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7. The method of claim 5 wherein determining whether the synthetic audio information is acoustically confusable with acoustic information corresponding to other tokens in the context free grammar comprises: perturbing the synthetic audio information; performing speech recognition on the perturbed audio information to obtain a speech recognition result; and determining whether the synthetic audio information is acoustically confusable with acoustic information corresponding to other tokens in the context free grammar based on the speech recognition result.

5. The method of claim 4 wherein identifying acoustically confusable tokens comprises: identifying a token in the context free grammar; generating synthetic audio information indicative of a pronunciation of the identified token; and determining whether the synthetic audio information is acoustically confusable with acoustic information corresponding to other tokens in the context free grammar.

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5. The method of claim 4 wherein the selecting of the processing parameter values of the speech recognition algorithm includes optimizing said parameters according to an accuracy of the word spotting algorithm.

4. The method of claim 3 further comprising selecting processing parameter values of the speech recognition algorithm for application to the data representing the first set of audio signals according to characteristics of the word spotting algorithm.

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1. A method of collaboration between a plurality of associated portlets in a portal server comprising: defining a common Portlet Application Session Object, the Portlet Application Session Object comprising a data store session object and configured to allow each portlet in a portlet application to share session information; associating each portlet in a portlet application with a portlet descriptor describing a dynamic context name, each portlet configured to access the common Portlet Application Session Object, the dynamic context name referencing a dynamic context configured to be changed during runtime; and forming collaboration groups of portlets having corresponding dynamic context names, a collaboration group being a subgroup of the group of portlets in the portlet application, the portlets in each collaboration group sharing dynamic context changes through the Portlet Application Session Object.

2. The method of claim 1 wherein said context names define dynamic context values; each said group of portlets including a master portlet and at least one slave portlet.

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5. A method comprising: under control of an electronic device that is configured with executable instructions, determining a difficulty value of a word of a plurality of words based at least in part on a frequency of occurrence of the word in a corpus of writings; determining a contextual importance of the word based at least in part on a subject matter area; receiving information from or derived for one or more users, including at least a particular user's lookup history of definitions of words; calculating a score for the word of the plurality of words indicative of how difficult the word is for the particular user at least from the determined difficulty value, the determined contextual importance, and the information from or derived for one or more users; and based at least in part on the score, determining a comprehension guide to be presented with the word.

12. A method as recited in claim 5 , wherein the information received from or derived for the one or more users further includes at least one or more lookup requests for a definition of the word from the one or more users.

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1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learning the preferred microgenres of content of the user as contained in content items selected by the user, the method comprising: providing access to a content system including a set of content items organized by genre information that characterizes the content items, wherein the genre information is specified by the content system, and wherein the set of content items contains microgenre metadata further characterizing the content items; receiving incremental input entered by the user for incrementally identifying desired content items; in response to the incremental input entered by the user, presenting a subset of content items to the user; receiving actions from the user selecting content items from the subset; analyzing the microgenre metadata within the selected content items to learn the preferred microgenres of the user; analyzing the date, day, and time of the user selection actions and analyzing at least one of the genre information and microgenre metadata of the selected content items to learn a periodicity of user selections of similar content items, wherein similarity is determined by comparing the at least one of the genre information and microgenre metadata of the selected content item with a previously selected content item, and wherein the periodicity indicates the amount of time between user selections of similar content items relative to a reference point; and associating the learned periodicity with the at least one of the genre information and microgenre metadata of the similar content items; in response to receiving subsequent incremental input entered by the user, selecting and ranking a collection of content items, wherein content items containing microgenre metadata matching more learned microgenre preferences of the user relative to other microgenre preferences are ranked more highly than other content items of the collection containing microgenre metadata matching less learned microgenre preferences of the user relative to other microgenre preferences, and wherein the selecting and presenting the collection of content items is further based on promoting the relevance of those content items characterized by genre information or containing microgenre metadata associated with periodicities matching the date, day, and time of the subsequent incremental input; and presenting the ranked collection of content items on a display device in an order reflecting the ranking of the content items.

3. The method of claim 1 , wherein the set of content items includes at least one of television program items, movie items, audio/video media items, music items, contact information items, personal schedule items, web content items, and purchasable product items.

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12. The apparatus of claim 11 , wherein a syntax of the data interchange protocol modeling language comprises a JavaScript Object Notation syntax.

13. The apparatus of claim 12 , wherein the memory and computer program code are configured to, with the processor, cause the apparatus to: generate an indication of an error in an instance in which the determination indicates that the object is not assigned a type and name, the error denotes that the data interchange protocol document is invalid, and wherein the data interchange protocol document is received from one of the communication devices.

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9. A system comprising: a processor to: define a meta-data class having meta-data used to describe a class and constituent components of the class, the meta-data class having a property; create a compiled version of the class, the compiled version of the class being embedded with the meta-data class; create an instance of the class; receive, from an entity, a request to access the instance of the class; access, based on receiving the request, the property of the meta-data class embedded in the compiled version of the class to determine how to access data associated with the instance of the class; receive, based on accessing the property of the meta-data class, information regarding how to access the data associated with the instance of the class, the meta-data providing the information, the meta-data providing a value to the entity, and the value being used to identify the instance of the class; and access, based on the information regarding how to access the data associated with the instance of the class, the data associated with the instance of the class.

19. The system of claim 9 , where storage for the instance is allocated, using the meta-data, when the instance is created.

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1. A conferencing method, comprising: obtaining audio of a conference for an endpoint; detecting speech in the obtained audio; determining that the detected speech constitutes a speech fragment by determining that a duration of the detected speech is less than a predetermined duration; generating an indicium indicative of the determined speech fragment; and including the generated indicium in data of the conference for an endpoint.

13. The method of claim 1 , further comprising outputting the audio associated with the speech fragment.

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1. A method for proofreading text generated by a speech application, consisting of the steps of: finding all closed-class vocabulary words in said text; and, automatically highlighting only said closed-class vocabulary words in said text during proofreading.

8. The method of claim 1, wherein the step of highlighting said closed-class vocabulary words is in accordance with at least one of a plurality of predetermined rules.

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35. The computer-readable computer memory medium of claim 25 , the method further comprising: receiving a designation of one or more of the plurality of search result snapshot objects; and associating ratings with each of the designated search result snapshot objects.

25. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed on computer processor, facilitates searches for publications, by performing a method comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history representation between a plurality of different individuals and/or entities.

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1. A method for capturing videos, comprising: setting a video capture class in a framework layer of a first programming language, the video capture class inheriting a class in a video capture bottom layer library and registering a callback function for the video capture bottom layer library; receiving, by the video capture class, a video capture command sent by an application in an application layer of a second programming language other than the first programming language; sending, by the video capture class, the video capture command to the video capture bottom layer library which starts to capture video data according to the video capture command; obtaining, by the video capture class, the video data from the video capture bottom layer library by using the callback function; sending, by the video capture class, the video data to an encoder which is pre-set in the framework layer of the first programming language and instructing the encoder to encode the video data; and providing, by video capture class, video data codes obtained by the encoder to the application in the application layer.

3. The method of claim 1 , wherein registering a callback function for the video capture bottom layer library comprises: setting a first function by using a callback function interface of a header file defining external interfaces of a camera class in the video capture bottom layer library; and setting the first function as the callback function for the camera class in the video capture bottom layer library.

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7. The apparatus of claim 1 further comprising a capturing or logging component for capturing the at least one audio signal; and a presentation device for outputting the at least one first search result fused with the at least one second search result.

1. An apparatus for detecting an at least one word in an at least one audio signal, the apparatus comprising a computing platform executing: a phonetic and text decoding component for generating from the at least one audio signal a combined lattice, the combined lattice comprising an at least one text part and an at least one phoneme part, the phonetic and text decoding component comprising: a quality monitoring component for obtaining a quality assessment of multiple parts of the at least one audio signal; a speech to text engine for detecting an at least one indexed word from an at least one first part of the at least one audio signal, the at least one first part having high quality; a phoneme detection engine for detecting an at least one indexed phoneme from an at least one second part of the at least one audio signal, the at least one second part having lower quality than the at least one first part; and a phoneme and text lattice generator for generating a combined lattice from the at least one indexed word and the at least one indexed phoneme; and a search component for searching for the at least one word within the combined lattice, the search component comprising: a text search component for searching for the at least one word within the at least one text part of the combined lattice and generating an at least one first search result; a grapheme to phoneme converter for extracting an at least one phoneme from the at least one word; a phonetic sequence search component for searching for the at least one phoneme within the at least one phoneme part of the combined lattice and generating an at least one second search result; and a fusion component for fusing the at least one first search result with the at least one second search result to obtain a fused result.

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4. The learning organizer of claim 1 wherein the plurality of fill-in-blanks is provided for writing details of the learner.

1. A learning organizer, comprising: a sheet folded substantially along a central line to form a first half and a second half, the sheet includes a front portion and a rear portion; a plurality of flaps located on the first half; a plurality of holes located along and proximate to the central line; a plurality of lines on the rear portion; and a plurality of fill-in-blanks pre-printed on the second half; whereby the learning organizer provides assistance to a learner to break down learning information into each of the plurality of flaps.

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28. The computer readable storage medium of claim 27 , wherein the input source comprises a string.

29. The computer readable storage medium of claim 28 , wherein the string comprises a part of a script.

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21. The method of claim 9 additionally comprising the step of testing and tracking a user's knowledge of the language core over time.

9. A method of natural language training, the method comprising the steps of: developing a language core of words in only a single natural language from automatically analyzing current sources of language usage for one or more characteristics; developing material in the same natural language that utilizes the language core to a predetermined percentage; and analyzing the material over time to verify that it utilizes the language core to the predetermined percentage.

