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12. A method for parsing XML, the method comprising: pulling an XML item from computer readable storage medium; selectively pulling at least on XML node from the XML item; and selectively parsing the pulled XML node into one or more sub-items based on an input from a user code, the sub-items comprising one or more of a start token, an end token or a data element.

19. The method of claim 12 , further comprising checking the pulled XML item to determine if it is valid.

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11. The computer-readable medium of claim 10 , wherein the start feature tag and the end feature tag represent a bookmark.

10. The computer-readable medium of claim 7 , wherein the start feature tag and the end feature tag each include an attribute that is set to a same value indicating the association between the start feature tag and the end feature tag.

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3. The method of claim 2 , where the one or more features of the search query include a location from which the search query was submitted, and the location is a geographical location.

2. The method of claim 1 , where the one or more features of the search query include at least one of: a term in the search query, a natural language of the search query, a time at which the search query was submitted, or a location from which the search query was submitted.

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20. The computerized system of claim 15 , wherein the set of NEC words are stored in an existing web index.

15. A computerized system comprising: one or more processors; and one or more computer storage media storing instructions to cause the one or more processors to: receive a uniform resource locator (URL) corresponding to a web page, wherein the URL includes a first string of encoding characters; transform the first string of encoding characters into one or more NEC words, wherein said transforming includes inferring a translation based on content from the web page, the content including at least one element of the web page other than the URL, wherein transforming the first string of encoding characters into one or more NEC words includes representing said first string of encoding characters by one or more pairs of URL substrings and corresponding NEC words; and store the set of NEC words in a web index.

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8. The medium of claim 7 , wherein the second set of items comprises identifiers of games played by the sports team.

7. The medium of claim 6 , wherein the first search term comprises an identifier of a sports team.

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15. The method according to claim 14 , further comprising: obtaining the speech recognition data and the data for adaptation on the each application from the storage device; and combining the data for speech recognition and the data for adaptation to generate speech recognition process data.

14. The method according to claim 13 , wherein speech recognition data on processing of a speech recognition process common to the applications and data on adaptation processing of the speech recognition process that is mutually different in accordance with the respective applications are stored and held in a storage device; and wherein the step of generating recognition result hypotheses includes: extracting a feature of the speech supplied from the one speech input unit; and generating the recognition result hypotheses for the extracted feature, using the speech recognition data on the common processing stored in the storage device; and the step of receiving the recognition result hypotheses and generating and outputting recognition results includes: simultaneously generating the recognition results suited for the applications, respectively, using the data on the adaptation processing stored in the storage device, based on one of the recognition result hypotheses, and outputting the generated recognition results to the corresponding applications, respectively.

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16. The method of claim 15 , further comprising determining whether the handwritten annotation is executable.

15. A computer-implemented method for implementing digital ink revisions, comprising: obtaining an image of a document containing at least one handwritten annotation; sending the image to a search engine to facilitate locating an original unannotated version of the document; recognizing a handwritten annotation in the image of a document using the original unannotated version of the document; executing a command associated with the handwritten annotation, the association between the command and the recognized handwritten annotation is based at least in part on user actions; and adjusting a layout of the document based at least in part upon execution of the command associated with the handwritten annotation, the manner in which the layout is adjusted in response to the command is based at least in part on user-defined preferences applied to the document that allow a user to select a granularity level such that the layout of the document will only be modified at or below the selected level, wherein selection of a line level allows the layout to be modified only at or below the line level, selection of a paragraph level allows the layout to be modified only at or below the paragraph level, selection of a section level allows the layout to be modified only at or below the section level, and selection of the document level allows the layout of the entire document to be modified.

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18. The method of claim 1 , further comprising: receiving a request for information from a client; identifying a subset of the documents based on the request, wherein the subset of the documents is identified based on the classification information associated with the subset of documents associated with the second set of editing instructions; providing the subset of the documents and associated editing instructions in the second set of editing instructions and classification information to the client; and wherein the associated editing instructions define formats in which the subset of the documents are to be displayed.

1. A method for determining information associated with documents, comprising: receiving documents, wherein the documents include images; determining a first set of editing instructions and classification information associated with the documents using image-processing software; and providing the images and first set of editing instructions and classification to a group of individuals receiving a second set of editing instructions and classification information associated with the documents, wherein the second set of editing instructions and classification information are generated by a group of individuals and include modifications and additions to the first set of editing instructions and classification information, and wherein the second set of editing instructions and classification information include subjective comments about content in the documents storing the documents and the second set of editing instructions and classification information in a non-transitory computer-readable medium, wherein the second set of editing instructions and classification information facilitate searches for content in the stored documents; receiving a request for information that is associated with a time-varying subjective value identifying information by searching through the stored documents using the second set of editing instructions and the classification information; and providing the information in response to the request, wherein the information includes multiple versions of at least one of the documents, and wherein the multiple versions are, at least in part, based on different editing instructions and classification information in the second set of editing instructions and classification information from different individuals in the group, which includes different identified subjective content, thereby proving different images that reflect the time-varying subjective value.

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242. The computer program product of claim 225 , further comprising: program code for displaying the matching resume on a display screen.

243. The computer program product of claim 242 , wherein the display includes a first portion, a second portion, and a third portion, the first portion showing a list of said at least one resume, the second portion showing at least one attribute extracted from the matching resume, the third portion showing the matching resume.

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2. The authoring tool of claim 1 , further configured to generate the plurality of gallery item descriptors from one or more data objects generated for each of the plurality of gallery items respectively.

1. An authoring tool, embedded in a non-transitory tangible computer readable medium, the authoring tool configured to: enable authoring of a gallery card among a plurality of cards of a wrap package, the gallery card having a fixed layout of content authored into the card, the authoring tool enabling an author to: (a) select a gallery card for authoring; (b) select a gallery item template; (c) author content into a new gallery item derived from the selected gallery item template; (d) author a plurality of gallery items for the gallery card by authoring content into each of a plurality of gallery items respectively; and (e) define a sequence order for rendering the plurality of gallery items of the gallery card; the authoring tool further including a behavior tool for declaring a transitional behavior that is associated with the plurality of gallery items when the gallery card is navigated; the authoring tool further configured to: (1) generate a plurality of gallery item descriptors for the plurality of gallery items respectively, each of the gallery item descriptors defining a fixed aspect ratio and a fixed layout for the content authored into the associated gallery item respectively; (2) generate a JSON gallery card descriptor including the plurality of gallery item descriptors; and (3) generate a JSON wrap descriptor that represents the wrap package of cards, the wrap descriptor including a plurality of card descriptors for the plurality of cards of the wrap package including the JSON gallery card descriptor for the gallery card, wherein the gallery card has a fixed presentation that is defined by: (i) the defined sequence order for rendering the plurality of gallery items; (ii) the fixed layout of the content authored into each of the plurality of gallery items respectively; and (iii) the fixed aspect ratio of the gallery card, wherein the fixed presentation of the gallery card is maintained as authored when the wrap package is rendered on a consuming device regardless of the type or class of the consuming device or the size or orientation of the rendering environment provided by the consuming device, wherein the gallery card is imbued with a behavior corresponding to the declared transitional behavior by a runtime viewer located at the consuming device when the wrap package is rendered, wherein the behavior is selected from a library of behavior definitions maintained by the runtime viewer.

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12. The non-transitory computer readable storage medium of claim 11 , wherein the data structure is stored in random access memory of a cluster computing framework configured to process data within the data structure in at least near real-time.

11. A non-transitory computer-readable medium storing a set of instructions that are executable by one or more processors of an apparatus to cause the apparatus to perform operations to facilitate a displaying of an aggregate in at least near-real-time in a user interface, the facilitating including reducing an amount of processing time and an amount of resources required to perform the displaying of the aggregate by incrementally updating the aggregate instead of using a batch process to create an additional aggregate, the operations comprising: acquiring a data stream of payment card and transaction data from a first source, the data stream of the payment card and transaction data comprising a first data stream; storing a first set of data in a data structure, the first set of data taken from the first data stream, the first set of data including at least a portion of the payment card and transaction data; producing the aggregate from the first set of data by running a query on the data structure; acquiring a data stream of interaction data from a second source, the data stream of the interaction data comprising a second data stream; performing the incremental updating the aggregate, the incremental updating including creating a modified data structure based on the first data structure, the modified data structure including a second set of data into the aggregate, the second set of data taken from the second data stream and including at least a subset of the interaction data; and based on the incremental updating of the aggregate, running the query on the modified data structure and modifying the user interface in at least near-real time to include at least some of the second set of data as it is acquired from the second data stream.

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2. The program product of claim 1 wherein the semantic units are words of a human language.

8. The program product of claim 2 further comprising logic that ranks words in the index in terms of data reduction and assign pointers to words based on pointer length and word ranking.

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3. The method of claim 2 , comprising determining a weight for each n-gram based on a number of times links to the given web page are selected when the n-gram is included in the at least one search query that was used to present a search results page that includes the links to the given web page.

5. The method of claim 3 , comprising filtering one or more n-grams from the search queries based on the weight associated with the n-gram being below a predetermined value.

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22. The spine stabilization device of claim 21 , wherein said inner core of said centering rod is made of a super-elastic metal.

21. A spine stabilization device comprising: a first element; a second element; and a self-centering joint connecting the first element and the second element; wherein the self-centering joint includes, a housing having a socket; a retainer received in the socket such that the retainer is deflectable relative to the housing; and a centering rod having an inner core and an outer sheath, the centering rod received partially within retainer and partially within the housing; and whereby deflection of the retainer bends the centering rod and the centering rod exerts a restoring force on the retainer.

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4. The anchor assembly of claim 1 wherein said saddle includes reinforcing ridges.

1. An anchor assembly comprising: an anchor body; an anchor head including a first arm and a second arm extending substantially parallel to one another and away from the anchor body, the first arm and the second arm separated by a gap; a shaft connected to the first arm and the second arm across the gap; a saddle having a longitudinal bore, a transverse bore which intersects the longitudinal bore, and a member capture opening adapted to receive a member wherein the member capture opening intersects the longitudinal bore; said transverse bore of said saddle being mounted about said shaft such that the saddle can move relative to the anchor head; a set screw received in said longitudinal bore of said saddle and adapted to lock the member in said member capture opening of said saddle; and said saddle including reinforced walls that prevent said saddle splaying when said set screw locks the member in said member capture opening of said saddle.

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23. The program storage device of claim 20 including representing said output as part of said software layer of said design tool, and deleting said output when no longer required.

20. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform method steps for using text from a design tool to display an output to a user, said method steps comprising: graphically displaying said output from said text of said design tool; graphically listing design rule violations; displaying said output as part of a software layer of said design tool such that no permanent changes are made to any original design file; requesting that particular violations be saved in a subset output file; generating and annotating said subset output file for use by other users such that said subset output file contains only said particular violations said user requested to be saved; generating said subset output file in a form that allows said subset output file to be applied against the design file; generating software help functions allowing said user to gain information about design rule violations; and iterating this process using said subset output file through a rule checking process as many times as necessary to remove said particular violations.

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9. The word processing system of claim 1, wherein said correction buffer is divided into a plurality of bytes, and also including a further predefined relative position, a character count successively incremented upon reading each character of a next word from said file, said character counter being cleared prior to reading a first character of said next word and attaining a word-length value upon reading the last character thereof; and under control of said address means, including said word-length value in the character counter, said writing means store each character of the next word in successive bytes of the correction buffer, the frequency-of-use count element at said predefined relative position in reference to said successive bytes, and the word-length value in said further predefined relative position in reference to the successive bytes.

11. The word processing system of claim 9, further including blanking means initializing said correction buffer to a predetermined series of blank bytes as said cleared state, and blank byte detecting means; and wherein said predefined relative position for storing said respective frequency-of-use count element associated with each differentiable word upon a first reading thereof in said text is a first one of said blank bytes found by said detecting means following all words currently stored in said correction buffer, said further predefined relative position for storing said word-length value is a next one of the blank bytes, sand said characters follow in successive bytes thereafter.

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13. The computing system of claim 12 , wherein the script API module is configured to: identify embedded script code in a document; call the malware monitor logic upon identifying the script code; and store the script code in the heap memory.

12. A computing system for zero-day malware detection comprising: a script application programming interface (API) module implemented at least partially in hardware to load a script code into heap memory for execution; a decoder implemented at least partially in hardware to identify one or more commands comprising an indirect branch call and redirect an execution pointer to point to a predetermined memory location pointer based on the detection of the indirect branch call, the predetermined memory location pre-loaded with malware monitoring logic; a heap memory to dynamically store the script code; the malware monitoring logic preloaded into the predetermined memory location to identify the script code in the heap memory and evaluate the script code for malware prior to execution of the script code; a processor implemented at least partially in hardware, the processor configured to: execute the malware monitoring logic in a sandbox upon execution of the redirection of the instruction pointer to the predetermined memory location; identify, in the heap memory by the malware monitoring logic, script code loaded into the heap memory; and evaluate, by the malware monitoring logic, the script code in the heap memory for malicious code prior to execution of the script code identify, by the malware monitoring logic, an execution start time of the script code in the sandbox; identify, by the malware monitoring logic, an execution end time of the script code in the sandbox; determine a time period between the execution start time and the execution end time of the script code; and determine, based on the time period, that the script code contains malware.

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5. The method of claim 4 , wherein the motion vector of the temporal merge candidate is a motion vector of a motion vector storing unit corresponding to the position of the temporal merge candidate block.

6. The method of claim 5 , wherein a size of the motion vector storing unit is 16×16.

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12. The method of claim 1 , wherein said selected product records are displayed in the user interface.

13. The method of claim 12 , wherein said selected product records are displayed with a link to a page of at least one shopping service.

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7. The method of claim 4 , wherein: each of the n-gram language model weights λ m from n-gram language model weights λ M satisfies λ c , m ′ = 1 N c ⁢ ∑ w ∈ W ⁢ ⁢ p ⁡ ( c ❘ w ) ⁢ ∑ i = 1  w  ⁢ ⁢ λ c , m ⁢ p m ⁡ ( w i ❘ h i ) ∑ j = 1 M ⁢ ⁢ λ c , j ⁢ p j ⁡ ( w j ❘ h j ) , and each of the sentence cluster weights γ c from the set of sentence cluster weights γ C satisfies γ c ′ = 1  W  ⁢ ∑ w ∈ W ⁢ ⁢ p ⁡ ( c ❘ w ) , ⁢ where N c = ∑ w ∈ W ⁢ ⁢ p ⁡ ( c ❘ w ) ⁢  w  , ⁢ p ⁡ ( c ❘ w ) = γ c ⁢ p c ⁡ ( w ) ∑ i = 1 C ⁢ ⁢ γ i ⁢ p i ⁡ ( w ) , ⁢ p c ⁡ ( w ) = ∏ i = 1  w  ⁢ ⁢ ∑ m = 1 M ⁢ ⁢ λ c , m ⁢ p m ⁡ ( w i ❘ h i ) , c is one of the clusters in the set of sentence clusters, C is the quantity of clusters in the set of sentence clusters, m is a language model from the set of two or more language models G M , M is the quantity of language models in the set of two or more language models G M , |w| is the quantity of n-grams in the sentence w from the set of development sentences W, and p m (w i |h i ) is the probability that n-gram w i , follows history h i as estimated by a language model G m from the set of two or more language models G M .

4. The method of claim 2 , further comprising: maximizing a combination of the probabilities by repeating the determination of at least one of the weights in the set of n-gram language model weights λ M , the determination of at least one of the weights in the set of sentence cluster weights γ C , and the probabilities p w of the sentences in the set of development sentences W.

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10. The method of claim 1 , wherein classifying the user into at least one emotional state of the set of emotional states comprises classifying the user into the emotional state associated with the at least one online element of the set of online elements.

1. A method comprising: using one or more computers, obtaining and storing a first set of information comprising a set of emotional states with which online elements may be associated; using one or more computers, obtaining and storing a second set of information comprising information relating to a set of online elements; using one or more computers, based at least in part on the second set of information, assigning each of the set of online elements to at least one associated emotional state, of the set of emotional states; using one or more computers, obtaining and storing a third set of information comprising information relating to online activity of a user in association with at least one online element of the set of online elements, and comprising an emotional state to which the at least one online element of the set of online elements is assigned; using one or more computers, based at least in part on the third set of information, classifying the user into at least one emotional state of the set of emotional states; presenting the user with an online advertisement based at least in part on the at least one emotional state, of the set of emotional states, into which the user is classified; and based at least in part on at least one direct online activity of the user and at least one indirect online activity of the user, predicting an emotional state that the user is likely to be in at a particular time at which, or during a particular period of time during which, the online advertisement is anticipated to be served, wherein the at least one direct online activity of the user includes one or more of usage, usage frequency, extent of personalization, sharing of emoticons, and sharing of emoticlips, and wherein the at least one indirect online activity of the user includes one or more of visits to specific user post, user review or blog entry domains or Web sites, and engagement with specific user post, user review or blog entry domains or Web sites.

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16. The method of automated dictionary population, as recited in claim 15 , wherein the message includes at least one of text messages, voice messages, embedded audio feeds and video data.

15. A computer implemented method for automated dictionary population, useful in association with a personal appliance including at least one dictionary which includes entries, the method for automated dictionary population comprising: retrieving a message containing words, wherein the message is received by the personal appliance; parsing the words of the message; comparing the parsed words to the entries of the at least one dictionary, wherein the comparing identifies new words of the parsed words which are not found within the at least one dictionary; generating statistical information for the parsed words; applying semantic rules to identify phrases from the parsed words by identifying word groups that include joining words; linking the words of the identified phrases and storing the linking of the words of the identified phrases with additional information that allows them to remain linked without storing the entire identified phrases; and storing the new words within at least one of the at least one dictionary, wherein the storing the new words enables recall of the new words for generating a candidate word list.

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8. The mobile display apparatus as set forth in claim 1 , wherein: the display section is a liquid crystal display.

1. A mobile display apparatus serving as a client device of an external host apparatus, the mobile display apparatus comprising: a display section; a voice output section; a video signal input section arranged to receive an input video signal from the external host apparatus; a display control section arranged to display in the display section an image based on the input video signal; a text recognizing section arranged to (i) extract a text image from an image corresponding to the input video signal and (ii) convert the text image into a text code; and a voice output control section arranged to output voice sounds corresponding to the text code through the voice output section; wherein the video signal input section outputs the input video signal supplied from the external host apparatus to the display control section and the text recognizing section; the text recognizing section converts the text image extracted from the image corresponding to the input video signal supplied from the video signal input section into a text code, and outputs the text code to the voice output control section so that the image corresponding to the input video signal is displayed in the display section; and the voice sounds corresponding to the text code are outputted from the voice output section.

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12. One or more computer readable memories storing information to enable a computing device to perform a process comprising: using a plurality of electromyography (EMG) sensors arbitrarily arranged on a user's forearm to obtain samples of EMG signals generated by muscle contractions of a user while the user is performing one or more predefined finger gestures; monitoring the predefined finger gestures using a secondary input mechanism to verify that correct gestures were performed; extracting feature samples from the sampled EMG signals and labeling feature samples according to the corresponding finger gestures that have been verified as correct by the secondary input mechanism; training a machine learning model with the labeled feature samples; and using the trained machine learning model to evaluate EMG signal samples obtained during arbitrary finger gestures to identify those arbitrary finger gestures relative to one or more of the predefined finger gestures performed by the user.

14. The computer readable memories of claim 12 wherein the predefined finger gestures comprise concurrent movement of two or more different fingers.

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19. The system of claim 18 , wherein each annotator comprises an annotator specific to the managed research domain, wherein the common ontology is specific to the managed research domain, wherein the alert further identifies the cited content, wherein that the first monitored change to the cited content undermines the measure of semantic conformity with the citing content is determined without requiring any user input.

18. The system of claim 17 , wherein the set of annotators are composed according to an Unstructured Information Management Architecture (UIMA), wherein the operation further comprises notifying the author of the cited research paper without requiring any user input specifying to notify the author of the cited research paper.

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7. The method of claim 1 in which the act of using the label data to present the label image comprises: using the label data to obtain second form data representing a second form that shows the label image in a field that can be marked to select the label image; and providing the second form data to printing circuitry; the act of receiving the signal selecting the label image comprising: receiving data representing an image of the second form that shows a mark in the field selecting the label image.

1. A method comprising: storing a data file in a data processing system; receiving data representing an image of a form from a facsimile machine; the form showing a user modifiable field in which a user has made marks by hand; the marks forming a label image within the user modifiable field; the label image identifying the stored data file to the user; using the data representing the image of the form to obtain label data defining the label image and storing the label data; obtaining associating data that associate the data file stored in the data processing system and the label data so that the stored data file can be accessed in the data processing system in response to a signal from a user selecting the label image; using the label data to present the label image to the user so that the user can provide a signal selecting the label image; receiving the signal selecting the label image from the user; and in response to the signal selecting the label image, accessing the stored data file.

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1. A spelling, counting and memory game comprising at least one word card which has a word imprinted on the reverse face of said word card and a numerical representation of that word on the obverse face of said word card, with the numerical representation being formed by a set of numbers in which each number represents a letter of the alphabet as determined by the numerical arrangement of the letters in the alphabet; and a plurality of playing cards in which indicia corresponding to the letters of the alphabet or numbers representing letters of the alphabet are printed on said playing cards, so that each of said playing cards represents one of the letters of the alphabet.

