined preliminary intent to generate an intent hypothesis associated with the multi-modal natural language input on the central device; and return the intent hypothesis associated with the multi-modal natural language input and information relating to one or more requests associated with the multi-modal natural language input to the input device, wherein the input device is configured to invoke one or more actions based on the returned intent hypothesis and the information relating to one or more requests associated with the multi-modal natural language input.

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12. The system of claim 9 , wherein obtaining a candidate phrase that includes at least some of the identified subwords as the verification phrase comprises: obtaining multiple candidate phrases including the candidate that includes at least some of the identified subwords; determining that the candidate phrase includes at least some of the identified subwords; and in response to determining that the candidate phrase includes at least some of the identified subwords, selecting the determined candidate phrase as the candidate phrase that includes at least some of the identified subwords from among the multiple candidate phrases.

9. A system comprising: one or more computers; and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a request for a verification phrase for verifying an identity of a user; in response to receiving the request for the verification phrase for verifying the identity of the user, identifying subwords to be included in the verification phrase; in response to identifying the subwords to be included in the verification phrase, obtaining a candidate phrase that includes at least some of the identified subwords as the verification phrase; and providing the verification phrase as a response to the request for the verification phrase for verifying the identity of the user.

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13. The system according to claim 6, wherein said vowel contrasts comprise a pair of vowel speech sounds, wherein each vowel speech sound is paired with all other vowel speech sounds that have a same backness.

6. A speech intelligibility testing system, comprising: a sound device for producing a plurality of stimulus words to be heard by a test subject, each of said plurality of stimulus words comprising a plurality of speech sounds; a display means, configured to display to said test subject a set of selectable word pairs corresponding to a set of contrasting speech sounds whenever a stimulus word is provided to said test subject, each of said words comprising a real word, said set of contrasting speech sounds comprises consonant contrasts and vowel contrasts, a first word of said word pair corresponding to said stimulus word and a second word of said word pair differing from said first word by at least one of said set of contrasting speech sounds; and means for said test subject to select one word of said word pair upon deciding which one of said two words was heard.

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15. A computer program product comprising a computer usable storage medium having stored therein computer usable program code for automatically surfacing tagged content in a vertical application, the computer program computer usable program code, which when executed by a computer hardware system, causes the computer hardware system to perform parsing text from content in an end user application; comparing the parsed text to social bookmarks and associated metadata in a social bookmarking system to determine whether the parsed text matches at least one of the social bookmarks in the social bookmarking system by matching portions of the parsed text to respective ones of the social bookmarks and associated metadata; and, upon determining that the parsed text matches the at least one of the social bookmarks in the social bookmarking system, visually emphasizing the matched portions of the parsed text from the content in the end user application by determining a frequency of match to respective ones of the social bookmarks and associated metadata and adjusting a color of text associated with the matched portions of the parsed text proportionately based upon the determined frequency of match so as to visually differentiate the matched portions from the content.

16. The computer program product of claim 15 , wherein comparing the parsed text to the social bookmarks comprises restricting the parsed text to a limited vocabulary during the comparing.

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13. The method of claim 12 , wherein continuously recording the audio information includes sampling the audio information at a defined sampling rate sufficient to enable extraction of the one or more additional keywords from the audio information.

12. The method of claim 1 , wherein recording the audio information in the overwriteable circular buffer includes continuously recording the audio information in the overwriteable circular buffer by overwriting the oldest audio information with newest audio information upon reaching the limited data storage capacity.

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1. A method for using input signal quality to improve speech recognition, comprising: obtaining quantitative measurements of the quality of an input signal of a speech recognition system, the quantitative measurements including at least a signal-to-noise ratio and a loudness of the input signal; analyzing the quantitative measurements to categorize the quality of the input signal into a qualitative category; and establishing a rejection threshold used in rejecting a speech recognition result for speech included in the input signal in dependence on the qualitative category of the input signal quality, the speech recognition result having a confidence score indicating a level of confidence in an accuracy of the speech recognition result, the rejection threshold establishing which confidence scores indicate that the speech recognition result is to be rejected as being incorrectly recognized.