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1. At a computer system including a Web browser, a method for presenting a map of user-traversed Web sites from a Web browsing session, the method comprising: for each of a plurality of Web sites the Web browser traverses during a Web browsing session: an act of tracking various activities indicative of Web browser has contact with the traversed Web sites; an act of gathering a representative portion of accessed content from each the traversed Web sites, the representative portion being actual content from the traversed Web sites; subsequent to the Web browsing session ending and for each of the plurality of traversed Web sites traversed during the Web browsing session: an act of deriving a relative weight for the traversed Web site based on the various activities tracked for the traversed Web site during the Web browsing session, the relative weight indicative of significance of contact with the traversed Web site relative to other traversed Web sites; and an act of visually displaying a Web site map of the plurality of traversed Web sites traversed during the Web browsing session, the Web site map including visually displaying a geometric shape navigable item for each of the plurality of traversed Web sites, each geometric shape navigable item being specific to a single one of the traversed Web sites, and each geometric shape navigable item visually displaying and containing the accessed representative content from the corresponding traversed Web site, and such that the size of geometric shape navigable item varying based on the relative weight for the corresponding traversed Web site so as to visually represent the significance of the contact with the traversed Web site, including increased size of geometric shape navigable items to thereby indicate traversed Web sites having more significant contact and reduced size of geometric shape navigable items to thereby indicate traversed Web sites having less significant contact, such that the geometric shape navigable items for the plurality of traversed Web sites traversed during the Web browsing session are simultaneously displayed with varying sizes to thereby indicate significance of contact with the respective traversed Web site.

5. The method as recited in claim 1 , wherein the act of deriving a relative weight for the traversed Web site based on the various activities tracked for the traversed Web site during the Web browsing session comprises an act of accessing browsing activity from an activity repository.

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10. The method of claim 9 , wherein steps B through E are repeated a plurality of times during the interactive online event.

9. A method for monitoring a participant's level of attentiveness within an interactive online event, the method comprising: A) receiving video from a participant accessing an interactive online event; B) capturing a facial image from the received video; C) analyzing the captured facial image, wherein analyzing comprises: comparing the captured facial image to a plurality of predefined facial expressions; and matching the captured facial image to at least one predefined facial expression wherein each match assigns a value to the captured facial image; D) determining a level of attentiveness of the interactive online event by processing each assigned value; and E) providing the determined level of attentiveness to a host device accessing the interactive online event.

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7. The system of claim 1 , wherein the computer-executable instructions further cause the processing device to: successively generate words for the album narrative based at least on a statistical machine-learned model.

8. The system of claim 7 , wherein the computer-executable instructions further cause the processing device to: bias the generated words based at least on the preliminary narrative information extracted from the knowledgebase.

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21. An article of manufacture comprising: a storage medium; and computer-readable programming instructions stored on the storage medium and configured to program a computing device to perform operations including: receiving an audio input and a facial image sequence for a period of time at an electronic device, wherein the audio input includes a decipherable portion and an indecipherable portion; converting the decipherable portion of the audio input into a first symbol sequence portion, the converting including: detecting separations between spoken words in the decipherable segment based on the facial image sequence, and processing the decipherable portion into the first symbol sequence portion based in part on the detected separations; processing a portion of the facial image sequence that corresponds temporally to the indecipherable portion of the audio input into a second symbol sequence portion; and integrating the first symbol sequence portion and the second symbol sequence portion in temporal order to form a symbol sequence.

24. The article of claim 21 , wherein the operations further include further determining that the audio input is initiated when the facial image sequences indicate that a speaker begins to utter sounds, and determining that the audio input is terminated when a facial image of a speaker moves out of the view of a camera of the electronic device or when the facial image sequence indicates that the speaker has not uttered sounds for a predetermined period of time.

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1. A computer-implemented method, comprising: aggregating a plurality of authority documents; identifying a plurality of citations in at least one of the plurality of authoritative documents; identifying, in the plurality of citations, content that includes at least one noun-verb pair; assigning a unique control ID to represent each unique noun-verb pair from the plurality of citations; assigning a unique noun ID to represent each unique noun from the plurality of citations; generating a table having a plurality of rows, wherein each of the rows is assigned a citation ID; and storing in each row data indicating: portions of the content, the citation that corresponds to content, the control ID that corresponds to the content, and one or more unique noun IDs that correspond with to the content, such that the contents of the table are usable to analyze compliance with at least one noun-verb pair.

4. The computer-implemented method of claim 1 , further comprising: identifying a first set of citations and a second set of citations in the plurality of citations, wherein the first and the second set of citations are sourced from the plurality of authoritative documents, wherein the second set of citations is more recent in time than the first set of citations, and wherein each citation has content; assigning a unique citation ID to each citation in the first set and a same unique citation ID to each citation in the second set corresponding to the citation in the first set; comparing each citation in the second set to the corresponding citation in the first set that is assigned the same unique citation ID as the citation in the second set to determine an editorial status of each citation in the first set; identifying a difference between a citation in the second set with a citation in the first set that has the same unique citation ID as the citation in the second set; assigning to a citation of the second set having the same content as the content of a citation of the first set having the same unique citation ID a first editorial status; assigning to a citation of the second set having a unique citation ID that is not in the first set a second editorial status; assigning to a citation of the second set having different content as the content of a citation of the first set having the same unique citation ID a third editorial status; assigning to a citation of the second set having an indication of a deprecation of the content of the first set having the same unique citation ID a fourth editorial status; and generating a compliance report based on citations in the second set that have the first, the second, and the third editorial statuses.

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6. The method according to claim 4 , wherein the peripheral device application is a manual viewer application that can display manual information relating to the peripheral device.

4. A peripheral device control method for an information processing apparatus capable of managing a peripheral device, the method comprising: managing a peripheral device application via a peripheral device management screen to be displayed in a viewing area using peripheral device management function control information that defines information required to control each function; storing storage destination information relating to the peripheral device application in a storage unit; externally designating the storage destination information; and comparing first language information included in first storage destination information externally designated with second language information included in second storage destination information stored in the storage unit, wherein the display of the peripheral device management screen is switched using language information included in the peripheral device management function control information and the second language information, and the peripheral device application switches a view content of the viewing area using the first storage destination information when the first language information matches the second language information, and using third storage destination information, which can be generated by replacing the first language information included in the first storage destination information by the second language information, when the first language information does not match the second language information.

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4. The apparatus according to claim 3 , wherein the first selection unit preferentially re-selects basic term candidates, which match a lexical category decided by the keyword selected from keywords presented by the presentation unit and have high relevancies, as the basic terms.

3. The apparatus according to claim 1 , further comprising a search unit configured to conduct a refined search for the document set using a keyword selected from keywords presented by the presentation unit, and to obtain a partial document set, and wherein the clustering unit calculates the statistical correlation degrees between the basic terms based on the partial document set, calculates the conceptual correlation degrees between the basic terms based on the general concept dictionary, and re-clusters the basic terms based on the weighted sums, the second selection unit re-selects keywords of respective clusters from the basic terms and the technical terms based on a re-clustering result of the basic terms, and the presentation unit presents the re-selected keywords.

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29. A directional filter comprising: a processor; a non-transitory memory including instructions that when executed by the processor cause the directional filter to: determine one or more directional indicator values from composite audible signal data, the composite audible signal data including a respective audible signal data component from each of a plurality of audio sensors; determine a gain function from the one or more directional indicator values, the gain function targeting one or more portions of the composite audible signal data, wherein determining the gain function from the one or more directional indicator values includes determining, for each directional indicator value, a respective component-gain function based on the directional indicator value and a corresponding target value associated with the directional indicator value, and the respective component-gain function includes a distance function of the directional indicator value and the corresponding target value; and filter the composite audible signal data using the gain function in order to produce directionally filtered audible signal data, the directionally filtered audible signal data including one or more portions of the composite audible signal data that have been changed by filtering with the gain function.

37. The directional filter of claim 29 , wherein the non-transitory memory also includes instructions that when executed by the processor cause the directional filter to combine one or more of the respective component-gain functions.

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28. A system as in claim 21 , wherein the operations further comprise ranking term frequencies based on lengths of the inverted lists retrieved from the terms inverted index.

29. A system as in claim 28 , wherein the ranked inverted lists are searched according to the ranking.

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7. The computer-implemented method of claim 5 , wherein said entropy threshold is zero.

5. The computer-implemented method of claim 1 , wherein interactively narrowing said one or more candidate application programming interfaces comprises: identifying, for said substep, one or more parameters; for each parameter of said one or more parameters: dividing said one or more candidate application programming interfaces into one or more clusters; computing an entropy, based on said one or more clusters; responsive to said entropy being greater than an entropy threshold: presenting, by said natural language interface system, one or more narrowing questions and recalculating said entropy, based on said one or more narrowing questions, until said entropy is at or below said entropy threshold; and responsive to said entropy being equal to or less than said entropy threshold: assigning a value to said parameter.

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9. The speech recognition apparatus according to claim 1 wherein the segment relation value calculating unit calculates the segment relation value indicating a relative feature of the target segment with respect to one or more adjacent segments based on plural vectors which are base vectors that correspond to the target segment and one or more adjacent segments, and whose lengths indicate durations of respective unit segments.

10. The speech recognition apparatus according to claim 9 , wherein the segment relation value calculating unit calculates the segment relation value which is a value concerning an angle formed by an added vector obtained as a sum of the plural vectors and a predetermined reference vector.

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38. The system of claim 31 wherein receiving one of the text inputs is in response to a suggestion generated by the avatar.