4. A spelling memory game as claimed in claim 1, wherein the plurality of playing cards are number cards having numbers representing the letter of the alphabet printed on said number cards, so that each of said number cards represents one of the letters of the alphabet and has the number corresponding to that letter printed thereon.

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10. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon, which, when executed by a processor, cause the processor to perform operations comprising: defining text to be included within a first text message; assigning one or more tags to the first text message, wherein the one or more tags are chosen from a plurality of available tags, and wherein the plurality of available tags are defined before the text to be included within the first text message is defined; and transmitting the first text message, including the text and the one or more tags, to one or more recipients; wherein the plurality of tags includes one or more of a handraise tag, a chat tag, a minute tag, and a scribe tag, and wherein at least one of: the handraise tag is assigned to a message when a user indicates an intention to focus the attention of participants of an online discussion on the message; the chat tag is assigned to a message when a user indicates an intention to discuss the message in greater detail; the minute tag is assigned to a message when a user indicates that the message should be memorialized within minutes associated with the online discussion; the scribe tag is assigned when the user indicates that the message should be supplemented for ease of use by a user with a disability.

11. The computer program product of claim 10 wherein the one or more tags include a metadata-based tag.

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19. An apparatus for identifying one or more of a plurality of enterprise-level business processes of an enterprise and a plurality of monitoring templates, comprising: a memory; and at least one processing device, coupled to the memory, operative to: obtain, using said at least one processing device, at least one of said plurality of enterprise-level business processes and said plurality of monitoring templates, wherein at least one of said obtained enterprise-level business processes and said obtained monitoring template has an associated monitoring intent comprising one or more monitoring keywords, wherein said monitoring intent links one or more business goals of said enterprise to a given enterprise-level business process such that said monitoring intent can be searched to identify at least one existing enterprise-level business process that is related to a new enterprise-level business process being created; obtain, using said at least one processing device, a user-specified monitoring intent from said user, said user-specified monitoring intent comprising one or more search keywords; assign, using said at least one processing device, a score to at least one of said obtained enterprise-level business process and said monitoring template, wherein said score is based on a matching of a semantic context of said associated monitoring intent and one or more of said monitoring keywords from said associated monitoring intent with a semantic context of said user-specified monitoring intent and said search keywords of said user-specified monitoring intent; and identify, using said at least one processing device, said one or more of said plurality of enterprise-level business processes and said plurality of monitoring templates based on said assigned score.

20. The apparatus of claim 19 , wherein said processor is further configured to generate a ranked list of said one or more of said plurality of enterprise-level business processes and said plurality of monitoring templates based on said score.

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1. A method of optimizing a sequence of operations adapted for execution by a processor, wherein the processor executes an operation set and has a set of registers, and wherein the method comprises: associating symbolic expressions with each of at least a subset of the set of registers, thereby creating a plurality of associated symbolic expressions, wherein each of the plurality of associated symbolic expressions may be emitted as one or more operations; holding a set of dependency indicators that specify, for each particular associated symbolic expression from the plurality of associated symbolic expressions, which of the other associated symbolic expressions must be emitted prior to emitting the particular associated symbolic expression; locating an operation, if any, that is next within the sequence of operations and setting that operation to be a working operation; processing the working operation as follows: a) handling the working operation by a combination of updating, if necessary, any of the associated symbolic expressions and emitting any of the associated symbolic expressions; b) identifying any of the updated associated symbolic expressions that must be emitted prior to emitting any of the other associated symbolic expressions, and then updating the set of dependency indicators to include any such dependencies; and c) identifying any of the updated associated symbolic expressions that no longer need to be emitted prior to emitting any of the other associated symbolic expressions, and then updating the set of dependency indicators to remove any such dependencies; wherein the set of dependency indicators includes a matrix of dependency indicators; wherein each column of the matrix of dependency indicators is associated with a particular register from the set of registers; wherein each row of the matrix of dependency indicators is associated with a particular register from the set of registers; wherein each dependency indicator found in a non-diagonal element of the matrix of dependency indicators indicates that the associated symbolic expression associated with the particular register associated with the row is to be emitted after the emission of the associated symbolic expression associated with the particular register associated with the column; and when any row of the matrix of dependency indicators is read the diagonal element of the row of the matrix of dependency indicators is read normally; and when any column of the matrix of dependency indicators is read, the diagonal element of the column is read as not indicating dependency regardless of the state of the dependency indicator in the diagonal element.

5. The method of claim 1 wherein: the working operation has associated therewith a destination register and one or more source registers and the dependency indicators show that a particular one of the one or more source registers must be emitted before the destination register; process (a) further includes emitting the associated symbolic expression associated with the particular source register prior to the handling of the working operation.

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9. The translation system according to claim 7 , wherein the translation language setting processor selects a candidate language group including only used languages of speakers near the translation device from a translation language group including a plurality of languages, based on the located language information and the position information, and wherein the translation device includes a display for displaying languages included in the candidate language group, and a selector for selecting the translation language from the candidate language group.

10. The translation system according to claim 9 , wherein the translation language setting processor sets the languages included in the candidate language group in an order according to the position information, and wherein the display displays the languages based on the order of the languages included in the candidate language group.

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8. A system comprising at least one processor configured to: send, via at least one communication medium, a request to obtain information; receive, via the at least one communication medium, a response to the request to obtain information, the response comprising one or more search results and a voice grammar dynamically generated based on the one or more search results; present via the device at least some of the one or more search results to a user of the device; and use the voice grammar dynamically generated based on the one or more search results to process user speech spoken by the user subsequent to the at least some of the one or more search results being presented to the user.

11. The system of claim 8 , wherein the at least one processor is further configured to present the at least some of the one or more search results to the user at least in part by: providing an indication to the user that the user is allowed to select at least one search result of the one or more search results by speaking one or more words associated with the at least one search result.

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13. The method of claim 11 , wherein browser status bar spoofing is uncovered by examining execution context of a spoofing attack that includes an HTML page, and user action sequence that include multiple raw mouse messages.

11. A method comprising: A processor examining graphic user interface (GUI) logic; identifying flaws in the logic that expose security damage; mapping a visual invariant to a program invariant; discovering inputs to GUI logic that include user actions and an execution context to cause the program invariant to be violated, the discovering comprising document object trees, active scripts, and user actions that cause the visual invariant to be violated; and constructing real visual spoofing attacks based on the inputs to GUI logic.

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16. A system for annotating an unindexed document for shared use, the system comprising: one or more processors; a document matching module stored on a memory and executable by the one or more processors, the document matching module configured to receive a first digital image from a portable capture device, the first digital image depicting at least a first portion of the unindexed document, wherein the unindexed document is unknown to an index of stored documents, receive from a first user of the portable computing device an annotation associated with the unindexed document, extract features from the first digital image, and recognize a second user from the features of the first digital image, wherein the first digital image depicts at least the first portion of the unindexed document and the unindexed document is associated with the annotation from the first user; a user association component stored on the memory and executable by the one or more processors, the user association component configured to, responsive to recognizing the second user from the features of the first digital image depicting at least the first portion of the unindexed document, create a new tie between the first user and the second user in a network of users who have captured documents with similar features, determine a first group of users, including the first user, who have operated on the unindexed document from users who have ties with the second user in the network, determine a second group of users who have not operated on the unindexed document from the users who have ties with the second user in the network, and weaken the ties between the second user and the second group of users of the network based on the first group being larger than the second group; a database stored on the memory and accessible by the one or more processors, the database configured to store the first digital image, the extracted features and the annotation as an annotated digital image; and a document authoring component stored on the memory and executable by the one or more processors, the document authoring component configured to, responsive to creating the new tie, make the annotated digital image available to the second user and share an identity of the second user with the first user.

17. The system of claim 16 , further comprising the document matching module configured to receive a second digital image of at least a second portion of the unindexed document from the second user, extract features from the second digital image and determine that the second digital image is similar to the first digital image based on comparing the extracted features from the first digital image to the extracted features from the second digital image, and the user association component configured to strengthen an existing tie between the first user and the second user in the network based on determining that the second digital image is similar to the first digital image.

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6. The method of claim 1 , wherein the markup language document further includes code that is operable to determine the value of the variable.

10. The method of claim 6 , wherein the code operable to determine the value of the variable includes a call to a universal resource identifier from which a function can be returned that can be executed to determine the value to the variable.

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11. A system, comprising: a processor configured to: provide a data store including a plurality of documents; provide a semantic model including a plurality of concepts, wherein the semantic model is derived at least in part from a reference source that includes content not included in the data store; determine at least one similarity metric for each document of the plurality of documents, wherein each respective similarity metric represents a similarity between a respective document of the plurality of documents and a respective concept of the plurality of concepts in the semantic model; receive a search query; compute at least one relevance metric of the search query, wherein each relevance metric represents a relevance of the search query to a respective concept of the plurality of concepts represented in the semantic model; and determine a ranking of at least a subset of the plurality of documents with respect to the search query using at least the at least one similarity metric and the at least one relevance metric; and memory coupled to the processor and configured to store the semantic model.

14. The system of claim 11 , wherein computing the at least one relevance metric includes embedding the search query in the semantic model.

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1. A method comprising: examining, by a computing device, a program code that includes at least procedural programming language statements; detecting, by the computing device, a first non-procedural programming language statement in the program code, the first non-procedural programming language statement having multiple implementations one of which is selected based on a presence or absence of a second non-procedural language statement in the program code; in response to detecting the first non-procedural programming language statement, determining, by the computing device, if the program code includes the second non-procedural programming language statement defining a context specific implementation of the first non-procedural programming language statement; in response to determining that the program code includes the second non-procedural programming language statement, introducing into the program code, by the computing device, a declaration for an undefined variable to flag the presence of the second non-procedural programming language statement, the undefined variable being declared using an extern keyword; inserting, by the computing device, function calls compliant with an Open Database Connectivity (ODBC) standard; compiling, by the computing device, the program code; at link-time, selecting, by the computing device, one of a plurality of alternative object modules based on whether the compiled program code includes the undefined variable, a first of the alternative object modules providing a definition of the undefined variable and the context specific implementation of the first non-procedural programming language statement being selected if the compiled program code includes the undefined variable, and a second of the alternative object modules providing a second implementation of the first non-procedural programming language statement being selected if the compiled program code does not include the undefined variable; and building, by the computing device, an executable program corresponding to the program code by linking-in the selected alternative object module.

2. The method of claim 1 , wherein the non-procedural programming language statements are embedded SQL (ESQL) statements.

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2. The method of claim 1 , wherein the request further comprises an application identifier.