2. The method of claim 1 , wherein, if the qualitative category of the input signal indicates that the input signal quality is low, establishing the rejection threshold comprises reducing a baseline rejection threshold.

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23. The product summary generator of claim 22 , wherein the recommendation made by the summary generation module is an advertisement for which compensation is received in exchange for recommending the selected alternative product.

22. A product summary generator for automatically generating a self-updating naturally-reading narrative product summary about a selected product, the product summary generator comprising: at least one computer processor; at least one memory device coupled to said at least one computer processor and storing instructions that, when executed by the at least one computer processor define modules, said modules comprising: a summary generation module adapted to evaluate an existing narrative product summary including: reconciling the existing narrative product summary into an existing attribute associated with the selected product, the existing attribute including at least one of an existing attribute name, an existing attribute value, or an existing attribute unit, and resolving forms in the existing narrative product summary to an existing assertion model; an engine module adapted to compare at least one of the existing attribute name, the existing attribute value, the existing attribute unit, and the existing assertion model, respectively, to at least one of a current attribute name, a current attribute value, a current attribute unit, and a current assertion model to determine if at least one of the comparisons shows a change in the attribute name, the attribute value, the attribute unit, or the assertion model; a product attribute module adapted to obtain at least one new attribute associated with the selected product, the at least one new attribute including at least one of a changed attribute name, a changed attribute value, or a changed attribute unit, an alternative product selection module adapted to select an alternative product; an assertion model module adapted to retrieve new assertion models that define forms in which assertions describe the selected product and in which assertions describe the selected alternative product in a natural manner; and the summary generation module further adapted to combine the at least one new attribute with a new retrieved assertion model to describe the selected product in the narrative and to combine the selected alternative product with another retrieved assertion model to recommend the selected alternative product in the narrative.

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4. The computer-implemented system of claim 1 , further comprising at least one device to receive the encoded voice stream and to decode the translated text.

5. The computer-implemented system of claim 4 , wherein the at least one device is capable of presenting a representation of the translated text.

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13. The method of claim 10 , wherein each display area comprises access and control features, the access and control features comprising an option to filter search results; and wherein the method further comprises: in response to selecting an option in a display area to filter the search results, receiving filtered search results from a search engine; and displaying only the filtered search results in the results display area.

14. The method of claim 13 , wherein the search results are filtered based on an action that a member of the social networking service that corresponds to the display area has taken with respect to content associated with the search results, or an association that the member has with the content.

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11. The computer-implemented method of claim 5 , wherein the first hypothesis comprises at least one node representing a number of audio frames corresponding to the first non-speech.

5. A computer-implemented method comprising: determining that received audio data corresponding to at least one utterance includes first audio data, wherein the first audio data corresponds to a first source direction; performing automatic speech recognition processing on the first audio data to determine a first hypothesis including one or more of at least one first word or a representation of at least one first word potentially corresponding to the first audio data; determining that a first portion of the first audio data corresponds to speech; determining a first value representing a first time duration of the first portion of the first audio data; determining a first duration weight factor based at least in part on the first value; determining, in the first hypothesis, a representation of first non-speech, the first non-speech following the first portion of the first audio data; determining a second value representing a second time duration of the first non-speech; determining a first pause duration value by using the first duration weight factor to adjust the second value; and determining an endpoint based at least in part on the first pause duration value.

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26. The computer-implements server according to claim 25 , wherein the processor further executes the application to: apply the criteria to determine at least one of the compatibility and aesthetic attractiveness of each selected graphical visualization to a range of data in the partitioned second data sets; determine a context for each selected graphical visualization in the set of graphical visualizations; and rank each selected graphical visualization in the set of graphical visualizations according to at least one of the criteria and context.

25. The computer-implemented server according to claim 22 , wherein the processor further executes the application to: determine whether each graphical visualization in the set of graphical visualizations corresponds to the data structure; select each graphical visualization in the set of graphical visualizations that is representative of the data structure; and discard each graphical visualization in the set of graphical visualizations that is not representative of the data structure.

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15. The one or more non-transitory storage media of claim 13 , wherein receiving, determining, and removing are performed subsequent to the first search but prior to any subsequent search.