31. A system for conducting commerce, the system comprising: a server computer comprising a processor device and memory coupled to the processor device, the server computer configured by a computer program product to: receive one or more text inputs corresponding to transaction requests; analyze the text inputs using natural language processing to build conversations based on the transaction requests; provide added information based on results of analyzing the transaction requests by the natural language processing; search a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response to trigger a facility to present additional information about the key concept; build by a conversational engine a conversation based on the transaction requests and key concept; statistically analyze the information stored in the database to derive useful market data based on the added information; track interactions with the user; store information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generate voice-synthesized, follow-up responses through the avatar in response to the transaction requests based on information stored in the database including the statistically analyzed added information regarding the transactions; receive subsequent text inputs from the user; analyze the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take; and cause the determined action to execute.

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1. A method comprising: classifying, by a computing device, speech into at least one voice cluster based on identified acoustic features of the speech, the at least one voice cluster corresponding to a text cluster and a customized language model that reflects characteristics of a speaker of the speech; determining, by the computing device, a text query based on the customized language model and one or more text strings determined based on the speech; receiving, by the computing device, search results based on the text query, each of the search results having a ranking indicating a measure of importance relative to other of the search results; and re-ranking, by the computing device, the search results based on re-scoring the search results using the text cluster; receiving a user interaction log comprising click data associated with a user interaction with the re-ranked search results; updating the at least one voice cluster based on the user interaction with the re-ranked search results; and updating the customized language model based on the click data associated with the user interaction with the re-ranked search results.

2. The method of claim 1 , comprising: re-assigning scores to the one or more text strings based on evaluating the one or more text strings using the customized language model.

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2. The temporal formatting method of claim 1 wherein each respective media item segment indicates flexibility metric data measuring a presentation quality of the respective media item segment at each of selected durations within the range of predictable elapsed presentation durations when the media item segment is presented by the at least one media presentation device for the selected duration; and operating the processor to assign the document presentation time value to each event in each respective media item segment includes selecting a duration, referred to as a selected duration, within the range of predictable elapsed presentation durations using the flexibility metric data, and assigning the document presentation time values to the respective media item segment on the basis of the selected duration; the selected duration being the duration in the range of durations that simultaneously produces document presentation time values that satisfy the temporal constraint data specified between the respective media item segment and a second media item segment and that provide an acceptable presentation quality when the respective media item segment is presented by the at least one media presentation device for the selected duration.

1. A method of temporally formatting first and second temporally related media items included in a time-dependent document in an information presentation system; the information presentation system including memory for storing data, a processor connected for accessing the data stored in the memory, and at least one media presentation device; the data stored in the memory including instruction data indicating instructions the processor executes; the method comprising: operating the processor to obtain, for each of the first and second media items, at least one pair of temporally adjacent media item event data items, referred to as a pair of temporally adjacent events, identifying a media item segment; each event in each pair of temporally adjacent events marking a point in time in the respective media item such that a second event in the pair of events follows a first event in time; each media item segment indicating whether occurrence of the media item segment in the time-dependent document is predictable or unpredictable; operating the processor to obtain temporal constraint data indicating a time ordering relation value specified between first and second temporally related event data items, referred to hereafter as a pair of temporally related events, identified from among the temporally adjacent events; a first one of the temporally related events being an event included in a media item segment in the first media item and a second one of the temporally related events being an event included in a media item segment in the second media item; operating the processor to obtain a durational time data item, hereafter referred to as a duration, for each respective media item segment; each durational time data item indicating an elapsed time for presenting the respective media item segment on the at least one media presentation device; each durational time data item further indicating whether the duration is predictable or unpredictable; each predictable duration indicating a range of predictable elapsed presentation durations for a respective media item segment; and for each respective media item segment having a predictable occurrence and a predictable media segment duration, operating the processor to assign a document presentation time value to each event included in the respective media item segment using the range of predictable elapsed presentation durations indicated for the respective media item segment and using the temporal constraint data specified between the respective media item segment and a second media item segment; each respective media item segment for which document presentation time values are assigned having a computed presentation duration falling within the range of predictable elapsed durations for the respective media item segment; the document presentation time values assigned satisfying the temporal constraint data specified between the respective media item segment and the second media item segment.

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11. A security system comprising: a plurality of sensors configured to sense security breaches and generate detection signals based thereon; a controller configured to receive the detection signals from the plurality of sensors and selectively generate an alarm signal in response to the detection signals; a database accessible by the controller, the database storing a user identification for each of a plurality of users of the security system and a preferred language for communicating with each of the plurality of users of the security system, the preferred language being selected from a plurality of different available languages; and a user interface in communication with the controller, the user interface comprising an input device configured to receive a user identification to identify a particular user and a communication device configured to communicate with the particular user in the user's preferred language, and wherein in response to at least one of the sensors sensing a security breach, the communication device provides an indication to the particular user that an alarm signal will be issued, the indication being provided in the particular user's preferred language and including instructions given in the particular user's preferred language regarding how to abort the alarm signal.

14. The system of claim 11 , wherein the communication device includes at least one of a display, a speaker, and a printer.

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2. The method according to claim 1 wherein the method further comprises the steps of pre-recording words describing facial expressions in the database.

3. The method according to claim 2 wherein the method further comprises the steps of using pamphlets of facial expression coordinates of facial expressions in the database and associating each facial expression with the pre-recorded words.

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1. An information processing device comprising: a memory, one or more processors coupled to said memory for executing: a communication unit configured to transmit textual information; a schedule storage unit configured to store schedule information; a keyword storage unit configured to store multiple keywords that are classified into multiple categories; a keyword extraction unit configured to extract keywords from the textual information transmitted by the communication unit on the basis of the keywords stored in the keyword storage unit, and specify one category corresponding the extracted keywords when extracting a keyword which was classified into a plurality of categories based on a position thereof and relationships to other words in the text information; a schedule information creation unit configured to create new schedule information or revised schedule information which causes schedule information stored in the schedule storage unit to be updated, based on the keywords extracted by the keyword extraction unit and the categories of the extracted keywords; and a schedule updating unit configured to store the new schedule information into the schedule storage unit, and update the schedule information stored in the schedule storage unit with the revised schedule information, wherein the schedule information creation unit is configured to: determine whether the extracted keywords include a keyword classified to a category for revising the schedule, indicating completion of a job, or settlement of existing schedule information, and create the new schedule information including date and content when determining there is no keyword classified to the category for revising the schedule, indicating completion of a job, or settlement of existing schedule information; and create schedule information for updating the existing schedule information when determining there is a keyword classified to the category for revising the schedule, indicating completion of a job, or settlement of existing schedule information, and wherein the schedule updating unit is configured to: compare the new schedule information with the schedule information stored in the schedule storage unit to find a similar schedule information which is similar to the new schedule information, update the found similar schedule information with the new schedule information when finding the similar schedule information, and store the new schedule information in the schedule information storing unit when not finding the similar schedule information; and compare the schedule information for modifying and the schedule information stored in the schedule storage unit to find a similar schedule information which is similar to the schedule information for modifying, update the found similar schedule information with the schedule information for modifying when finding the similar schedule information stored in the schedule storage unit, and store the schedule information for modifying in the schedule storage unit when not finding the similar schedule information in the schedule storage unit.

5. The information processing device according to claim 1 , wherein the keywords include a combination of an arbitrary word and a specified word, and the keyword extraction unit is configured to extract the arbitrary word from the textual information when finding the text sequence matching with the keyword comprising the combination of an arbitrary word and a specified word.

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1. A system for converting user-selected printed text to a synthesized image sequence, comprising: processing electronics configured to receive an image of text over a network, the text being a passage from a source text, to translate the text of the image of text into a machine readable format, and, in response to receiving the image: to determine the source text from the text; to search for and to receive, from a source other than the image of text, auxiliary information comprising another passage within the source text; and to generate model information based on the auxiliary information and the text translated into the machine readable format.

31. The system of claim 1 , wherein the processing electronics are further configured to translate the image of text using a handwriting recognition engine.

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3. A speech processing device according to claim 1 , wherein said phrase determination unit further comprises a section designation unit that is configured to designate section information of input speech, and said phrase determination unit is configured to temporarily change the threshold within a set section for each section set by said section designation unit.

1. A speech processing device comprising: an analysis unit that is configured to output a feature amount by performing speech detection/analysis of input speech; and a speech recognition unit that is configured to output a recognition result by performing speech recognition based on the feature amount, wherein: said speech recognition unit comprises a phrase determination unit that is configured to determine a phrase boundary based on comparison between a hypothetical word group generated by the speech recognition and a word representing phrase boundary set in advance, said speech recognition unit is configured to output the recognition result for each phrase up to the phrase boundary determined by said phrase determination unit, said phrase determination unit is configured to stand by until an occupation ratio of a number of the words representing the phrase boundaries in the hypothetical word group generated by the speech recognition unit to a number of all the words of the hypothetical word group exceeds a set threshold, and said phrase determination unit is configured to determine the phrase boundary based on a likelihood of the word representing the phrase boundary in the hypothetical word group when the occupation ratio exceeds the set threshold.