1. A method comprising: receiving, by a processing device of a first server from a web service provided by a web server, a request comprising: a locale identifier identifying a location of a user device interacting with the web service; and user-inputted content received by the web service from the user device, wherein the request is generated by the web service in response to receipt of the user-inputted content; identifying, by the processing device of the first server, a language parameter in view of the locale identifier, wherein the language parameter comprises a file associated with a language relating to the location of the user device; identifying, by the processing device of the first server, a content presentation engine in view of the language parameter; caching by the processing device of the first server, the language parameter and the content presentation engine to a data store of the user device, the content presentation engine to render the user-inputted content on the user device according to the language parameter; and utilizing the content presentation engine to render the user-inputted content in the language.

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16. The at least one non-transitory computer readable medium of claim 15 wherein the at least one machine learning technique is at least one technique from a group consisting of: Vector Machines; self organizing maps; Neural Networks; and Latent Semantic Indexing.

15. The at least one non-transitory computer readable medium of claim 14 wherein the program code for identifying at least one executable file of the same specific category with an acceptable reputational score, the identified categorization data comprising indications of extracted terms related to those of the executable file with the unacceptable reputational score, further comprises: program code for applying at least one machine learning technique to categorization data corresponding to executable files in the database, to identify contextually related groups of terms pertaining to executable files with acceptable reputations.

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31. A digital processing machine used to discover trends in a database, the device comprising: a database; a digital processing apparatus, the digital processing apparatus configured to receive data and commands from a signal-bearing medium tangibly embodying a program of machine-readable instructions executable by the digital processing apparatus and used to perform a method for discovering trends in a database, said method comprising: generating a set of selected items from a database based on predefined constraints, the predefined constraints involving one or more items of a mining input expression; determining a support value for an itemset based upon the number of times the itemset appears in the database; entering the itemset into a set of large itemsets if the support value of the itemset is greater than a minimum support value and the itemset contains at least one of the selected items; and outputting an association rule when the number of times the entered itemset appears in the database bears a predetermined relationship to a number of times an associated itemset appears in the database and thereby satisfies a minimum confidence constraint.

35. The machine recited in claim 31, where the method for discovering trends in a database further comprises: forming a second itemset by concatenating the large itemsets with a set of large items in accordance with a predetermined concatenation regime to generate a set of candidate itemsets, where an item is large if the support value of the item is greater than a minimum support value; arranging the candidate itemsets so that each item within an itemset which is also contained in the set of selected items precedes any item not in the set of selected items; and using the set of candidate itemsets to output the association rules.

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15. The method of claim 1 , wherein the profile comprises a location of the participant.

1. A method for generating a transcription of a videoconference, comprising: matching human speech of a videoconference to writable symbols, the human speech encoded in audio data of the videoconference; determining a probability that a portion of the human speech matches a profile of a participant of a plurality of participants of the videoconference, the profile stored in tangible computer-readable memory; if the probability is less than a predetermined threshold, using video data of the videoconference to determine which participant of the plurality of participants of the videoconference is the most likely source of the portion of the human speech; and generating a transcription of the videoconference that identifies an association of the portion of the human speech and the participant of the plurality of participants of the videoconference determined to be the most likely source of the portion of human speech.

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11. The method of claim 10 , wherein the search request comprises at least a portion of a first textual identification string of the at least one textual identification string from the knowledge database.

10. A method, comprising: accessing, by a system comprising a processor, a knowledge database comprising nodes on a variety of topics from a variety of sources, wherein each node comprises structured data on a topic, the structured data comprises at least one textual identification string associated with the topic; accessing, by the system, a media storage comprising a plurality of content items, where each content item comprises metadata at least partially populated by a creator or viewer of the content item; generating and storing, by the system, associations between the content items and the textual identification strings based upon the metadata and the textual identification strings meeting at least one matching criteria; retrieving, by the system, a search request; identifying, by the system, an association between a content item from the media storage and at least one textual identification string from the knowledge database based on the search request matching at least one of metadata associated with the content item or the at least one textual identification string from the knowledge database; and presenting, by the system, the content item and the at least one textual identification string from the knowledge database to a receiving party in response to the search request.

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2. The method of claim 1 , comprising: comparing performance of the current language model with performance of the adapted language model; and using the adapted language model for decoding audio content if performance of the adapted language model is better than a performance of the current language model.

1. A computer-implemented method of automatically producing an improved transcription, the method comprising: obtaining, by a processor, an audio input, the audio input comprising a recording of audio signal; producing, by the processor, a first transcription of the audio input using a current language model; associating, by the processor, words included in the first transcription with probabilities each probability indicating for an associated word the likelihood that the word is a legitimate word; selecting, by the processor, a set of words from the first transcription having associated probabilities greater than a threshold; using, by the processor, the selected set of words to search, in at least one of: the internet and a database, for a set of additional textual objects that include at least one of the selected set of words, wherein the additional textual content objects are selected from the list consisting of: webpages, text posted in a social network, articles published on the internet and textual documents; using, by the processor, the additional textual objects to train a new language model; adapting, by the processor, the current language model based on the new language model to produce an improved adapted language model; and producing, by the processor, a second transcription of the audio input using the adapted language model.

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4. The computer implemented method of claim 3 , further comprising: affiliating each node with a plurality of header parameters from each document associated with the node, said plurality of header parameters being arranged in a table.

5. The computer implemented method of claim 4 , wherein said documents are emails and wherein said plurality of header parameters comprises two or more fields from an email header selected from the group of fields consisting of: “To”, “From”, “Subject”, and “Date”.

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1. A computer implemented system for generating data from social media messages of at most 140 characters for the real-time evaluation of publicly traded equities or commodities, comprising: an ingest component in the form of a computer for ingesting social media messages of at most 140 characters: a filter module of the computer eliminating expressions not considered useful language from social media messages and configuring input social media messages into useful formats to form filtered social media messages, wherein the filter module eliminates URLs and hash tags from the social media messages; a language processor of the computer processing the filtered social media messages based upon lexical databases to form filtered and processed social media messages, wherein the language processor includes a stock-based lexical repository composed of lexical items used in the ingested social media messages, as well as lexical items used in stock exchange and financial news wire, wherein the lexical items of the stock-based lexical repository are associated with specific polarity and strength values; a sentiment calculator of the computer applying rules based upon the association of the lexical items of the stock-based lexical repository with specific polarity and strength values to the filtered and processed social media messages so as to compute a representation of sentiment values associated with the social media messages as they relate to the publicly traded equities or commodities, wherein the rules are applied in head-complement, modifier-modified, and subject- predicate relations to pairs of the lexical items in their local syntactic context based upon the specific polarity and strength value of the lexical items; and a computer monitor having a graphical user interface displaying the sentiment values as they relate to the publicly traded equities or commodities, wherein the publicly traded equities or commodities are represented as graphic objects which change in size and color to depict sentiment as a function of intensity and polarity.

18. The computer implemented system according to claim 1 , wherein the language processor includes a part of speech tagger assigning lexical categories to each of the filtered social media messages, a partial parser recovering the structure of syntactic structures of the filtered social media messages, and a lemmatizer reducing the spelling of words of the filtered social media messages to their lexical root.

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8. The method of claim 7 , further comprising: displaying said set of portions matching said criteria on a display unit; and enabling a user to send a plurality of requests indicating that respective desired ones of said set of portions are to be replaced with corresponding ones of a set of new portions, wherein said first request and said second request are contained in said plurality of requests.

7. The method of claim 5 , further comprising: receiving a search request specifying a criteria for finding desired portions of said current XML data, wherein said criteria is required to be specified based on only said third set of elements; generating a search query corresponding to said search request, wherein said search query is directed to said staging table in said database; identifying a set of portions of said current XML data matching said criteria by performing said search query on said tabular data stored in said staging table in said database, wherein said set of portions are part of said first element; and sending said set of portions as a response to said search request.

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15. The apparatus of claim 11 , wherein the memory further stores instructions that, when executed by the one or more processors, cause the apparatus to: for each topic in the set of topics, automatically extract a set of attributes that provides a context for the topic from a subset of the content items containing the topic.

16. The apparatus of claim 15 , wherein the memory further stores instructions that, when executed by the one or more processors, cause the apparatus to: obtain one or more sentiments associated with the topic; and group the set of attributes by the one or more sentiments.

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1. A main work construction method for reinforced concrete building comprises the following steps: a) arranging at least one lifting platform and multiple lifting mechanisms on a surface layer of a permanent foundation; b) constructing a top story framework on said lifting mechanisms and said lifting platform, wherein constructing the top story framework comprises constructing a roof board directly on said lifting platform; c) lifting the top story framework by said lifting mechanisms off the surface layer of the permanent foundation; d) supporting the lifted top story framework by supporting devices, descending and resetting the lifting mechanisms to the surface layer of the permanent foundation, constructing a second top story framework on the lifting mechanisms and the lifting platform, and permanently connecting the top story framework with the second top story framework; wherein the second top story framework is positioned below the top story framework; e) lifting said top story framework and said second top story framework by the lifting mechanisms off the permanent foundation; wherein the lifting mechanisms and the lifting platform are commissioned and calibrated between step a) and step b), and said commissioning and calibration comprise the following steps: putting a commissioning heavy object on the lifting platform, preloading the lifting mechanisms, determining a whole construction height datum, weighing the commissioning heavy object, calculating a gravity center of load formed by the commissioning heavy object and the lifting platform and a load distribution, and preparing for lifting operation during construction; wherein lifting the top story framework by said lifting mechanisms off the surface layer of the permanent foundation comprises lifting the lifting platform by said lifting mechanisms off the surface layer of the permanent foundation.

6. The main work construction method for reinforced concrete building of claim 1 , wherein in step c) and step e), the lifting mechanisms are controlled to lift several times.

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1. A non-transitory storage medium, comprising: text-based subtitle data for providing subtitle comprising a style set and dialog information, the style set comprising a plurality of style information, the style information comprising: area information indicating an output area of the subtitles; and font information for designating a font type and a font size, and the dialog information comprising: text information comprising subtitle contents; reference style information indicating one style information, of the plurality of style information, to be applied to the subtitle contents included in the dialog information; partial style information to be applied to a portion of the subtitle contents included in the dialog information; and beginning and ending time information for designating the times of the subtitle contents.

7. The non-transitory storage medium as claimed in claim 1 , wherein the partial style information does not depend on the text information.

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13. The system of claim 10 , wherein the data structure comprises a stochastic signature comprising statistical values associated with a plurality of microgenres, and wherein each microgenre of the plurality of microgenres is associated with a respective statistical value indicating its relevance to the user.