13. One or more non-transitory storage media storing instructions which, when executed by one or more processors, cause: displaying one or more search results from a previous search of a particular database; receiving first input specifying a query of the particular database comprising a first text string comprising one or more terms; processing the query against the particular database by performing a first search of the particular database for the one or more terms; in response to identifying no search results for the query, classifying each of the one or more terms, of the first text string, as a bad term; adding the one or more terms to a first list that is empty before the one or more terms are classified as bad terms; receiving second input that changes the first text string to a second text string; determining whether a particular term in the second text string begins with a term in the first list; in response to determining that the particular term in the second text string begins with a term in the first list, removing the particular term from the second text string; processing the query against the particular database by performing a second search of the particular database for only the second text string without the particular term; in response to identifying no search results based on the second search, incrementing a counter; determining whether the counter is equal to a particular threshold; continuing to display the one or more search results that were displayed from the previous search only if the counter is less than the particular threshold.

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4. The method of claim 2 , wherein the mode is development mode.

2. The method of claim 1 , further comprising: at the processor: receiving the source file for preprocessing, wherein the source file comprises source code and is written in the client-side scripting language; parsing the source file and identifying directive information for the preprocessed directive within the source code of the source file, wherein the directive information comprises: data on the at least the portion of the client-side scripting language file and a mode; and wherein the step of creating comprises: creating the version of the source file for the mode that comprises: the source code from the source file and the at least the portion of the client-side scripting language file.

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13. A system for classifying text on a computer for electronic communication management in a contact center, comprising: means for analyzing, in the computer, text from an electronic communication received from a customer to determine the customer's intent by identifying concepts in the text and building a concept model containing the identified concepts; means for providing, in the computer, a knowledge base having a plurality of nodes including a set of learning nodes, each of the learning nodes being provided with statistical information for determining a relevance of the text to a category associated with the node; means for calculating, in the computer, a set of match scores for the concept model using the knowledge base, each match score of the set of match scores indicating the relevance of the text to a category associated with a node of the knowledge base, the category including at least one suggested action to be performed in response to the electronic communication, wherein the suggested action is representative of the relevance of the text to the category, and the suggested action includes generating an automatic response to the customer or routing the electronic communication to an agent to generate an assisted response to the customer; and means for performing, in the computer, the suggested action in response to the electronic communication based on the calculated set of match scores, in order to improve the response of the contact center to the electronic communication received from customers by the contact center.

15. The system for classifying text of claim 13 , wherein the plurality of nodes further includes a set of rule-based nodes.

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13. A communication system comprising: an audio visual asset recorded by a first user using a predetermined script to communicate with a second user; at least one audio visual segment created by partitioning the audio visual asset such that a variable final message compilation is anticipated; at least one of a naming paradigm and a data tagging system to tag the at least one audio visual segment such that the at least one audio visual segment is accessible via an audio visual data tag and is exported to the variable final message compilation; a multimedia synthesis compiler to compile the variable final message compilation upon uploading of the at least one audio visual segment into the multimedia synthesis compiler; and a message sent to the second user from the variable final message compilation based on the at least one audio visual segment.

15. The system of claim 13 wherein the multimedia synthesis compiler compiles the variable final message compilation such that the final message compilation is outputted in at least one audio visual segment.

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8. The method of claim 5 wherein the one or more audio items are predicted to follow the identified initial audio item based on an observed sequence using previously identified sequences of songs in a multiplicity of audio items.

9. The method of claim 8 , wherein the identified initial audio item is a first song, and the one or more audio items predicted to follow the identified initial audio item includes one or more songs on a same album as the first song.

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17. The apparatus of claim 1 , where the network apparatus is further configured to: obtain a listing of a plurality of possible matches to said speech input, thereby creating an ambiguity; and receive via the wireless interface further digitized representations regarding at least one of the listed plurality of possible matches to resolve the ambiguity.