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9. At a computer system, the computer system including a processor and system memory, a method for providing technical assistance services for a developing software product, the developing software product being developed by a plurality of different product development groups, one or more other software developers developing other software products that are to depend on at least a portion of the developing software product, the technical assistance service allocated to a software developer to assist the software developer in developing a dependent software product, the method comprising: an act of a service allocation module receiving a service request for technical assistance services from a software developer that is developing another software product that is depend on at least a portion of the functionality of the developing software product, the service allocation module controlling the allocation of service requests to a plurality of different service providers, the developing software product having a functionality defined by the plurality of different development groups, changes to the functionality of the developing software product being determined by at least one group of the plurality of different development groups, such that changes to the functionality of the developing software product is determined independent of the one or more other software developers developing other software products that are to depend on at least a portion of the developing software product and wherein changes to the functionality of the developing software product cause changes in the technical assistance; an act of accessing request allocation criteria for the software developer, at least one request allocation criterion included in the service request, at least one request allocation criterion maintained at the service allocation module; an act of the processor identifying an optimum service provider, from among the plurality of service providers, for servicing the service request by matching the accessed request allocation criteria and service provider characteristics to provide a match in accordance with a routing algorithm; an act of sending the service request to the optimum service provider; an act of receiving an answer to the to the service request from the identified service provider, the answer is based at least in part on the service provider's expertise with respect to the at least one portion of the developing software product's functionality that the other software product is to depend on; and an act of at least notifying the software developer of the existence of the received answer.

12. The method as recited in claim 9 , wherein the act of identifying an optimum service provider that is to respond to the service request comprises an act of identifying a service provider from a service providers that are located in different locations around the world.

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12. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause data processing apparatus to perform operations comprising: accessing a video feed that captures an object in at least a portion of the video feed; operating a generative tracker to capture appearance variations of the object in the video feed; operating a discriminative tracker to discriminate the object from the object's background as captured by the video feed, wherein operating the discriminative tracker comprises using a sliding window to process data from the video feed, and advancing the sliding window to focus the discriminative tracker on recent appearance variations of the object in the video feed; and training the generative tracker and the discriminative tracker based on the video feed, wherein the training comprises updating the generative tracker based on an output of the discriminative tracker, and updating the discriminative tracker based on an output of the generative tracker; and tracking the object with information based on an output from the generative tracker and an output from the discriminative tracker.

13. The computer program product of claim 12 , wherein the operations further comprise: operating the discriminative tracker to use information based on an output of the generative tracker to reacquire the object in the video feed after an occlusion of the object in video feed or change in viewpoint or illumination of the video feed; and operating the generative tracker to use information based on an output of the discriminative tracker to focus on the object.

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3. The invention of claim 1 , wherein step (b) comprises: (b1) generating multi-level hierarchical groupings of Internet Protocol (IP) addresses in the association based on similarities between at least first and second levels of domain names in failed domain-name queries made by hosts corresponding to the IP addresses; (b2determining, for each hierarchical grouping, a highest percentage of failed domain-name queries for which a most recently added IP address in the hierarchical grouping has at least first and second levels of domain names in common with another IP address in the hierarchical grouping; and (b3) identifying each highest-level hierarchical grouping having its determined percentage more than a specified percentage threshold as a candidate cluster of hosts.

1. A computer-implemented method for detecting malicious software agents, the method comprising: (a) constructing an association based on a plurality of failed queries for domain names sent to one or more domain-name servers by a plurality of hosts during a time period; (b) deriving, from the association, one or more candidate clusters of hosts; (c) determining, for each candidate cluster and for each of a plurality of time intervals during the time period, a number of new domain names appearing in the failed queries of the candidate cluster during the time interval; (d) determining, for each candidate cluster, a freshness metric based on the numbers of new domain names for the plurality of time intervals in the time period; and (e) detecting one or more malicious software agents on the hosts based on the one or more freshness metrics.

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51. The computer-readable medium of claim 27 , further comprising: (B) identifying a first formula in a first one of the plurality of cells; (C) identifying a second formula in a second one of the plurality of cells; and (D) generating a general formula based on the first formula and the second formula.

27. A non-transitory computer-readable medium comprising computer program instructions executable by a computer processor to perform a method, the method comprising: (A) converting a plurality of atomic tuples, representing a plurality of cells stored in a grid, into a plurality of schema tuples, the method comprising: (A) (1) assigning a plurality of logical types to theplurality of atomic tuples; (A) (2) assigning a role of locator to a first subset of the plurality of cells based on the plurality of logical types; (A) (3) extracting from the plurality of atomic tuples a locator tuple slice, wherein the locator tuple slice comprises a plurality of locator tuples corresponding to a plurality of contiguous cells, from the plurality of cells, having the role of locator and forming a 1XN shape within the grid; (A) (4) determining, based on values of at least some of the plurality of contiguous cells, whether any empty cells in the plurality of contiguous cells implicitly contain missing values; (A) (5) if any of the empty cells are determined to implicitly contain missing values, then storing the missing values of the locator tuples of the locator tuple slice corresponding to the cells which are determined to implicitly contain missing values; and (A) (6) converting the plurality of locator tuples into a plurality of logical schema tuples corresponding to the plurality of locator tuples, wherein each of the plurality of logical schema tuples comprises a type of the corresponding locator tuple and a value of the corresponding locator tuple.

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19. A system for maintaining a data related to tagging, comprising: one or more processors and one or more memories storing computer-usable instructions configured for: a tag database configured to store data related to tagging by storing: tag information comprising a first tag, user information, and tagged content information, the tagged content information identifying first tagged content tagged with the first tag, the user information identifying a first user that tagged the first content with the first tag; a tag access service configured to provide, on a plurality of computing devices associated with the first user, a user experience layer with access to one or more portions of the data related to tagging; the user experience layer configured to: provide a visual representation of at least some of the data related to tagging; and provide an interactive user interface, through the tag access service, to at least a portion of the data related to tagging; wherein a tag collection is represented as a bi-partite graph, the bi-partite graph is traversed to determine that the tag collection corresponds to a category, and the personal tag collection is provided to a user based upon a topic of interest derived from the category.

20. The system of claim 19 , wherein the tag database is further configured to store data related to tagging by storing query information, or comprising a first query submitted by the first user to identify the first content.

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1. A method comprising: obtaining, using one or more computing devices, context data for a current context of a self-driving vehicle; determining, using the one or more computing devices, a contextually-determined action for the self-driving vehicle based on the obtained context data and a reasoning model, wherein the reasoning model was determined based on multiple sets of training data, wherein the multiple sets of training data include multiple context data and action data pairings, and wherein determining the contextually-determined action for the self-driving vehicle comprises determining, using a premetric, closest context data in the multiple sets of training data that is closest to the current context based on the premetric and determining an action paired with the closest context data as the contextually-determined action for the self-driving vehicle, wherein the premetric is a Minkowski distance measure of order zero; determine, using the one or more computing devices, whether performance of the contextually-determined action results in an indication of an anomaly for the self-driving vehicle; determining, using the one or more computing devices, a portion of the reasoning model that caused the determination of the contextually-determined action that resulted in the indication of the anomaly for the self-driving vehicle based on the obtained context data; updating, using the one or more computing devices, the portion of the reasoning model that caused the determination of the contextually-determined action that resulted in the indication of the anomaly for the self-driving vehicle, in order to produce a corrected reasoning model; obtaining, using the one or more computing devices, subsequent contextual data for a second context for the self-driving vehicle; determining, using the one or more computing devices, a second contextually-determined action for the self-driving vehicle based on the obtained subsequent contextual data and the corrected reasoning model; and causing performance, using the one or more computing devices, of the second contextually-determined action for the self-driving vehicle.

2. The method of claim 1 , wherein the reasoning model is a case-based reasoning model.

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1. A database network router apparatus for data tokenization, the apparatus comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: receive a request directed to a tokenized database, wherein the tokenized database contains one or more tokenized data values and wherein the request does not include any tokenized data values; apply one or more rules to the request; rewrite the request based on at least one of the one or more rules, wherein the rewritten request is configured to cause one or more non-tokenized data values specified in the request to be tokenized by a software agent resident on the tokenized database when data is added to the tokenized database as a result of the request and wherein the rewritten request is configured to cause the tokenized database to return non-tokenized data values when data is received from the tokenized database as a result of the request; and transmit the rewritten request to the tokenized database.

2. The database network router apparatus of claim 1 , wherein applying one or more rules and rewriting the request comprises: selecting a retrieval rule when the database access request is a data retrieval request; and rewriting the request to insert a de-token command into the request, the de-token command signaling to a software agent resident on the tokenized database to de-tokenize the tokenized data values retrieved as a result of the request prior to transmitting the data values back to the database network router.

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9. A computing device comprising at least one computer executable module for performing the method of claim 6 .

6. A method for using templates having associated metadata files, the method comprising: parsing all the metadata files; storing a single file for each template in a UI (“User Interface”) accessible location based upon whether the template is a user-created template, a pre-defined template, an item template or a project template; building an index of all the templates; displaying the index in a customized UI, wherein the UI displays an identifier for a template in a format depending upon whether the respective template is a user-created template, a pre-defined template, an item template or a project template; receiving a selection of a template from the index; invoking a template engine based upon the selection of the template from the index, the template engine causing reading of a metadata file associated with the selected template, the metadata file including three sections, a TemplateData section that defines an appearance of the selected template, a TemplateContent section that defines content and creation parameters of the selected template and a ReplaceParameters section, wherein the metadata file provides information regarding the template contents and template creation process and wherein the metadata file determines whether data to be created will be created in a separate folder for the data, wherein the metadata file is created by using inference rules to index at least one file by determining elements of the at least one file to be generalized; performing parameter substitution to enable replacement of key parameters on template instantiation; creating a project according to specifications of the metadata file.

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5. The method of claim 3 wherein each said certainty region is enlarged by one of a selected set of factors to create an associated one of said confidence regions.

3. The method of claim 2 wherein confidence regions are formed as enlarged certainty regions.

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2. The method recited in claim 1, wherein the step of incorporating the specific data table includes: blowing the specific data table into a PROM which is thereupon incorporated into the inserter.