10. A system configured to identify content items ordered based on microgenres of desired content items, the system comprising: a server comprising circuitry configured to: receive, from a client device of a user, through the user interfacing with a video consumption application that is executed at the client device, an input identifying a desired content item of a plurality of content items, wherein each content item of the plurality of content items is associated with: a respective genre that broadly characterizes the respective content item, a respective microgenre that, with respect to the respective genre, narrowly characterizes the respective content item, and a respective relevance value that indicates how relevant the respective content item is to the user; cause to be stored, at a database, an entry associated with a microgenre of the desired content item in a data structure associated with a profile of the user; identify, based on the profile of the user, a subset of the plurality of content items, wherein the respective microgenre associated with each content item of the subset comprises the microgenre of the desired content item; increase the respective relevance value associated with each content item of the subset; rank each content item of the plurality of content items in an order reflecting the respective relevance value associated with each content item of the plurality of content items; and cause the client device to, using the video consumption application, generate a display based on the order.

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15. The method of claim 11 , comprising: using the second teaching ink data set by a handwriting trainer to produce a handwriting recognizer for a target language.

11. A method for generating a teaching ink data set comprising: receiving a first set of ink input from a plurality of ink sources, at least one of the ink sources being selected from the group consisting of implicit field data, scripted untruthed ink, scripted truthed ink, and ink from at least one other language of a same script as a target language for a recognizer; generating a first teaching ink data set based upon executing a first plurality of machine learning methods selected from the group consisting of a character n-gram distribution leveling method, an allograph method, a subject diversity method, a machine truthing method, and a print and cursive data selection method upon the first set of ink input; receiving a second set of ink input from a plurality of ink sources, at least one of the ink sources being selected from the group consisting of implicit field data, scripted untruthed ink, scripted truthed ink, and ink from at least one other language of a same script as a target language for a recognizer; and generating a second teaching ink data set based upon executing a second plurality of machine learning methods upon the second set of ink input in light of the first teaching ink data set, the first plurality of machine learning methods comprising machine learning methods different from machine learning methods of the second plurality of machine learning methods.

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5. The computer-implemented process of claim 1 , wherein generating the initial list of candidate string comprises: identifying matching strings in the input history; and appending words to the matching strings to make word sequences.

1. A computer-implemented process comprising: receiving an input string of characters into memory; accessing an input history, the input history comprising a plurality of strings of characters previously used and stored in memory, using a processor, generating in memory an initial list of candidate strings, the candidate strings being strings in the input history having a prefix that matches the input string; selecting, using a processor, M most recent candidate strings and N most frequent candidate strings from the initial list of candidate strings, to create a secondary list of candidate strings; sorting, with a processor, the secondary list of candidate strings by recency in the input history to provide a sorted list of candidate strings; altering the sorted list of candidate strings to provide a final list of candidate strings, such that strings are dissimilar in a set of strings at a beginning of the final list of candidate strings; and presenting the final list of candidate strings for selection in place of the input string.

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14. The non-transitory computer readable medium of claim 13 , further comprising computer instructions that, when executed by at least one processor, cause the at least one processor to: correct interfering text blocks in the plurality of text blocks; and identify justification alignment of each text block in the plurality of text blocks.

19. The non-transitory computer readable medium of claim 14 , wherein the computer instructions, when executed by at least one processor, cause the at least one processor to correct interfering text blocks by merging text blocks when a first text block comprises a second text block and splitting a text block into two or more smaller text blocks to remove the interference.

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13. The system of claim 12 further comprising a fourth component configured to identify one or more contextual keywords for query keywords as a function of the co-occurrence scores and the lexical generality scores.

12. The system of claim 11 further comprising a third component configured to determine lexical generality scores of the query keywords.

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8. The method of claim 1 , wherein the confidence scores are determined using a machine-learning method.

1. A method of generating a search result list in response to a search query from a searcher using a computer network, the method executed with a computer having a processor, the method comprising: (a) maintaining a first database including a first plurality of search listings comprising sponsored search listings having a sponsored content; (b) maintaining a second database including documents having a general web content; (c) receiving, by the processor, a search query from the searcher; (d) identifying, by the processor, from the first database a first set of search listings comprising sponsored search listings having documents generating a match with the search query, and from the second database a second set of search listings comprising general web listings having documents generating a match with the same search query as used to identify the sponsored first set of search listings; (e) determining, by the processor, a confidence score for each listing from the first set of search listings, wherein the confidence score is determined in accordance with a relevance of each listing when compared to the listings of the second set of search listings after execution of step (d); (f) ranking, by the processor, the sponsored first set of search listings in accordance, at least in part, with the confidence score for each search listing thereof, wherein the processor associates the sponsored first set of search listings with at least one feature different than the relevance of each search listing when compared to the listings of the second set of search listings, and the processor further orders the sponsored first set of search listings in accordance with the at least one feature, the at least one feature comprising any of a number of clicks, a click-through rate, and a conversion rate derived from historical click-through and conversion data from user activity on the sponsored first set of search listings; (g) computing a plurality of demotion terms related to a plurality of the top-ranked sponsored first set of search listings, wherein the demotion terms capture non-ideal characteristics thereof; (h) updating the confidence score of each of the top-ranked sponsored first set of search listings based on the plurality of demotion terms; and (i) re-ranking the top-ranked sponsored first set of search listings according to the updated confidence scores.

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32. The system of claim 29 further comprising the document repository and the NLP system.

29. A system for processing natural language information, comprising: a processor; a memory; and a semantic network editing tool, said semantic network editing tool including one or more modules communicatively coupled with a natural language processing (NLP) system and a document repository to facilitate extraction of processed information from the NLP system for use in a semantic network wherein the semantic network editing tool is disposed to be used to view and edit entities and triplets included within the semantic network and to map entity types and relation types of a first ontology of the NLP system to element types and relation types, respectively, of a second ontology of the semantic network, the first ontology being different from the second ontology; wherein communicatively coupling the one or more modules with the NLP system includes automatically converting one or more semantic network entity types and associated semantic network templates into NLP extractor definitions and wherein the extractor definitions are trained using sample documents prior to being utilized to facilitate the extraction of the processed information from the NLP system, wherein ones of the element types are associated with ones of the semantic network templates, each of the semantic network templates including a plurality of roles corresponding to a plurality of additional element types.

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13. A method according to claim 9 , wherein providing a page address comprises providing responsive to a popularity level of said page.

9. A method of WWW page retrieval from a web site, comprising: receiving information associated with content of a web site, wherein said received information is not a WWW address and comprises characters typed for entry by a user into a URL entry field in a browser operable on an electronic device having web browsing capabilities, in which a standard URL address would be entered; said information being received by a software not associated with said site; analyzing said information to correct spelling in said information to a spelling-corrected input; providing a page address of a page of said site, responsive to said spelling corrected input, by said software; sending the page address to the browser for retrieving said page responsive to said page address; and thereby causing said page to be directly displayed to the user using the browser, without any additional user intervention beyond the entry of said information, wherein said page address is determined using a database of associations, said database is at least logically associated with a particular user, and said database includes user information regarding a particular user, which user information is entered by said user, which page is selected for display responsive to said user information and wherein said database is stored at a location remote from where said information received by said software is entered by the user for display of said page.

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24. A computer program product, encoded on a computer readable medium, operable to cause a data processing apparatus to perform operations comprising: selecting a candidate query in a query sequence stored in a query log, the query sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query; determining a navigation score for the revised query; and determining that the quality score for the revised query is greater than a quality score threshold and that the navigation score for the revised query is greater than a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation.

60. The computer program product of claim 24 , wherein the search operation, responsive to receiving an input query, generates a set search results responsive to the input query, each search result including a corresponding resource locator that specifies the location of a corresponding resource and ranked according to a first order, and wherein the operations further comprise: receiving from a search session an input query for the search operation; determining that the input query matches the candidate query and determining that one of the search results includes a corresponding resource locator referencing the navigational resource, and in response increasing the rank of the search result that includes the resource locator referencing the navigational resource to rank the search results according to a second order; and providing the set of search results ranked according to the second order for the search session.

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5. The document checking apparatus according to claim 1 , wherein the second determining includes: determining, when it is determined that the number of the common elements is not less than the first similarity determination number, whether an appearance density of the pair of the target character string and the another character string inside the target document is higher than a reference value; and specifying, when it is determined that the appearance density of the pair of the target character string and the another character string inside the target document is higher than the reference value, a part that has a high appearance density by the determination as a similar part similar to the confidential document inside the target document.

8. The document checking apparatus according to claim 5 , further comprising an output unit that outputs the similar part specified by the processor.

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28. The method of claim 19, wherein the steps of performing voice classification analysis are performed by a text-independent voice classification.

19. A method of controlling access of a speaker to one of a service and a facility from among a multiplicity of speaker candidates, the method comprising the steps of: (a) receiving first spoken utterances of the speaker, the first spoken utterances containing indicia of the speaker; (b) decoding the first spoken utterances; (c) generating a sub-list of speaker candidates that substantially match the speakers decoded spoken utterances; (d) activating databases respectively corresponding to the speaker candidates in the sub-list, the databases containing information respectively attributable to the speaker candidates; (e) performing a voice classification analysis on voice characteristics of the speaker; (f) eliminating speaker candidates who do not substantially match these characteristics; (g) querying the speaker with at least one question that is relevant to the information in the databases of speaker candidates remaining after the step (f); (h) further eliminating speaker candidates based on the accuracy of the answer provided by the speaker in response to the at least one question; (i) further performing the voice classification analysis on the voice characteristics from the answer provided by the speaker; (j) still further eliminating speaker candidates who do not substantially match these characteristics; and (k) iteratively repeating steps (g) through (j) until one of one speaker candidate and no speaker candidates remain, if one speaker candidate remains then permitting the speaker access and if no speaker candidate remains then denying the speaker access.

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9. The method of claim 1 , wherein highlighting at least the subset of the plurality of items comprises highlighting at least one item representing at least one of: an application; an application preference control; or a preference pane corresponding to the application.

1. A method for highlighting items corresponding to search results, comprising: displaying a plurality of items in a user interface display; while maintaining display of the plurality of items: receiving a first user input representing at least a portion of a search term; in response to receiving the first user input, highlighting at least a subset of the plurality of items, the subset of the plurality of items including: a first item that represents at least a one item having metadata that at least partially matches the first user input; a second item that represents at least one item having metadata that at least partially matches the first user input; and a third item that represents at least one item having metadata that represents at least one item having metadata that at least partially matches the first user input; while the first item, the second item and the third item are highlighted, receiving a second user input representing an additional portion of the search term; and in response to receiving the second user input, incrementally changing the displaying and highlighting of the plurality of items in response to the second user input, including: maintaining the highlighting of the first item, wherein the first item represents at least one item having metadata that at least partially matches the first user input and the second user input representing the additional portion of the search term; maintaining the highlighting of the second item, wherein the second item represents at least one item having metadata that at least partially matches the first user input and the second user input representing the additional portion of the search term; and ceasing to highlight the third item, wherein the third item does not represent any items having metadata that at least partially matches the first user input and the second input representing the additional portion of the search term.