1. Network apparatus configured to provide information to at least one client apparatus in communication therewith, the network apparatus comprising: a wireless interface; and a network interface in data communication with the wireless interface; wherein said network apparatus is configured to: receive via the wireless interface a digitized representation of a speech input, the digitized representation generated by a speech recognition apparatus of the at least one client apparatus, the input relating to an organization or entity which a user of the at least one client apparatus wishes to locate; forward the digitized representation via the network interface to a server disposed remotely from the client apparatus, for identification by the server of a location associated with the organization or entity, and retrieval of data associated with the location; receive the data, the data relating to a graphical or visual representation of the location, the graphical or visual representation of the location being useful to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and forward the received data to the at least one client apparatus via the wireless interface for display on a display device of the client apparatus.

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18. The non-transitory computer-readable medium of claim 15 , wherein the sets of instructions when further executed by the computer cause the computer to: receive one or more manually generated tags associated with the video file; based at least in part on the one or more manually entered tags, determine a preliminary category for the video file; based on the preliminary category, generate a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generate an ontology of the plurality of words based on the targeted transcript; rank the plurality of words in the ontology based on a plurality of scoring factors; and based on the ranking of the plurality of words, generate one or more automated tags associated with the video file.

15. A non-transitory computer-readable medium having sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive a list of candidate tags for a video file; receive a transcript of audio associated with the video file; rank the list of candidate tags for the video file based on a plurality of ranking factors; filter candidate tags from the list of candidate tags which rank below a threshold value; present the filtered list of candidate tags in a user interface; receive a selection of one or more of the filtered list of candidate tags; receive one or more additional tags; based on the selected one or more of the filtered list of candidate tags and the evaluate the transcript and the one or more additional tags, evaluating the transcript and producing an updated list of candidate tags for the video file; establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file.

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5. A system comprising: one or more processing units; computer-readable memory; instructions stored in the computer-readable memory to implement an asset service, executable on the one or more processing units, to: receive a work by an author; receive an alternate version of the work, the alternate version of the work including a change to the work; and receive data from an author device including a poll asking for indication of a preference between the work and the alternate version of the work; instructions stored in the computer-readable memory to implement a comment module, executable on the one or more processing units, to receive answers to the poll; instructions stored in the computer-readable memory to implement an activity service, executable on the one or more processing units, to create an event based on the asset service receiving the work and to store a record of the event in an author activity log, the event comprising at least an identification of the author, an identification of the work, and a type of the event; and instructions stored in the computer-readable memory to implement a notification service, executable on the one or more processing units, to create a notification about the event and send the notification to a device associated with a user who has previously selected to receive notifications for activities associated with one or more of the author or with the work.

13. The system of claim 5 , further comprising instructions stored in the computer-readable memory to implement a real-time messaging service, executable on the one or more processing units, to pass messages between a first device associated with the author and a second device associated with a contributor that has provided feedback on the work.

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1. A computer-implemented method comprising: receiving, by a computer system on a network, text obtained from a data source on the network, wherein the text includes unstructured data, wherein the text is associated with an item, wherein the item is associated with a plurality of attributes; searching the text, wherein the text is searched using the plurality of attributes, wherein searching includes determining whether the text includes an attribute from the plurality of attributes; determining a plurality of subsets of the text that are associated with a particular attribute from the plurality of attributes, wherein the plurality of subsets of the text include a qualitative assessment of the particular attribute; normalizing the plurality of subsets of the text, wherein normalizing includes reducing the subsets of the text to a common form; determining a plurality of scores for the particular attribute, wherein determining includes using the normalized subsets of the text and a source of the text, and wherein the scores associate the qualitative assessment from each of the normalized subsets of text with a numerical value; determining a resolved score for the particular attribute, wherein the resolved score is determined using the plurality of scores; determining an attribute format for displaying the plurality of attributes associated with the item, wherein determining includes using the resolved score for the particular attribute; displaying the plurality of attributes using the attribute format; determining a score for the item, wherein determining includes aggregating a plurality of scores associated with the plurality of attributes including the resolved score; generating an index, wherein the index includes the resolved score and the plurality of subsets of the text; displaying the plurality of subsets of the text using the index.

7. The computer-implemented method of claim 1 , further comprising: determining a confidence level for each of the plurality of scores; and using the confidence level to assign a weight to each of the plurality of scores, wherein the weight is used to determine the resolved score.