5. The method recited in claim 2 further comprising the step of: blowing a PROM identification code into the PROM.

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11. The system of claim 10 , where the processor is further programmed to: receive a request to undo a selected one of the displayed plurality of edited changes associated with the editable file; and revert the selected one of the plurality of edited changes associated with the editable file.

10. A system, comprising: a display; a user input device; and a processor programmed to: display a plurality of edited changes associated with an editable file on the display in response to receipt of a request via the user input device to display the plurality of edited changes; display, proximate to the displayed plurality of edited changes, a separate contextual representation of the editable file that comprises a contiguous series of individually expandable and compressible blank representations of pages of the editable file, where each subsequent blank page representation in the contiguous series shares one common border with a respective previous blank page representation in the contiguous series; display a context indicator within an expanded blank page representation of the separate contextual representation of the editable file that represents a location within the editable file associated with a first of the displayed plurality of edited changes; and iteratively update, in response to detection of user selections of elements of the displayed plurality of edited changes received via the user input device, the context indicator within iteratively expanded blank page representations of the separate contextual representation of the editable file to represent a location within the editable file associated with each selected element of the displayed plurality of edited changes.

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17. The system of claim 16 , wherein which of said search results are provided in said subset is based on said style of writing of said search results as compared to said user writing style specific to said document.

16. The system of claim 13 , wherein said instructions further include instructions to associate each of one or more of said reference sources with at least one style of writing.

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19. A computer-implemented system for assessing brain health of a person, wherein the computer-implemented system comprises a processor executing instructions for learning a function mapping, the computer-implemented system: receiving inputs from a data collection module installed at one or more electronic devices, the inputs associated with one or more interactions of the person with the one or more electronic devices, the inputs recorded by the data collection module without requiring additional actions by the person while the inputs are recorded; computing, by the computing system, a brain health metric by learning the function mapping from the inputs to the brain health metric, wherein the brain health metric is a percentile rank relative to a population of users, the brain health metric indicating the person's likelihood of being in at least one of a cognitive state and a neuropsychological state; and outputting, by the computing system, the brain health metric.

23. The computer-implemented system of claim 19 , wherein learning the function mapping comprises: using a loss function with one of a linear function and a non-linear function; and identifying a set of optimal weights that produce a minimum of the loss function.

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1. A device for determining interest, comprising: a storage device that stores, on a user-by-user basis, a co-occurrence frequency in correlation with a user, the co-occurrence frequency indicating how many times a pair of words is used in a same cluster of a first document, on a pair-by-pair basis, to which the user gained access previously; a hardware processor configured to: accept, from a person who is to conduct a search, designation of a second document and any one of a plurality of users; and determine that, among a plurality of pairs of words, a pair which is used in a same cluster of the designated second document and which also satisfies a predetermined condition of the co-occurrence frequency corresponding to the designated user is a particular pair in the second document.

3. The device according to claim 1 , wherein the predetermined condition is that a ratio of the co-occurrence frequency to either one of a volume of the number of all words or a volume of the number of all pages in the first document is equal to or greater than a predetermined ratio.

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

17. The system of claim 15 , wherein the composition model is a Naive Bayes model.

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1. A system comprising: a processor; a data bus coupled to the processor; and a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code used for identifying unchecked criteria in unstructured data within a form and comprising instructions executable by the processor and configured for: identifying checked data in a form; identifying a first set of unstructured data as pertinent to the checked data in the form; and, identifying unchecked criteria in unstructured data within the form based upon the identifying the first set of unstructured data, the identifying comprising detecting and classifying text spans representing the unchecked criteria within the form to facilitate accurate interpretation of the text spans, the unchecked criteria comprising a discrete item that represents a question in the form lacking a response.

2. The system of claim 1 , further comprising: identifying a first checklist section in the form, the first checklist section containing a first set of checklist data pertinent to the checked data in the form.

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11. The computer of claim 1 , wherein execution of the programming by the processor configures the computer to: when initializing the configuration specified in the XML configuration file: adjust the display priority for each item based on a boost, bury, or suppress rating, the boost rating indicating to adjust the display priority of the item upwards, the bury rating indicating to adjust the display priority of the item downwards, and the suppress rating indicating to not display the item.

12. The computer of claim 11 , wherein execution of the programming by the processor configures the computer to: when generating the XML dimension hierarchy file, output to the XML dimension hierarchy file a ranking that is calculated based on the adjusted display priority of the item from the configuration file as the at least one synonym to index each item.

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23. A system comprising: at least one processor; and a computer-readable medium containing program code that when executed cause the at least one processor to perform operations comprising: receiving, at a server device and from a client device, a search query entered on the client device by a user; determining, using the server device, that the user belongs to at least a first population group; determining, using the server device, that at least a first article is responsive to the search query; determining, using the server device, an interest value reflecting an interest of the first population group in the first article, the interest value based on at least one selection of the first article made when the first article was previously presented to at least one member of the first population group in response to an earlier search query identical to the search query; determining, using the server device, a first ranking score for the first article, the first ranking score based at least in part on the interest value; and outputting a search result from the server device to the client device in response to the search query, the first article ranked in the search result according to the first ranking score.

43. The system of claim 23 , wherein the interest value is based at least in part on a total selection score, a selection score based at least in part on the first population group, a smoothing factor, a number of times a query was input by members of the first population group, and a number of times a query was input.

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22. The method of claim 8 , additionally comprising: sending the first and second audio annotations to a processing device external to the acquisition device, converting the form of the first and second audio annotations into data of respective first and second character strings, and storing the data of the plurality of content items along with the associated first and second character strings as representations of the respective first and second annotations.

25. The method of claim 22 , wherein sending the first and second audio annotations to a processing device includes use of a utilization device different from the acquisition device for sending the audio annotations through a network to the processing device, and the first and second character strings are sent back to the utilization device from the processing device through the network.

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1. A computer-implemented method of predicting a user behavior with respect to an item, the method comprising: arranging a memory to store a factor graph specifying a bi-linear collaborative filtering model, wherein the factor graph is updated based on: one or more latent user traits, the latent user traits including one or more demographic traits; one or more latent item traits, the latent item traits including one or more product feature descriptions or service feature descriptions; and a determination of an inner product of at least one latent user trait and at least one latent item trait, the factor graph comprising a plurality of probability distributions representing belief about the one or more latent user traits and the one or more latent item traits of the bi-linear collaborative filtering model; predicting the user behavior with respect to a plurality of different user and item pairs by arranging a first processor to apply an inference process to the factor graph; recommending, via an output, at least one of the plurality of items to the user based at least in part on the predicted user behavior; and updating a variance of the plurality of probability distributions based at least in part on actual user behavior.

4. A method as claimed in claim 1 , wherein the first processor is arranged to update a variance of the plurality of probability distributions at specified time intervals.

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6. The method as described in claim 5 , wherein the performing of the threshold value calculation based on the textual characteristic factor and the data analysis characteristic factor to acquire the dynamic threshold score for each search term comprises: employing a linear regression model, Score 0 =F 0 (f 1 , f 2 , . . . ,fi), to perform a fitting calculation and to acquire a first threshold score, Score 0 , for the search term, wherein fi is a textual characteristic factor corresponding to the search term, i is an integer less than or equal to N, and N is a natural number; employing a linear regression model, Score 1 =F 1 (f′ 1 , . . . , f′ k ), to perform fitting calculations and to acquire a second threshold score, Score 1 , for the search term, wherein f ′ k is a data analysis characteristic factor corresponding to the search term, k is an integer less than or equal to M, and M is a natural number; and performing a fitting calculation based on the linear regression model Score =F(score 0 , score 1 )×p 1 ×p 2 to acquire the dynamic threshold score for the search term, wherein p 1 is a duty cycle of the first threshold score and p 2 is a duty cycle of the second threshold score.

5. The method as described in claim 1 , further comprising establishing the threshold value dictionary, including: performing a threshold value calculation based on the textual characteristic factor and the data analysis characteristic factor to acquire a dynamic threshold score for each search term; and saving the search term and the dynamic threshold score of each search term in a data dictionary format to the threshold value dictionary, wherein: the textual characteristic factor is a characteristic weight matched to the search term and the data information; and the data analysis characteristic factor is an analytic parameter characteristic weight corresponding to the search term.

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1. A text conversion method for converting a paragraph in a source language into a target language, adapted to an electronic device having a processor, wherein the paragraph comprises a plurality of source language terms, the text conversion method comprising: providing a term mapping table by the processor, wherein the term mapping table records a term mapping relationship between the source language and the target language; performing a tokenization process on the paragraph by the processor to obtain a plurality of tokenization results; comparing the tokenization results with the term mapping table by the processor to determine that each of the source language terms is belonging to a first type or a second type, wherein each of the source language terms belonging to the first type is corresponding to a single target language term, and each of the source language terms belonging to the second type is corresponding to a plurality of candidate target language terms; converting the source language terms belonging to the first type into the corresponding target language terms by the processor according to the term mapping relationship recorded in the term mapping table; regarding each of the source language terms belonging to the second type, calculating a co-occurrence relevance of a plurality of relevant terms corresponding to each of the candidate target language terms by using a language model by the processor, wherein each of the relevant terms is constituted by one of the candidate target language terms and at least one word before and after the candidate target language term in the paragraph; selecting a plurality of candidate language terms corresponding to higher ones of the co-occurrence relevance among the candidate target language terms by the processor, wherein each co-occurrence relevance corresponding to one of the selected candidate target language terms is higher than a first threshold; respectively translating each word in each of the selected candidate target language terms into a corresponding reference language word by using a dictionary supporting the target language and a reference language by the processor; determining a relevance between the corresponding reference language words in each of the selected candidate target language terms according to the dictionary and the corresponding reference language words by the processor, so as to select the candidate target language term having the highest relevance between the corresponding reference language words as the target language term; and converting the source language term into the target language term in the paragraph by the processor.