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2. The method of claim 1 wherein step B is performed by the cell phone to which said text message received in step A is directed using an on-board GLOBAL POSITIONING SATELLITE receiver with at least two location fixes and the time of those fixes being reported to a mobile switching center (MSC) or mobile telephone switching office (MTSO) of said cellular system via administrative or command and control or paging channels or whatever other channels are used in said cellular system for sending data from said cell phone to said MSC or MTSO.

1. A method comprising the steps: A) receiving an incoming text message directed to a cell phone registered in a cellular system; B) automatically determining a location fix of said cell phone at at least two different times and recording said location fixes and the time of each location fix; C) using a computer to calculate the approximate speed of said cell phone using said location fixes and the interval between each location fix; D) comparing the speed calculated in step C to a discrimination speed which is set to discriminate between a cell phone with a user who is driving and a cell phone with a user who is sitting, walking or running or standing still; E) using a computer to determine if an automatic text message response indicating the user of the cell phone to which the text message received in step A is directed is not able to respond immediately is to be sent to the sender of said text message received in step A; F) if step E determines an automated response text message response is to be sent, using a computer to automatically generate said automated response text message and sending it back to the sender of the text message received in step A; and G) if step E determines no automated text message response is to be sent, forwarding the text message received in step A to the cell phone to which it is directed in the manner normally used by said cellular system.

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17. The method of claim 1 , wherein at least one of said plurality of functionality modules is a conversion module configured for converting at least one instance of an associated said instance type.

1. A method for obtaining contextually related instances using one or more different functionality modules, comprising: a) providing to a system comprising at least one server a plurality of different functionality modules and a graph mapping a plurality of contextual relations among a plurality of instance types, each said functionality module being associated with at least one of said plurality of contextual relations in said graph and configured for providing at least one instance of a respective type; b) receiving a query defining contextual linkage between at least one known instance and at least one requested instance from a client connected to said system via a network, said at least one known instance is not directly associated with a type of said requested instance; c) identifying, by said system, a match between said contextual linkage and a sub-graph of said graph, said sub-graph being associated with a group of said plurality of functionality modules; and d) dividing said query to a number of single step queries; e) iteratively executing at least some of said number of single step queries by said system, wherein one of said number of single step queries includes a first member of said group with said at least one known instance for obtaining at least one intermediate instance and another of said number of single step queries includes a second member of said group with said at least one intermediate instance for obtaining said at least one requested instance; f) responding to said received query with said obtained at least one requested Instance; wherein said functionality module implements at least one of a web service and a code script; wherein members of said group are executed in an order matching dependencies in said sub graph.

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4. The method of claim 1 , wherein indicating at least one call path from the plurality of call paths further comprises selecting at least one call path from the plurality of call paths according to the number of occurrences of the at least one type of event for a particular dialog node.

1. A method of analyzing speech application performance comprising: determining a call path for each of a plurality of calls from a log of an interactive voice response system comprising a speech application, wherein each call path is defined by an ordered set of dialog nodes of the speech application; counting a number of occurrences of at least one selected type of event for the dialog nodes of the plurality of call paths; and indicating at least one call path from the plurality of call paths according, at least in part, to the number of occurrences of the selected type of event within the at least one indicated call path.

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9. A computer system for ranking documents, comprising: a memory storing computer-executable instructions of: a sentence classifier; a document rank classifier trained based on classifications of sentences of documents, the classifications being generated using the sentence classifier, and trained based on ranks of documents; and a component that classifies sentences of a document using the sentence classifier, represents the document by classifications of its sentences as determined by the sentence classifier, and applies the document rank classifier to the classified sentences to generate a rank for the document; and a processor that executes the computer-executable instructions stored in the memory.

11. The computer system of claim 9 wherein the sentences are classified based on sentence mode.

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1. A method for evaluating compliance of at least one agent reading at least one script to at least one client, the method comprising at least the following: conducting at least one voice interaction between the at least one agent and the at least one client, wherein the at least one agent follows the at least one script at an agent workstation; evaluating the at least one voice interaction with at least one automatic speech recognition component adapted to analyze the at least one voice interaction, wherein the at least one voice interaction is divided into viewable panel-level segments and a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding expected text, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding expected text, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding expected text, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding expected texts; and determining whether the at least one agent has adequately followed the at least one script wherein a set of action rules is applied to the output of the determining, wherein the set of action rules includes a quality assurance action to be taken.

18. The script compliance method of claim 1 , wherein evaluating the at least one voice interaction includes evaluating a plurality of panels.

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2. The method of claim 1 , further comprising: decreasing a time remaining in respective ones of said content item idle timers in response to detecting a user performing a specific operation on said associated one of said content items in said active subset of said set of content items.

3. The method of claim 2 , wherein said specific operation is dynamically determined in response to determining at least one use pattern of said user.

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3. The decomposing apparatus of claim 2, wherein the font name is mapped with the available font by reference to a font substitution table in which unavailable fonts are mapped against fonts available in the font storage section.

2. The decomposing apparatus of claim 1, wherein a font available in the font storage area is mapped with the font name when the corresponding font is not available in the font storage section.

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12. The message decoding method as claimed in claim 11 , further comprising: the process module determining whether the repetition value of the first word group buffer is less than a predefined value; and the processing module controlling the electronic system to display the first buffer word group when the repetition value of the first word group buffer is not less than the predefined value.

11. A message decoding method for an electronic system capable of displaying messages, the electronic system comprising a processing module, a storage module, and a receiving module, wherein the processing module is electrically connected to the storage module and to the receiving module, the receiving module is used for receiving an un-decoded string of a message from a message transferring terminal, the processing module is used for decoding and compiling the message received by the receiving module, and the message decoding method comprises: the processing module decoding an un-decoded string of a message received from the message transferring terminal, acquiring a plurality of characters and a plurality of position information corresponding to each of the characters, and saving the characters into the corresponding positions of a word group decoding buffer of the storage module; when the word group decoding buffer is full, the processing module determining whether the word group of the word group decoding buffer is the same as one of the word group of the word group handling buffer of the storage module; and increasing the repetition value of the first buffer word group when the processing module determines that the word group in the word group decoding buffer is the same as a the first buffer word group in the word group handling buffer.

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1. A non-transitory computer readable medium storing a document creation support program causing a computer to function as: a receiving unit that receives: (1) a defined text, and (2) edition process information, the edition process information having recorded therein an operation history when creating the defined text, and the defined text including a sentence associated with the operation; a revision range extraction unit that extracts a revision range where a preset operation writing or erasure appear a plurality of times in a sentence associated with the operation history from the edition process information received by the receiving unit; a document feature quantity extraction unit that determines, as a first feature quantity, the number of occurrences of words in the sentence in the defined text and determines, as a second feature quantity, the number of occurrences of words in a revised version of the sentence in the defined text, the revised version being associated with in the revision range; and a sentence example information search unit that searches for sentences in sentence example information based on both (1) the first feature quantity of occurrences of a word or phrase and (2) the second feature quantity of occurrences of a word or phrase.

3. The non-transitory computer readable medium according to claim 1 , wherein the document creation support program causes the computer to further function as a sentence example information recording unit that additionally records the sentence in the defined text and the sentence in the revision range to the sentence example information in association with the first feature quantity and the second feature quantity.

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9. The method of claim 1 , further comprising providing at least one axiom which constrains operation of the theorem prover module.

13. The method of claim 9 , wherein said at least one axiom applies to multiple different location objects and is selected from among: a first axiom that states that each of the multiple different location objects that is normal has a meaningful corresponding address object; a second axiom that states that each of the multiple different location objects is identified by a respective address object; a third axiom that states that a constructor function produces non-basic location objects for field-type access terms; a fourth axiom that states that other value objects of pointers are equal to other address objects of other location objects obtained through dereference of the pointers; a fifth axiom that states that two field-type location objects are identical when the two field-type location objects share a same parent location object and a same link from the same parent location object; and a sixth axiom that states that, when two respective parent location objects have equal value objects, then two corresponding child field-type location objects which depend from the two respective parent location objects via another same link also have equal value objects.

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2. The method of claim 1 , wherein: the method further comprising, for each predicate, in the second subset of the plurality of predicates, generating another selectivity value; and estimating the cost includes estimating the cost based on the other selectivity value(s).

1. A method comprising: storing summary data that (a) specifies a number of each element of a plurality of elements of an XML document that is part of XML data and (b) indicates a hierarchical relationship among the plurality of elements; identifying, in a particular query that targets a portion of the XML data, a plurality of predicates that comprises a first subset and a second subset that is different than the first subset; analyzing the summary data based on the first subset of the plurality of predicates; determining that at least a first predicate in the first subset of the plurality of predicates is correlated with a second predicate in the second subset of the plurality of predicates; in response to determining that the first predicate is correlated with the second predicate, generating a single selectivity value based on the first subset of the plurality of predicates, one or more predicates that do not belong to the first subset of the plurality of predicates, and the summary data; associating the single selectivity value with the first subset of the plurality predicates; and estimating, based on the single selectivity value, a cost of executing the particular query; wherein the method is performed by one or more computing devices.

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4. The non-transitory computer-readable storage medium according to claim 3 , wherein the program instructs the microprocessor to perform the further step of choosing the user-selectable combination function out of a totality of Boolean operations.

3. The non-transitory computer-readable storage medium according to claim 1 , wherein the program instructs the microprocessor to perform the further step of basing the user-defined combination on choosing at least one user-selectable combination function and is further based on providing the plurality of the search criteria options as parameters to the user-selectable combination function.

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81. The system of claim 68 further comprising a transformation generator for deriving a transformation from the business data schema into a second business data schema, using results of said mapping analyzer.

68. A system for mapping a business data schema into a generic data schema, the system comprising: a memory for storing the business data schema, wherein the business data schema represents at least one type of business data instance in terms of alphanumeric values and links to business data instances, and including a plurality of generic instance mappings; a mapping generator for defining a mapping from the business data schema into the generic data schema a mapping analyzer for representing the mapping from the business data schema into the generic data schema in terms of the generic instance mappings; and a transformation generator for deriving a transformation from first data conforming with the business data schema into second data conforming with the generic data schema, wherein the transformation is based on the generic instance mappings.

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15. The computer program product of claim 11 , said method further comprising: said processor receiving selection rules for selecting text; said processor selecting text in accordance with the received selection rules; and before said receiving first text entered by the user, said processor indexing the selected text to generate multiple indexed segments of text which include the plurality of indexed segments of text.

18. The computer program product of claim 15 , wherein the selection rules for selecting text are based on the number of words in segments of the text.