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3. A method according to claim 2 , wherein said intermediary apparatus is an HTTP intermediary.

30. A method according to claim 3 , wherein said intermediary apparatus authorizes said user to perform said editing.

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65. The computer readable storage medium of claim 49 wherein the options area contains a help option.

49. A computer readable storage medium having program code stored thereon, wherein the program code is arranged so that, when the program code is executed by a computer, a note is displayed, the note has an options area, a notation area, and a grab area, and the notation area and the grab area are different areas of the note and so that, when the options area is activated, a list of options is displayed, wherein the options area contains a nonmove option.

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16. The medical decision making support apparatus according to claim 15 , wherein the inference unit obtains an inference result by calculating a posteriori probability of each inference result based on the plurality of elements of medical information in association with a plurality of inference results for which a plurality of priori probabilities are set.

18. The medical decision making support apparatus according to claim 16 , wherein the calculation unit calculates the degree of effect for each of the plurality of inference results, and the presentation unit presents medical information of a partial set for which the degree satisfies a predetermined condition, as one of affirmation information and denial information, for each of the plurality of inference results.

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10. An apparatus for interfacing with a managed device, comprising: a processor configured for: receiving a message including an identifier indicative of a location at which interface information associated with the managed device is stored, wherein the interface information comprises information adapted for use by a management system to interface with the managed device; obtaining the interface information, wherein the interface information comprises an interface routine and a description of the interface routine, wherein the interface routine is specified using an interpreted language, wherein the interface routine description is specified using a descriptive language; and initiating a request to perform a function on the managed device using the interface routine and the interface routine description.

12. The apparatus of claim 10 , wherein the identifier comprises a Uniform Resource Locator (URL).

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15. The method of claim 14 wherein receiving the selection of the template from the plurality of templates comprises receiving a selection of a template for computer-implemented agents that provide online ordering services.

14. The method of claim 1 wherein receiving the data representing the properties of the other computer-implemented agent comprises: providing an entity access to an application programming interface that includes a plurality of templates for different types of computer-implemented agents, each of the templates in the plurality of templates identifying a data flow for computer-implemented agents that indicates a type of response for the other computer-implemented agent given a particular type of input; receiving, for the entity, a selection of a template from the plurality of templates; and receiving, for the entity, a modification to the template that identifies a customization to the data flow of the selected template for the other computer-implemented agent.

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1. A method for reporting traffic information using pre-recorded audio, comprising the steps of: receiving data for a set of traffic incidents, said data including parameters for each of said traffic incidents, one or more of said parameters include at least one code representing a value for said parameter; identifying groups of files that store speech for describing said traffic incidents, each group of files is associated with at least one of said incidents, said step of identifying groups comprises the steps of: for each incident of at least a subset of said traffic incidents, accessing parameters for said incident, and for each parameter of at least a subset of said accessed parameters, identifying one or more files that store speech using a set of information correlating codes for said parameter to references to audio files; and automatically presenting said stored speech from each group of files.

14. A method according to claim 1, further including the step of: adding additional files to said groups, said additional files include filler speech.

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16. The computing device of claim 10 , wherein the removing the character from the image is based at least in part on the homography.

10. A computing device comprising: a processing system including one or more processors; and one or more computer-readable storage media having stored thereon multiple instructions that, when executed by the processing system, cause the processing system to perform acts including: identifying, by the at least one computing device, a region of interest in the image including text; transforming, by the at least one computing device, the region of interest to correct distortion based at least in part on a homography; using, by the at least one computing device, an optical character recognizer to recognize a character based on a detected font used within the text; receiving, by the at least one computing device, a user input to remove the character; removing, by the at least one computing device, the character from the image based on a content aware fill process; and outputting, by the at least one computing device, a result of the removing of the character from the image.

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14. The method of claim 1, wherein automatically generating at the data processing systems the comic panel reflecting the interaction event further comprises automatically generating a plurality of comic panels reflecting the interaction event.