4. The text conversion method according to claim 1 further comprising: obtaining a source language data set and a target language data set through information retrieval and web mining; finding a source language text and a corresponding target language text respectively from the source language data set and the target language data set; generating a parallel corpus by using the source language text and the corresponding target language text; and expanding a content of the term mapping table according to the parallel corpus.

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34. The method as recited in claim 17 wherein said first type style is a bold type style.

17. In a digital processing system, a method of processing a binary text image to identify and distinguish a location of a first type style, said image containing at least a first region of said first type style and a second region of a second type style, comprising the step of eroding said binary text image with a first structuring element to provide a first destination image, using said first destination image to form a second destination image containing substantially only said first type style from said text image wherein the step of forming a second destination image further comprises the steps of, i) forming a seed image from said first destination image wherein said step of forming a seed image further comprises the steps of, a) dilating said first destination image vertically, b) closing said image horizontally, c) opening said image horizontally; d) dilating said image horizontally; and e) ANDing an image from step d) with said binary text image to form said seed image; said seed image comprising ON pixels only within regions of said first type style, ii) growing said seed image into a mask image to provide a third destination image, and iii) ANDing said third destination image with said binary text image to provide said second destination image said first structuring element more likely to provide a hit in said first region than in said second region; remaining pixels used to identify said location of said first type style, and distinguish said location of said first type style from said second region of said second type style.

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17. The computer storage medium of claim 16 , wherein identifying one or more candidate clusters of observations responsive to the generated query comprises: identifying one or more candidate clusters of observations responsive to the generated query using the cluster index.

18. The computer storage medium of claim 17 , wherein a respective summarized cluster for each of the one or more candidate clusters includes at least one attribute value that is included in the generated query.

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4. The method of claim 1 , wherein the causing of the selected at least one cybersecurity training action comprises assigning, using the computer system, the selected at least one cybersecurity training action to the user.

6. The method of claim 4 , further comprising determining, using the computer system, a proficiency level that the user is to achieve.

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21. The system of claim 15 , wherein at least one word in the set of score words is also included in the set of search words.

15. A system, comprising: a computing device; and a computer-readable storage device coupled to the computing device and having instructions stored thereon which, when executed by the computing device, cause the computing device to perform operations comprising: receiving a set of words for use in monitoring network traffic, each word having at least one metric associated therewith; transmitting respective requests to a plurality of computer-implemented social networks through respective application program interfaces (APIs) over a network, the respective requests each including a set of search words, the set of search words comprising a subset of words of the set of words; receiving a set of messages comprising at least one message from each of the plurality of computer-implemented social networks, each message in the set of messages comprising a message distributed through a respective computer-implemented social network and at least one search word in the set of search words; scoring each message in the set of messages based on metrics of respective score words in a set of score words to provide respective scores, the set of score words comprising a subset of words of the set of words, and at least one score word in the set of score words being absent from the set of search words; and providing the messages for display in a rank order by score in a user interface.

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11. The computer system of claim 9 , wherein the service description comprises a representation of the service.

9. A computer system comprising: one or more computer processors; and a computer readable storage medium containing instructions that when executed by the one or more computer processors are operable to: receive an application extensibility description for an application, the application extensibility description including a set of application extension points; receive a service description for a service, the service description including a set of service elements; receive a specification of an integration design comprising a plurality of atomic adaptation patterns to link particular service elements in the service description to particular application extension points in the application extensibility description, wherein the plurality of atomic adaptation patterns define a plurality of steps for integrating the service into a plurality of application layers of the application, the application layers comprising a presentation layer, a business process layer, a service layer, and a configuration layer, and wherein each atomic adaptation pattern comprises one or more ports coupled to particular service elements in the service description and one or more ports coupled to particular application extension points in the application extensibility description; generate an integration description based on the integration design, wherein the integration description is used to execute integration of the application with the service; generate a query for a recommendation for connecting an application extension point in the application extensibility description to a service element in the service description based on a context, the context being a state of the adaption/extension of the service into the application; search a semantic model to determine a search result indicating a recommended connection of an application extension point in the application extensibility description to a service element in the service description based on the query; and change the integration design based on the recommended connection.

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18. The method of claim 13 wherein the format includes text, audio, images and videos.

19. The method of claim 18 wherein the video format is presented in a sign language format.

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1. A method of assigning a direction of impact to an association between assets based on an impact of an event mapped to at least one of the assets, the method comprising the steps of: a computer creating a first topic map meta-model that identifies assets and events in a topic map based index with instance ontology based on a topic map meta model that identifies assets and a topic map meta-model that identifies events, mapping assets to events through at least one association between at least one asset of the topic map meta-model that identifies assets and at least one event of the topic map meta-model that identifies events; the computer assigning an identification in the first topic map meta-model to the at least one association between at least one asset of the topic map meta-model that identifies assets and at least one event of the topic map meta-model that identifies events; the computer creating a second topic map meta-model that identifies at least one association between at least one asset and at least one event in a topic map based index and instance ontology with the direction of impact of the event on an association in various scopes between assets, based on an impact of the event on at least one of the assets of the association; in response to a new event being added to the topic map meta-model identifying events, the computer re-creating the first topic map meta-model for the new event and the second topic map meta-model, adjusting the direction of impact associated with the association in the first topic map meta-model, the re-created first map meta-model including a topic map based index and instance ontology for the new event and the adjusted direction of impact; and the computer storing the re-created first topic map meta-model and the re-created second topic map meta-model into a repository.

2. The method of claim 1 , further comprising the step of the computer searching the first topic map meta-model and the second topic map meta-model stored in a repository, comprising the steps of: the computer receiving a query input from a user; the computer obtaining, from the query input, at least an identification of an association between at least one asset and at least one event in the first topic map meta-model; the computer searching the second topic map meta-model for the identification; and the computer displaying direction of impact assigned to the association in at least one scope to the user.

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38. The machine-readable non-transitory storage medium of claim 37 , further comprising instructions configured to cause a data processing system to perform operations including: deriving a time series using the transformed time-stamped data; and analyzing the derived time series using one or more time series analysis functions.

37. A machine-readable non-transitory storage medium, including instructions configured to cause a data processing system to perform operations including: analyzing, using a time series engine, a distribution of unstructured time-stamped data to identify a plurality of potential time series data hierarchies for structuring the unstructured time-stamped data, wherein a potential time series data hierarchy is a framework for structuring the data through use of multiple time series, and wherein the time series engine is at a server layer of a time series computing system; performing, using the time series engine, an analysis of the plurality of potential time series data hierarchies, wherein performing the analysis of the plurality of potential time series data hierarchies includes determining an optimal time series frequency and a data sufficiency metric for each of the plurality of potential time series data hierarchies; comparing data sufficiency metrics for the plurality of potential time series data hierarchies; selecting a hierarchy of the plurality of potential time series data hierarchies based on the comparison of the data sufficiency metrics; structuring the unstructured time-stamped data into structured time-stamped data according to the hierarchy and the optimal time series frequency, wherein structuring the transformed time-stamped data into the structured time-stamped data is performed using a single pass of the unstructured time-stamped data through the time series engine; computing a plurality of transformations of the structured time-stamped data using the single pass of the structured time-stamped data through the time series engine; transforming the structured time-stamped data into transformed time-stamped data according to the plurality of transformations; and providing, using an application programming interface, the transformed time-stamped data for visual presentation.

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1. A method for processing electronic mail comprising: computing a probability that a text string in an electronic mail message refers to an attachment as a function of a stored probability value for each of a plurality of sequences of words within the text string, the computing of the probability including computing a first probability that the text string refers to an attachment using a first set of stored probability values and, where the first probability exceeds a predetermined value, computing a second probability that the text string does not refer to an attachment using a second set of stored probability values, the probability that a text string in an electronic mail message refers to an attachment being computed as a function of the first and second probabilities; and where the electronic mail message lacks an attachment, prompting a user if the computed probability indicates that the text string refers to an attachment.

11. The method of claim 1 , further comprising, prior to computing the probability, identifying a language of the electronic mail message.

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13. The method of claim 12 , wherein generating dialog prosody information includes adjusting an emphasis tag on repeated information when the semantic structure of a current system utterance is identical to that of a previous system utterance.

12. The method of claim 9 , wherein generating dialog prosody information includes: generating discourse information for the semantic structure of the system utterance based on the speech act of the user utterance; generating prosody information, including an utterance boundary level, for the discourse information of the semantic structure; and generating an intonation pattern for the semantic structure of the system utterance based on the prosody information.

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22. A mobile device comprising: a display; a memory; and a processor communicatively coupled to the display and the memory, the processor being configured to implement a plurality of controllers, the controllers comprising: a device context determination controller configured to determine, based on a dynamic characteristic of the mobile device, a current device context value of at least one of a plurality of device context parameters, wherein the mobile device is associated with a user; a social context determination controller configured to receive, over a communications network, context information from each client device of a plurality of client devices, wherein each client device corresponds to a different social contact of a plurality of social contacts of the user, wherein the context information received from each client device comprises information relating to a social context of the client device of the social contact, and wherein the information relating to the social context of the client device of the social contact relates to historical application usage information of a plurality of applications of the client device of the social contact, and to determine a current social context value of at least one of a plurality of social context parameters based on the context information received from each client device of the plurality of social contacts of the user; a scoring controller, communicatively coupled to the device context determination controller and the social context determination controller, and configured to calculate, for each of the plurality of applications previously downloaded and stored on the mobile device, an application relevance score as a function of the current device context value and the current social context value; and a display controller, communicatively coupled to the scoring controller and the display, and configured to identify at least one of the plurality of applications downloaded to the mobile device as a pinned application, and dynamically update the display to show at least some of a plurality of application representations on a graphical user interface (GUI) rendered at the display, such that the application representations are arranged according at least to the application relevance scores, each application representation corresponding to one of the plurality of applications downloaded to the mobile device, the arranging comprising removing at least one application representation of the plurality of application representations according to a frequency of use of each of the plurality of application representations, reordering one or more application representations of the plurality of application representations according to the frequency of use of each such application representation, and listing an application representation corresponding to a most recently used application of the plurality of applications downloaded to the mobile device in a user-designated location of the GUI for the most recently used application, wherein the arrangement of the application representation of the pinned application is fixed and is not affected by changes in the application relevance scores.