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14. The apparatus of claim 13 , wherein the processing system is further configured to interpret the first and second movements as being gesture-related.

13. An apparatus for communicating control information, comprising: a processing system configured to: determine a first movement of a first device wearable by a user based on a first set of data received from the first device by way of an antenna, wherein the first set of data relates to the first movement of the first device, wherein the first determined movement is used to create a first set of possibly performed gestures; determine a second movement of a second device wearable by the user based on a second set of data received from the second device by way of the antenna, wherein the second set of data relates to the second movement of the second device, wherein the first and second movements occur simultaneously, wherein the second determined movement is used to create a second set of possibly performed gestures, and wherein the second wearable device is separate from and not integrated with the first wearable device; and infer, from the first and second sets of possibly performed gestures, that the first movement is representative of an intended command and the second movement is not representative of the intended command; and a transmitter configured to transmit information based on the inference and wherein inferring that the first movement is representative of the intended command and the second movement is not representative of the intended command is based on the first and second sets of possibly performed gestures indicating that the first and second movements are in substantially the same direction.

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15. The system of claim 13 , wherein the e-captcha challenge comprises a question to be answered.

13. A system of distinguishing between computers and humans through enhanced completely automated public turing test to tell computers and humans apart (e-captcha), comprising: a computer system having one or more storage devices that stores computer program instructions and one or more physical processors programmed with the computer program instructions that, when executed by the one or more physical processors, cause the computer system to: receive a request comprising an e-captcha specification, wherein the e-captcha specification comprises one or more parameters that specify a particular skill needed to solve the e-captcha and a specific domain to which the skill needed to solve the e-captcha is related; identify an e-captcha challenge based on the e-captcha specification, wherein the e-captcha challenge includes a skill-based action to be completed to validate that a user is a human user; provide the e-captcha challenge via the network responsive to the request; receive a response to the e-captcha challenge via the network; determine whether the skill-based action was at least partially correctly completed; generate information indicating whether the skill-based action was at least partially correctly completed; and provide via the network the information indicating whether the skill-based action was at least partially correctly completed.

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14. The method of claim 10 , wherein the feature is a continuous feature.

15. The method of claim 14 , wherein the continuous feature is one or more of an utterance audio duration, a latency of producing speech recognition results, or a time of day.

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21. A computing system for enabling a software application in a computing device to manipulate data through logical views, comprising: a memory; a definitions file having a plurality of sections that define a correspondence between stored data in a plurality of data sources and one or more logical views, the plurality of data sources containing at least one data source that is not a relational database, each of the plurality of data sources storing data; and a join engine stored on the memory and configured, when executed, to automatically interface between at least one logical view and a corresponding plurality of stored data sources, including the at least one data source that is not a relational database, such that, when an operation is performed on the at least one logical view, underlying stored data is automatically manipulated in the corresponding plurality of stored data sources.

23. The computing system of claim 21 wherein the at least one data source is an XML file.

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1. A method comprising: receiving unconstrained input speech from a user; converting, via a processor, only the unconstrained input speech corresponding to single digits into a string of words, wherein each word in the string of words is modeled using a three segment structure comprising a plurality of heads and a plurality of tails; converting the string of words into a sequence of digits using classes of rules and according to an acoustic model database in which Markov models characterize acoustic features of numeric words; comparing the sequence of digits to a plurality of valid sequences of digits, to yield validity information; and providing the validity information to a device associated with the user.

2. The method of claim 1 , wherein the plurality of valid sequences of digits comprise one of valid credit card numbers, valid telephone numbers, and valid social security numbers.

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18. The method according to claim 10 , further comprising an act of storing, in a memory of the computer system, a database including the identified terms and associations.

10. A method for determining a business ontology, the method comprising acts of: performing an analysis by a computer system of a plurality of business documents, wherein the analysis comprises acts of: establishing an analysis scope that includes the plurality of business documents; determining a plurality of sentences within the plurality of business documents within the analysis scope, including separating the sentences for analysis; identifying terms and associations between terms within each separated sentence of the plurality of sentences, including determining a proximity between at least two of the terms within at least one sentence of the separated sentences, the proximity including a sentence proximity association for terms of the identified terms occurring in the same sentence but not in a same term group, a term proximity association for identifying actions acted upon terms of the identified terms by other terms, and a document proximity association for all verbs in the same business document of the plurality of business documents; analyzing the terms and associations including the sentence proximity association, the term proximity association, and the document proximity association; after analyzing the terms and associations, identifying frequently-used terms and associations within the plurality of sentences used most within the scope; and determining a business ontology based on the identified frequently-used terms and associations within the plurality of sentences among the plurality of business documents.

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1. An integrated development environment for developing user interface documents, the integrated development environment comprising: a processor of a machine; an editor to edit a user interface document; an adaptation engine to generate device class specific representations of the user interface document, each device class specific representation referring to a respective device class; and a device class dependent complexity indicator to determine, using the processor of the machine, complexity values of layout components of the device class specific representations by accessing a library of stored complexity evaluation functions associated with the layout components, each combination of a layout component with respect to each device class having a distinct complexity evaluation function in the library, to calculate a complexity value for each of the layout components with respect to each of the respective device classes in the device class specific representations using the corresponding distinct complexity evaluation function accessed from the library, and to aggregate the complexity values of the respective device class specific representations into a single complexity value for each device class, the complexity values being numerical values.

2. The integrated development environment of claim 1 , further comprising: a template wizard being interfaced to the editor to create a new user interface document by loading a predefined document template from the template wizard into the editor.

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10. The method of claim 1 , wherein receiving user interactions on one or more external systems, further comprises: receiving the user interactions as graph actions performed by users of the social networking system on the first set of graph objects on different external systems; categorizing the user interactions by which of the external systems the graph actions were performed on the first set of graph objects; and storing the categorization of the user interactions by external systems as a parameter in content item objects associated with content items.

11. The method of claim 10 , further comprising: aggregating graph actions performed by users connected to the viewing user based on the graph objects the graph actions were performed on in the different external systems; and generating content items comprising the aggregated graph actions performed by users connected to the viewing user based on the graph objects the graph actions were performed on in the different external systems.

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3. The system of claim 2 , wherein the meeting information includes meetings.

2. The system of claim 1 , wherein the meeting information includes the event to which the participants are to attend.

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4. The method for comparing a plurality of resumes described in claim 1 , wherein the step of generating the attribute array includes ignoring insignificant dependent concepts.

1. A method for comparing a plurality of resumes, including the following steps: receiving a first resume from a database stored on a computer; parsing the first resume into bands based on a predefined setting; generating a word array by parsing the text in each band into separate parsed words and storing each of the parsed words in the word array, wherein the word array includes separate rows for each of the parsed words and a column populated with information that is indicative of the band associated with each of the parsed words; standardizing each of the words contained in the word array, by iteratively correcting punctuation, replacing well-known abbreviations, or removing common words; generating an attribute array by iteratively comparing each of the parsed words contained in the word array to attributes in an attribute dictionary and adding each of the parsed words that match one of the attributes in the attribute dictionary to the attribute array, wherein the attribute array includes information regarding the number of times each of the attributes occurs within the first resume and information indicative of the band in which each of the attributes was first found; identifying root attributes based on the number of times in which attributes or multi-word attributes occur within the first resume and counting the number of occurrences of each root attribute in the first resume; identifying leaf attributes that are related to root attributes and counting the number of occurrences of each leaf attribute in the first resume; generating a first metric indicative of the significance of each of the attributes in the attribute array to the first resume; generating a second metric indicative of the significance of each of the root attributes to the first resume; generating a third metric indicative of the significance of each of the leaf attributes to the associated root attribute; weighting the first, second and third metrics, wherein for each attribute, the first, second and third metrics are one of the bands indicating a relative position of the attribute within the first resume, a number of occurrences of each of the associated root attributes in the first resume, and a support value indicating a relationship to each of the associated root attributes or a combination of the three metrics; ranking the attributes based on a weighted value of the first metric for each of the attributes; ranking the root attributes based on a weighted value of the second metric for each of the root attributes; ranking the leaf attributes based on a weighted value of the third metric for each of the leaf attributes; generating a profile for the first resume based on the rank of the attributes, the root attributes and the leaf attributes; selecting one or more additional resumes for comparison and generating profiles for the additional resumes by using the same steps that were employed to generate the profile for the first resume; comparing the profile for the first resume with the profiles for the additional resumes; and ranking the profiles for the additional resumes based on how closely the profiles for the additional resumes match the profile for the first resume.

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18. The system as recited in claim 17 , wherein the mixed-language question answering supplement processor is further configured to: receive a correspondence mapping of one or more named entities in the target language to one or more named entities in the source language.

17. A mixed-language question answering supplement system, comprising: a mixed-language question answering supplement processor configured to: receive a question in a target language; apply natural language processing to parse the question into at least one focus; for each focus, determine if one or more target language verbs share direct syntactic dependency with the focus; for each of the one or more verbs sharing direct syntactic dependency, determine if one or more target language entities share direct syntactic dependency with the verb; determine one or more Abstract Universal Verbal Types associated with each verb; for each of the one or more Abstract Universal Verbal Types, determine whether a dependency between a source language entity and a source language verb is of the same type as the dependency between the target language verb and the target language entity comprising: use a cognitive system to generate a plurality of reasoning algorithms to analyze the source language and the target language, wherein each reasoning algorithm generates a dependency score; train a statistical model employed by a question answer pipeline; apply the trained statistical model to determine a weight for each dependency score; apply the weight to each dependency score to generate weighted dependency scores; and processing the weighted dependency scores with the statistical model to generate one or more confidence scores measuring dependency; if the dependency is similar, return the source language entity as a member of a set; and if the set is full, return an answer in the target language to the question in the target language.

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5. The internet protocol television system of claim 1 , wherein the controller circuit is adapted to: receive from the set-top box the content in the form of textual content generated by a source other than the user; translate the textual content to the language understood by the user; and cause the set-top box to present the adapted avatar presenting the translated textual content.

6. The internet protocol television system of claim 5 , wherein the source corresponds to one of textual content of a website, or textual content of a book.

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2. The method of claim 1 , wherein the network resource is an attachment in an email message that was not sent to the first user.

6. The method of claim 2 , further comprising: generating the author map based on the second user associated with the email message that contains the network resource as the email attachment, wherein the second user is associated with the email message in response to the second user being listed either as a sender or as a recipient of the email message.

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1. A computer system, comprising: at least one processor; memory having instructions configured to cause the processor to: identify a plurality of citations in at least one of a plurality of authoritative documents; identify, in the plurality of citations, a content, wherein the content includes at least one noun-verb pair; assign a unique noun ID to represent each unique noun from the plurality of citations; and store, in each row of a plurality of rows of a table, data indicating: a portion of the content, the citation that corresponds to content, and one or more unique noun IDs that correspond to the content, such that the contents of the table are usable to analyze compliance with at least one noun-verb pair.