1. In a network including a plurality of data processing systems each having an associated display device, a method comprising: (a) receiving at each of the data processing systems an interaction event generated by any of the data processing systems; (b) automatically generating a comic panel based on the received interaction event, the comic panel providing a graphical representation of an instance in time of a sequential course of events; (c) displaying the generated comic panel on each of the display devices associated with the data processing systems; (d) when an input associated with a graphical representation of a character is received, automatically generating a balloon that includes text that corresponds to the received input associated with the character and automatically generating a tail that is positioned between a position of the balloon and another position for the graphical representation of the character in a current comic panel, the balloon, tail and graphical representation of the character being automatically disposed at positions that are non-overlapping of any other positions for balloons, tails and graphical representations of characters that were previously positioned for display in the current comic panel; and (e) when the input associated with the character is received and non-overlapping positions for displaying the balloon, tail and graphical representation of the character in the current comic panels are unavailable, automatically displaying a new comic panel that includes the balloon, tail and graphical representation of the character, wherein the balloon, tail and graphical representation of the character are disposed at separate positions that are non-overlapping in the display of the new comic panel.

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8. The method of claim 6 , wherein at least one of the telephone, the PDA, and the mobile computing device has a plurality of overloaded keys, each of the overloaded keys representing two or more characters.

6. The method of claim 1 , wherein the selection actions are entered by the user on at least one of a telephone, a PDA, a mobile computing device, a computer, and a remote control.

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15. A system including a continuous speech recognition engine hosted on a server that cooperates with a language identification engine, comprising: an input to receive supplied audio files from a client machine over a wide area network to the server hosting the continuous speech recognition engine; and wherein the language identification engine includes a front end module having an input to receive the supplied audio files, a universal phoneme decoder to identify phonemes and phoneme sequences in the audio files in each of two or more candidate languages, and a run-time language identifier module to receive the phonemes and phoneme sequences from the universal phoneme decoder, generate as an output from the universal phoneme decoder a stream of the identified phonemes and phoneme sequences for each of the two or more candidate languages, wherein the streams include a first stream of phonemes from the identified phonemes for a first of the two or more candidate languages, and a second stream of phonemes from the identified phonemes for a second of the two or more candidate languages, determine a confidence rating on an accuracy of an identification of the first candidate language of the two or more candidate languages for the first stream and an accuracy of an identification of the second candidate language of the two or more candidate languages for the second stream, and identify at least one of a particular spoken human language and a specific dialect of a spoken human language being spoken in the supplied audio files based on the confidence ratings.

18. The system of claim 15 , further comprising: a query input to receive query words of interest from a user of the client machine to a user interface of the continuous speech engine, and an intelligence engine to identify words from the query words and to return a hierarchical rank list of recognized words.

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9. A method of suggesting keywords for a litigation hold, comprising: receiving a seed set of keywords; identifying, by one or more processing devices, a set of documents corresponding to the seed set of keywords; determining an indication of relevance for each document in a subset of the set of documents, wherein the subset comprises a plurality of documents, and wherein the indication of relevance for each document comprises a specified percentage degree of relevance of the document to the seed set of keywords; computing a discriminatory power of the keywords based on the indication of relevance for each document, wherein the discriminatory power of each keyword is determined based on how many relevant and non-relevant documents are yielded based on the respective keyword; generating, by one or more processing devices, a suggested set of keywords with a highest computed discriminatory power, wherein each keyword in the suggested set of keywords occurs within a same portion of a particular one of the plurality of documents that is textually subdivided into two or more portions; and providing the suggested set of keywords to a client, wherein the suggested set is used to perform a further search of the set of documents.

10. The method of claim 9 , wherein each keyword in the suggested set of keywords is linguistically related to one or more keyword in the seed set of keywords.

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5. The method as claimed in claim 1 , wherein the method further comprises: receiving an assessment and grading report for the SQL query, wherein the assessment and grading report comprises at least one of problem comprehension skills of the participant (P), problem solving skills of the participant (P), problem solving speed of the participant (P), resource utilization by the SQL query, and speed of execution of the SQL query.

6. The method as claimed in claim 5 , wherein the assessment and grading report comprises a parameter for plagiarism checking of the SQL query with respect to at least one other submitted SQL query.