27. The system of claim 22 , wherein: the scoring controller is further configured to determine a predicted future context based on the current device context value and the current social context value; and the display controller is further configured to associate at least one of the plurality of applications downloaded to the mobile device with a template associated with the predicted future context and to dynamically update the display of the plurality of application representations on the GUI according to the template associated with the predicted future context.

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20. The system of claim 19 , wherein the design document is a bill of materials or an approved manufacturing list.

19. A system, comprising: a database including a new document table with data sent from a computer associated with a first entity to a computer associated with a second entity, a previous document table with data of a design document sent from the computer associated with the first entity to the computer associated with the second entity, the design document being sent from the computer associated with the first entity before the data of the new document table, and an internal document table with validated data of the design document, at least a portion of the database being stored within a memory of the computer associated with the second entity; the computer associated with the second entity programmed to access the database and as follows: identify data of the new document table that has changed from the data of the previous document table; compare the validated data of the internal document table with the changed data of the new document table; and replace the changed data of the new document table with the validated data of the internal document table, the validated data being accessible to the second entity and not being accessible to the first entity.

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13. The improvement of claim 11 wherein the insert has an outer surface releasably frictionally locked against the receiver.

11. In a bone anchor, the improvement comprising: a) a shank having a body for fixation to a bone and an integral upper substantially spherical head having a first radius; b) a receiver having a base, a first pair of upright arms and an outer surface, the receiver upright arms defining an open channel, the base defining a chamber and a lower opening, the chamber communicating with both the channel and the lower opening, each arm having a through aperture formed therein; c) at least one insert disposed within the receiver chamber, the insert having a surface sized and shaped for frictional mating cooperation with the shank head, the insert further having a second pair of upright arms, each arm having an outwardly extending wing, each wing extending through one of the apertures of the receiver, the wings being engageable by tooling placed adjacent to the receiver outer surface for movement of the insert both toward and away from the shank head; and d) a resilient open retainer having a base, the retainer captured within the chamber and expandable about at least a portion of the shank head and wherein expansion-only locking engagement occurs between the shank upper portion and the retainer base and between the retainer base and the receiver, the retainer having a concave second substantially spherical surface with a radius smaller than the radius of the shank head, the second surface terminating at upper and lower edges, the edges temporarily frictionally mating with the shank head, providing a friction fit between the retainer and the shank head during non-locking angular manipulation of the shank with respect to the receiver.

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44. A system comprising: a device; and one or more computers programmed to interact with the device and to perform operations comprising: receiving a first instance identifier identifying a first instance that is characterized by first data in a structured data collection organized in accordance with a defined data model, a second instance identifier identifying a second instance that is characterized by second data in the structured data collection, and a first attribute identifier identifying a first attribute of the first and second instances; using the first attribute identifier and the first instance identifier to identify and extract a first collection of values of the first attribute of the first instance from two or more documents of an unstructured electronic document collection; using the first attribute identifier and the first instance identifier to identify and extract a second collection of values of the first attribute of the second instance from two or more documents of the unstructured electronic document collection; selecting a first subset of the first collection of values from amongst the values in the first collection of values as suitably characterizing the first attribute of the first instance; selecting a second subset of the second collection of values from amongst the values in the second collection of values as suitably characterizing the first attribute of the second instance; merging a first value of the first subset and a second value of the second subset into the structured data collection after and in response to the first subset and the second subset being selected as suitably characterizing the first attribute; generating machine-readable instructions for displaying a structured presentation including the first value and the second value, wherein the structured presentation denotes characterization of attributes of particular instances by values that characterize the attributes of the particular instances by virtue of an arrangement of identifiers of the particular instances and the values; and sending the machine-readable instructions to the device.

56. The system of claim 44 , wherein the device comprises a display screen and is programmed to visually present the structured presentation on the display screen, including physically transforming one or more elements of the display screen.

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6. The apparatus according to claim 1 , wherein the display unit displays an alert message including the coined word and the dependency relation sentence.

1. A document proofing support apparatus comprising: an input unit configured to receive input of one of at least one proof document and at least one entry document, the proof document including one or more sentences that is to be subjected to a proofing process, the entry document including one or more sentences that is to be subjected to an entry process; an analysis unit configured to perform a morphological analysis, a syntactic analysis and a dependency analysis on each of sentences included in the entry document and generate analysis information including a dependency relation that indicates a semantic connection between words, and to perform a morphological analysis on each of sentences included in the proof document and generate morphological analysis information; a detection unit configured to detect as a possible coined word character string a compound word having a nominal continuation relation by referring to the morphological analysis information, the nominal continuation relation being a relation of two or more consecutive words that can be nouns; a database unit configured to store syntactic information on a correspondence between a sentence included in the entry document and the analysis information; a retrieval unit configured to retrieve whether or not a dependency relation sentence exists, the dependency relation sentence including component words of the possible coined word character string as case elements and having a dependency relation other than the nominal continuation relation between the component words, and to determine the possible coined word character string as a coined word if the dependency relation sentence exists; and a display unit configured to display a message including the coined word.

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16. The computer system of claim 15 , wherein the plurality of instructions further comprises instructions that are executed by the processor to obtain, from at least one electronic resource, a first set of associated data that is associated with the extracted first data of interest, second data of interest comprises the common predetermined characteristic, and a second set of associated data that is associated with the second data of interest, and to display, independent of the text-based electronic communications and the at least one electronic resource, the extracted first data of interest, the obtained first set of associated data, the obtained second data of interest, and the obtained second set of associated data.

15. A computer system, comprising: a processor; a memory; and a program comprising a plurality of instructions stored in the memory that are executed by the processor to: detect receipt of text-based electronic communications; identify first data of interest with a predetermined characteristic in the text-based electronic communications; extract, from a plurality of text-based electronic communications, a plurality of instances of the identified first data of interest from the text-based electronic communications, at least two of the text-based electronic communications sent to different intended recipients, wherein each text-based electronic communication includes first data of interest with a common predetermined characteristic, and wherein each text-based electronic communication includes first data or interest differing from first data of interest of other text-based electronic communications, the computer system associated with sending the one or more text-based electronic communications; obtain, for each identified first data of interest, a first set of associated data that is associated with the extracted first data of interest, each initial first set of associated data from at least one electronic resource; and display, independent of the text-based electronic communications and the at least one electronic resource, a plurality of instances of the extracted first data of interest, each instance of the extracted first data of interest displayed with the corresponding first set of associated data.

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22. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving information relating to (i) a communication device that has received an utterance and (ii) a voice associated with the received utterance, the received information relating to the communication device including a geographic location of the communication device; comparing the received voice information with a plurality of voice signatures in a comparison group, the comparison group corresponding to a plurality of different individuals each having an associated address within a geographic region encompassing the geographic location of the communication device, wherein the comparison group includes at least one voice signature for each different identified individual; attempting to identify the voice associated with the utterance as matching the voice signature corresponding to one of the individuals in the comparison group; if the attempt to identify the voice associated with the utterance is unsuccessful, iteratively repeating the attempting to identity the voice associated with the utterance using a modified comparison group, the modified comparison group corresponding to a different geographic region than was used in a previous attempt to identify the voice associated with the utterance, the iterative repeating of the attempting to identify the voice associated with the utterance continuing until the voice associated with the utterance is successfully identified; and providing the communication device with access to one or more resources associated with the individual whose voice signature matched the voice associated with the utterance.

28. The non-transitory medium of claim 22 wherein providing the communication device with access to one or more resources comprises providing the communication device with access to at least one of personal information and personalized services.

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10. The computer-readable storage medium of claim 9 , wherein the phonetic scheme is stored in a user-readable file format.

9. A computer-readable storage medium comprising instructions that are executable and, responsive to executing the instructions, a computer: receives input to create a phonetic scheme, the phonetic scheme comprising one or more phonetic character combinations in a source language and one or more native characters in a destination language for each of the phonetic character combinations; stores the phonetic scheme in a format that can be transferred to another computer; translates a phonetic character combination into one or more native characters in the destination language using the phonetic scheme, the phonetic character combination being translated by a phonetic input application executed by the computer; and displays a selectable list of suggestions of one or more native characters in the destination language, the suggestions including the one or more native characters in the destination language, a plurality of phonetic equivalents to the phonetic character combination based on the phonetic scheme, and a plurality of sound-alike equivalents to the one or more native characters in the destination language.

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2. The method according to claim 1 wherein the step of incorporating symbols comprises: generating the public symbols table in the relational schema for public symbols in the changed program code file, the public symbols being symbols having a definition in the changed program code file; and generating the referenced symbols table in the relational schema for referenced symbols in the changed program code file, the referenced symbols being only referred to in the changed program code file.