3. The computer system of claim 1 , wherein the instructions are further configured to cause the processor to generate an audit compliance report including evidence, wherein the evidence is based on the unique noun ID.

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15. The mobile device of claim 12 , wherein the handwriting messaging client is further configured to poll for new image data representative of other handwriting input sent from another mobile device.

16. The mobile device of claim 15 , wherein the handwriting messaging client is further configured to periodically poll for the new image data representative of the other handwriting input sent from the other mobile device.

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2. The method of claim 1 , wherein analyzing the identified phonemes to identify prosodic characteristics comprises identifying pauses between the identified phonemes of the speech of the patient from the audio sample.

5. The method of claim 2 , wherein automatically measuring fluency comprises counting a number of pauses that occur in the speech of the patient of the audio sample.

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6. The method of claim 1 , wherein the supplemental content includes a video associated with the rendered document.

1. A method in a computing system for providing an interactive environment associated with a rendered document, comprising: receiving, by a computing device that is in communication with a first mobile device, first text captured by the first mobile device from a first instance of the rendered document; identifying, by the computing device, from a repository of digital documents, a digital form of the rendered document that corresponds to the first captured text; receiving, by the computing device, from the first mobile device, supplemental content for the digital form of the rendered document; storing the supplemental content, by the computing device and in a database of supplemental content associated with the digital documents; receiving, by the computing device, from a second mobile device, second text captured by the second mobile device from a second instance of the rendered document; identifying, by the computing device, from the repository of digital documents, the digital form of the rendered document that corresponds to the second captured text; determining, by the computing device, that the supplemental content exists for the digital form of the rendered document; adding one or more indicators to the digital form of the rendered document that indicate that the supplemental content for the digital form of the rendered document exists; and providing the digital form of the rendered document along with the one or more indicators of supplemental content to the second mobile device.

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2. A method as defined in claim 1 , wherein presenting a test utterance to a labeler further comprises selecting the test utterance from a group of labeled utterances.

3. A method as defined in claim 2 , wherein selecting the test utterance from a group of labeled utterances further comprises generating the group of labeled utterances using the annotation guide.

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2. The method of detecting homophone contextual errors of claim 1 further comprising: (g) displaying at least one alternative homophone related to said homophone indicated to said operator.

1. The method of detecting homophone contextual errors in a string of data segments in an information processing system comprising: (a) storing a table of homophones, each homophone having stored therewith a set of contextual usage rules specific thereto and at least one of said homophones having stored therewith one or more pointers to a table of other sets of contextual usage rules; (b) scanning asid string for one of said homophones stored in said table of homophones; (c) detecting a homophone in said string; (d) accessing said contextual usage rules and any of said one or more pointers stored with said detected homophone, using said one or more pointers accessing any contextual usage rules in said table of other sets of contextual usage rules associated with said homophone; (e) comparing data segments surrounding said homophone with said accessed contextual usage rules associated with said homophone; and (f) indicating to an operator of said information processing system that a homophone has been found whose contextual usage rules do not compare with said data segments surrounding said homophone.

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17. The system of claim 15 , wherein the predicate-argument relations are identified using supertags.

15. A system comprising: a processor; and a computer readable storage medium having stored therein instructions which, when executed by the processor, cause the processor to perform operations comprising: collecting a plurality of task-oriented, human-human dialog interactions between users and human agents for a given domain; after collecting the plurality of task-oriented, human-human dialog interactions, extracting, via a processor, a respective dialog structure associated with each of the plurality of task-oriented, human-human dialog interactions, wherein extracting the respective dialog structure comprises: identifying a respective task in each of the plurality of task-oriented, human-human dialog interactions; identifying subtasks in the respective task and associating relations between the subtasks, wherein the identifying of the subtask is done using a chunk model equation PT*=argmax Σ ST P(ST|U)P(PT|ST), where PT* is the most likely plan tree, ST is each subtask in a sequence of utterances U, PT represents likelihood of each plan tree, and P represents the individual probabilities within the chunk model equation, where the chunk model equation uses the respective dialog structures U and ST as a weighted lattice; and identifying a dialog act and a set of predicate-argument relations for the subtasks by annotating user utterances in the plurality of task-oriented, human-human dialog interactions with tags; generating a clause from the set of predicate-argument relations; removing speech repairs and dysfluencies from a respective user utterance in each of the plurality of task-oriented, human-human dialog interactions; and storing the respective task, the subtasks, the dialog act, the set of predicate-argument relations, the clause, inter-clausal relations within the clause, and a set of dominance and precedence relations associated with the respective task as a dialog interaction dataset represented as a single tree.

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2. The method according to claim 1 , wherein the query comprises a graph query and the data sources comprise graph data sources.

1. A method for query evaluation, comprising: implementing a data query evaluation system at each data source of a set of distributed and networked linked data sources, wherein the distributed and network linked data sources respectively correspond to a plurality of nodes connected over a network, wherein the data query evaluation system at each data source is configured for: receiving a query over the set of distributed and network linked data sources; decomposing the query into a set of sub-queries of the query; evaluating each sub-query in the set of sub-queries with respect to each data source in the set of distributed and network linked data sources, wherein evaluating comprises determining which data sources in the set of distributed and network linked data sources are capable of answering each sub-query, wherein each data source of the set of distributed and networked linked data sources dynamically determines whether it is capable of answering each sub-query; summarizing results of the evaluating of each sub-query; exchanging between the distributed and networked linked data sources the summarized results of the evaluating, wherein each data source of the set of distributed and networked linked data sources dynamically provides the summarized results; executing, in parallel by the distributed and networked linked data sources, a distributed query evaluation process to compute a plurality of combinations of query results from the distributed and networked linked data sources which provide an answer to the query; computing a set of distributed plans by composing one or more of the sub-queries in one or more of the distributed and networked linked data sources; evaluating each plan in the set of distributed plans; selecting a sub-set of plans from the set of distributed plans to be executed for responding to the query; executing the selected sub-set of plans, wherein executing the selected sub-set of plans comprises: an exchange of data between each of the distributed and networked linked data sources that are part of the selected sub-set of plans; executing a plurality of sub-queries in respective ones of the distributed and networked linked data sources that are part of the selected sub-set of plans; and forwarding results of the execution of one or more given sub-queries of the plurality sub-queries to one or more data sources of the distributed and networked linked data sources that are part of the selected sub-set of plans, and which did not perform the one or more given sub-queries, wherein the results comprise answers and partial answers to the given sub-queries; and returning results of the query; wherein the implementing of the data query evaluation system at each data source is performed without: (i) transmission of queried data to a central repository; (ii) using a central federator for coordinating and merging the partial answers from the one or more data sources of the distributed and networked linked data sources that are part of the selected sub-set of plans; and (iii) using a global schema to evaluate the query; and wherein the steps of the method are performed via at least one processing device and at least one memory.

Generate a child claim based on:

1. A digital image search and retrieval system, comprising: a query parser for parsing a query submitted by a user through a client computer, said query including at least one metadata criterion relating to a first type of recorded metadata and said query is void of any reference to a second type of recorded metadata different than the first type of recorded metadata; said query parser having access to a metadata database for searching the metadata database for one or more digital images satisfying said metadata criterion; and a response composer communicatively coupled to the query parser for receiving from the parser a notification of metadata results responsive to the query; said response composer having access to the metadata database and a digital image database storing images identified by metadata stored in the metadata database wherein the response composer composes a response including one or more digital images from said digital image database corresponding to the metadata results from the query, the metadata for these images which corresponds to the first type of recorded metadata, and other metadata for these images which corresponds to the second type of recorded metadata, from said metadata database; and said response composer being communicatively coupled to said client computer for sending the response to the client computer for display to said user.

14. The system of claim 1 , wherein said corresponding metadata in said response includes recorded metadata specifically satisfying said metadata criterion, and the other metadata associated with said recorded metadata.

Generate a child claim based on:

1. A method for conducting an expert conversation, the method comprising: constructing a knowledge database comprising a dialogue repository comprising a plurality of dialogues, each dialogue representing a framework for creating at least one expert conversation and comprising a plurality of nodes and a plurality of edges extending between pairs of nodes, by identifying a subject for each node and associating an identifying text string with each node, the identifying text string comprising the identified subject for each node; grouping the nodes by common subject; into a plurality of node groups, each node group associated with a given subject; identifying containment hierarchies among the subjects, each containment hierarchy comprising a subset relationship between a given pair of subjects; organizing the node groups in the knowledge database in accordance with the containment hierarchies; and using the dialogue repository in combination with a runtime dialogue system in communication with the knowledge database and executing on a computing system that is in communication with an expert and a user to use the knowledge database to conduct a live expert conversation between the expert and the user using the plurality of nodes in the knowledge database as turning points in the live expert conversation to prompt the exchange of information between the expert and the user, to use the exchanged information to identify appropriate edges at each node and to extend the expert conversation across the identified appropriate edges through the plurality of nodes.

11. The method of claim 1 , wherein the nodes comprise decision nodes, each decision node comprising logic to determine a destination node linked to that decision node by one of the plurality of edges based on at least one of data and answers entered by the user at nodes other than that decision node.

Generate a child claim based on:

10. One or more non-transitory computer-readable storage devices comprising instructions that, when executed by one or more processors, cause performance of operations comprising: identifying, by a computing system, a particular search result that was determined, along with a plurality of first search results, to be responsive to a first query, wherein the particular search result corresponds to a particular result document and each first search result of the first search results corresponds to a respective first result document, wherein the particular result document is a particular web page and the particular search result is configured to provide navigation to the particular web page upon user selection of the particular search result from among a presentation of multiple search results; identifying, by the computing system, a second result document that is associated with the particular result document due to the second result document including content that identifies an object that is also identified by content included in the particular result document, wherein a second search result corresponds to the second result document; identifying, by the computing system, second relevance data that indicates a popularity of the second search result as a selection by a second population of users as a result for a second query that is identical to the first query or similar to the first query; and determining, by the computing system, a score for the particular search result based on (i) first relevance data that indicates a popularity of the particular search result as a selection by a first population of users as a result for the first query, and (ii) the second relevance data that indicates the popularity of the second search result as the selection by the second population of users as the result for the second query.

18. The one or more non-transitory computer-readable storage devices of claim 10 , wherein: the particular search result and the plurality of first search results were determined to be responsive to the first query as a result of a search by a first search engine of a first corpus of result documents; and the second search result was determined to be responsive to the second query as a result of a search by a second search engine that is different than the first search engine of a second corpus of result documents that is different than the first corpus of result documents.