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27. The apparatus as recited in claim 24 , at least one of the processor or the memory being further adapted for: comparing the regular expressions of the set of seed examples with the set of candidates to find at least a portion of the set of candidates that each match at least one of the expressions.

24. The apparatus as recited in claim 18 , wherein each of the set of seed examples is represented by a regular expression and each corresponding context includes one or more seed terms, wherein each of the final set of seed examples is represented by a regular expression and one or more seed terms, and wherein adding the selected subset of the set of candidates to the set of seed examples comprises: converting each of the subset of the set of candidates to a regular expression.

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9. The system of claim 8 , wherein the at least one matched document comprises information corresponding to a POI.

8. A system for processing queries for points of interest (POIs) using a map structure with multiple levels, the system comprising: a storage device that stores a set of instructions; and at least one processor configured to execute the set of instructions in order to: determine a weight assigned to each level of the map structure on which at least one match between a query for a POI and a document was found; calculate a geographic score based in part on a distance between a location associated with the query and a location of the at least one matched document; calculate a relevance score based on at least one of information in the query, preference information, or information associated with the at least one matched document; calculate an overall score for each match based on at least one of the weight assigned to the level on which the match was found, the geographic score, or the relevance score; rank documents matched for the query based on the overall scores; and provide a list of the ranked documents.

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2. The method of claim 1 , further comprising selecting, at the task completion handler, missing information from among the identified information, and guiding, at the task completion handler, a conversation to request the selected information, wherein the updated information is received by the dialog manager in response to the conversation requesting the selected information.

3. The method of claim 2 , further comprising: determining that the missing information is not relevant in a context in which the input was provided; and refraining from requesting the determined irrelevant information during the conversation.

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6. The location search method according to claim 5 , further comprising: setting a priority ranking of each of the input candidate character strings, based on priority values assigned in advance to the input candidate character strings; and increasing the priority ranking of the input candidate character string that partially matches the compound character string created by combining the input set character string with the character that is currently being displayed, among the plurality of characters assigned in advance to the button that is pressed next.

5. A location search method comprising: performing a character input process, wherein when one of a plurality of buttons in a character input portion is repeatedly pressed or pressed continuously for a given time or longer, a plurality of characters assigned in advance to the one button is displayed in an input character display portion in a predetermined cyclic sequence; when one of the plurality of buttons is pressed, and then, another of the plurality of buttons is pressed, the character displayed in the input character display portion immediately prior to pressing of the other button is set as an input set character whose input has been set; and when the character is input through the character input portion following the input set character, a character string is input; acquiring a search object character string that partially matches the input character string, as an input candidate character string, from a character string storage portion that stores a plurality of search object character strings; and assigning the input candidate character string to a character string button through which the input candidate character string is input, and displaying the input candidate character string assigned to the character string button; and creating a plurality of compound character strings by combining the input set character string whose input has been set with the plurality of characters assigned in advance to the button that is pressed next, and acquiring the search object character strings that partially match the respective compound character strings, as the input candidate character strings.

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5. The computer-implemented method of claim 1 , wherein the lexicon of known voice inputs is exclusive to the caller.

1. A computer-implemented method of recognizing a voice input received by an interactive voice recognition system, the computer-implemented method comprising: receiving an initial caller voice input from a caller, wherein the initial caller voice input is the caller saying an unintelligible phrase caused by a speech limitation of the caller; a processor determining that the initial caller voice input is a computer-unintelligible voice input that does not match any entry from a lexicon of known voice inputs; prompting the caller to transmit a secondary input to clarify the computer-unintelligible voice input, wherein the secondary input is a dual-tone multi-frequency (DTMF) phone keypad input from the caller that identifies a user-requested activity that the caller was requesting when saying the unintelligible phrase; utilizing the secondary input to match the computer-unintelligible voice input with a specific known voice input from the lexicon of known voice inputs; and updating the lexicon of known voice inputs with the computer-unintelligible voice input, wherein the computer-unintelligible voice input is matched to the specific known voice input from the lexicon of known voice inputs; matching the unintelligible phrase to the user-requested activity in a database that is specific for the caller; receiving the unintelligible phrase in a subsequent phone call from the user; and matching the unintelligible phrase to the user-requested activity for the caller.

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9. The system as claimed in claim 1 , wherein said weighting system assigns a weight to each individual predictor of the plurality of individual predictors based on a percentage of correctly provided suggestions of a total number of suggestions.

10. The system as claimed in claim 9 , wherein said weighting system adapts to multiple data domain types through adjustment of weighting for each individual predictor of said plurality of individual predictors based on past performance.

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8. The method of claim 1 , wherein customizing the user's experience comprises providing a customized search interface.

1. A computer-implemented method for modifying a user's search experience, the method comprising: assigning a first set of symbols that represent a first set of actions initiated by the user during creation of a first search trail; assigning a second set of symbols that represent a second set of actions initiated by the user during creation of a second search trail; determining a measure of interaction variance classification that represents an extent to which there are differences between that first and second sets of symbols, wherein determining the measure of interaction variance comprises determining the measure based at least in part on hyperlink navigations initiated by the user and indicated by the first and second sets of symbols; assigning a search behavior classification to the user based at least in part on the measure of interaction variance; and customizing, based at least in part on the assigned search behavior classification, the user's experience with a search process.

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1. A computer-implemented method comprising: identifying, using one or more computers, a plurality of transliterated terms in a target language, where identifying the plurality of transliterated terms in the target language comprises: identifying terms containing only characters of the target language, computing a statistic for each identified term of the terms containing only characters of the target language, where the statistic for each said identified term is based on a ratio of a probability of occurrence of the identified term in resources associated with one or more locales where the source language is spoken to a probability of occurrence of the identified term in resources associated with any locale, comparing the statistic for each said identified term to a specified threshold, and including a particular said identified term in the plurality of transliterated terms in the target language if the statistic for the identified term satisfies the specified threshold; for each transliterated term of the plurality of transliterated terms in the target language, mapping the transliterated term to one or more terms in a source language; and for a first transliterated term of the plurality of transliterated terms in the target language, identifying one or more second transliterated terms of the plurality of transliterated terms in the target language as candidate synonyms of the first transliterated term, where each of the one or more second transliterated terms is mapped to at least one term in the source language that is also mapped from the first transliterated term.

4. The method of claim 1 , where mapping the transliterated term to one or more terms in the source language further comprises: transliterating the transliterated term in the target language to the one or more terms in the source language.

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1. A method of selecting a microphone from two or more microphones for a multi-microphone speech processing system operating in a noisy environment, each of the microphones being associated with a respective channel and being suitable for picking up a noisy sound signal having a useful speech component from a main sound signal source (s(t)) mixed with a diffuse noise component, the method comprising the following steps: digitizing the sound signals picked up simultaneously by the two microphones (N, M); transforming the signals (x n (t), x m (t)) picked up on the two channels in such a manner as to produce a succession of frames in a series of frequency bands; applying an algorithm for calculating a speech-presence index of each channel; selecting one of the two microphones by applying a decision rule to the successive frames of each of the channels, which rule is a function both of a channel selection criterion and of said speech-presence index, and eliminating, from the successive frames, frequency bands that are situated beneath a second given threshold; and implementing speech processing on the basis of the sound signal picked up by the one selected microphone; which method is characterized in that: said transformation of the signals (x n (t), x m (t)) picked up on the two channels is a short-term Fourier transform; said speech-presence index is a confidence index calculated for each frequency band of each frame; and said selection criterion is calculated in frequency bands on only those frequency bands for which the confidence index is greater than a first given threshold, wherein: said multi-microphone speech processor system is a system having close-together directional microphones; and said channel selection criterion is an angle criterion based on comparing respective phases of the signals picked up simultaneously on the two channels, the microphone for selection being the microphone on which the signal is picked up sooner than the other.

3. The method of claim 1 , wherein the speech-presence confidence index is calculated for each frequency band, and said selection is performed providing the index is greater than a third given threshold, in a number of frequency bands that is greater than a fourth given threshold.

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9. The method of claim 6 , further comprising modeling the feature set to at least one audio environment.

10. The method of claim 9 , wherein modeling further comprises applying a statistical classifier to model a background environment of an audio input.