3. The method according to claim 2 wherein the step of generating the public symbols table comprises: locating public symbols in the changed program code file; and adding the located public symbols to the public symbols table; and wherein the step of generating the referenced symbols table comprises: locating referenced symbols in the changed program code file; and adding the located referenced symbols to the referenced symbols table.

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1. A method for storing an XML document of a plurality of documents, the method comprising steps of: storing in a persistent repository a persistent representation of the XML document that includes a navigable representation and a streamable representation that is separate from said navigable representation, wherein the XML document includes a tree of nodes in a hierarchical relationship, each node of the tree of nodes having an immediate hierarchical relationship with at least one other node in the tree of nodes, wherein the streamable representation contains nodes of the tree of nodes that are in document order, wherein the navigable representation contains a subset of nodes of the tree of nodes, the subset of nodes including less than all nodes of the tree of nodes, and wherein each particular node of the subset of nodes in the navigable representation includes at least one pointer to content, of said each particular node, that is contained in the streamable representation, and at least one pointer to another node of the subset of nodes in the navigable representation, said at least one pointer to the other node in the navigable representation being one of: a pointer to a parent node of said each particular node, a pointer to a child node of said each particular node, a pointer to a sibling node of said each particular node, or a pointer to a previous sibling node of said each particular node; wherein the steps are performed by one or more computing devices.

15. The method of claim 1 , wherein there is at least one node in the XML document that is contained in the streamable representation and is not contained in the navigable representation.

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9. The method of claim 7 , wherein generating the hypothesized speech power spectral density function includes: retrieving parameters corresponding to the hypothesized speech power spectral density function from a pre-created speech codebook.

7. A method for determining spectral parameters corresponding to a segment of signal, the method comprising: receiving the segment of the signal from a plurality of sensors; generating a hypothesized noise power spectral density function; generating a hypothesized speech power spectral density function; combining the hypothesized power spectral density functions to obtain a spectral hypothesis; evaluating a likelihood that the spectral hypothesis corresponds to the segment of the signal based on application of a discriminant function evaluated using a preconditioned conjugate gradient (PCG) process configured for block Toeplitz type matrices with a block size corresponding to the number of sensors.

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1. A method comprising: receiving, by a network interface of a network device, a packet stream; identifying one or more packets within the packet stream that satisfy one or more conditions of a plurality of predefined conditions specified by a rule by pre-matching, by an acceleration device of the network device, the packet stream with the plurality of predefined conditions; identifying, by the acceleration device, for a full-match processing stage a candidate packet of the one or more packets that satisfies all of the plurality of predefined conditions by correlating the one or more satisfied conditions of the candidate packet; generating, by the acceleration device, for use by the full-match processing stage a matching token and a corresponding location of the matching token within the candidate packet for each of the plurality of predefined conditions; and determining, by a context-aware pattern matching and parsing (CPMP) processor of the acceleration device, whether the candidate packet meets the rule by performing the full-match processing stage including fetching and executing special purpose CPMP instructions to perform context-aware pattern matching processing on the packet, wherein the context-aware pattern matching processing includes one or more of string matching, regular expression matching and packet field value matching based on, for each of the plurality of predefined conditions, corresponding contextual information provided by the rule, the matching token and the corresponding location.

15. The method of claim 1 , wherein the special purpose CPMP instructions are fetched from one or more instruction caches.

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1. A method for providing text-based dialogue between communicants in a portable environment, the method comprising: selecting a first dialogue language for a first communicant using a first text-based input communication device; selecting a second dialogue language for a second communicant using a second text-based input communication device; entering text-based communication data from the first communicant using the first text-based input communication device in the first dialogue language, wherein the text-based communication data from the first communicant is displayed on a first communicant display; entering text-based communication data from the second communicant using the second text-based input communication device in the second dialogue language, wherein the text-based communication data from the second communicant is displayed on a second communicant display; transmitting a copy of the text-based communication data from the first communicant to the second communicant while the text-based communication data is entered by the first communicant; receiving the text-based communication data from the first communicant by the second communicant; transmitting a copy of the text-based communication data from the second communicant to the first communicant while the text-based communication data is entered by the second communicant; receiving the text-based communication data from the second communicant by the first communicant; displaying the received text-based communication data from the first communicant on the second communicant display; and displaying the received text-based communication data from the second communicant on the first communicant display, wherein the first text-based input communication device and the first communicant display are comprised in a first communicant system, and wherein the second text-based input communication device and the second communicant display are comprised in a second communicant system separate from the first communicant system.

9. The method for providing text-based dialogue of claim 1 , further comprising: initiating an electronic connection between the text-based input communication device using a telephonic communication protocol; and connecting a telephonic input communication device to the electronic connection to establish communication between the text-based input communication device and the telephonic input communication device with which to conduct the text-based dialogue.

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2. The computer-implemented method of claim 1 wherein receiving the first request and receiving the second request comprises receiving the first request and receiving the second request from a single party.

4. The computer-implemented method of claim 2 further comprising: identifying a target community associated with the single party; and based on the identified target community, selecting the information satisfying the second request from among multiple information options.

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10. The computer program product as set forth in claim 6 wherein the requesting client comprises a user interface to a user of a client device.

6. A computer program product for handling a user request for invoking a computer service comprising: a computer-readable, memory storage device; and one or more computer program instructions embodied by the computer-readable, memory storage device, for causing a computer processor upon execution to perform operations comprising: performing a first natural language (NL) analysis on one or more computer service user programming documents, wherein API user documents describe in structured natural language one or more structured Application Programming Interfaces (APIs) with one or more API elements, and wherein each API element corresponds to a parameter or argument to use or invoke the computer service; extracting the one or more API elements from a user programming document according to the first NL analysis; performing a second NL analysis on an unstructured request from a client to use or invoke the computer service, the unstructured request comprising natural language containing one or more request components; matching the one or more request components to the one or more API elements; constructing a structured API call using the matching request components for API elements; and performing one or more operations selected from the group consisting of submitting the constructed structured API call to the computer service on behalf of the client, returning the constructed structured API call to the requesting client, and returning a result from an invoked corresponding computer service to the requesting client.

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42. The method of claim 29 , wherein generating the tag comprises programmatically generating the tag based on one or more selections made by the operator of the web site, said one or more selections specifying at least a type of content to be displayed via said update handler.

43. The method of claim 42 , wherein the tag consists of a single line of JavaScript code.

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13. The system of claim 11 wherein the users are located in a same country as the user.

11. A system comprising: one or more processors programmed operable to perform operations comprising: obtaining a plurality of search results responsive to a search query submitted by a user, wherein each search result refers to a respective document that is associated with a respective plurality of click measures, each click measure relating to a different respective natural language and representing, at least, a measure of behavior of users associated with the respective language in regards to the document when the document was referred to in a search result previously provided in response to the search query; for each of a first plurality of the search results, reducing the click measure associated with the document referred to by the search result, wherein the click measure relates to a respective natural language that is incompatible with a natural language of the user; calculating a respective scoring factor for each of the first plurality of search results based on the respective click measures associated with the document referred to by the first search result; and ranking the search results based upon, at least, the calculated scoring factors.

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17. The invention according to claim 1 further comprising means for manually selecting a specialized language model.

1. A system for substantially automating transcription services for one or more voice users, said system comprising: means for receiving a voice dictation file from a current user, said current user being one of said one or more voice users; an audio player used to audibly reproduce said voice dictation file; means for manually inputting and creating a transcribed file based on humanly perceived contents of said voice dictation file; means for automatically converting said voice dictation file into written text; means for manually editing a copy of said written text to create a verbatim text of said voice dictation file; means for training said automatic speech converting means to achieve higher accuracy with said voice dictation file of current user; and means for controlling the flow of said voice dictation file based upon a training status of said current user, whereby said controlling means sends said voice dictation file to at least one of said manual input means and said automatic speech converting means.

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12. The method of claim 11 , wherein a gateway associated with said called telephone number receives said call.

14. The method of claim 12 , further comprising: a browser receiving said called telephone number from said gateway.

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7. The method of claim 1 wherein said search results are transmitted from said search engine to an intermediary site and formatted at said intermediary site.

1. A method for obtaining query results on a wireless mobile device comprising the steps of: speaking a query to said wireless mobile device; converting, in said mobile device, said query into text; transmitting said text by said mobile device using a messaging protocol over a wireless network to a search engine; performing a search based on said text with said search engine; transmitting search results using said messaging protocol over said wireless network; formatting said search results; and displaying said search results on said wireless mobile device.

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10. A computer program product stored in a computer readable medium, comprising computer instructions that, when executed by an information handling system, causes the information handling system to mine threaded online discussions by performing actions comprising: performing, by the information handling system, a natural language processing (NLP) analysis of one or more threaded discussions pertaining to a given topic, wherein the analysis is performed across one or more web sites with each of the web sites including one or more of the threaded discussions, wherein the analysis results in a plurality of harvested discussions; correlating the plurality of harvested discussions across a plurality of threads from the one or more web sites; identifying a question from the harvested discussions; identifying a plurality of candidate answers from the harvested discussions, wherein each of the plurality of candidate answers pertain to the identified question; aggregating and merging a selected plurality of harvested discussions corresponding to each of the candidate answers, wherein the selected plurality of harvested discussions are supporting evidence corresponding to the respective candidate answer; generating a supporting evidence score based on one or more factors of the supporting evidence for each of the candidate answers, wherein at least one of the factors is selected from the group consisting of a quality of the supporting evidence, and a quantity of the supporting evidence; generating an answer post score for each of the candidate answers based on an identification of a rating within the threaded discussions pertaining to the respective candidate answer; generating a post provider score for each of the candidate answers based on an identified expertise level that corresponds to a provider of the respective candidate answer; generating a follow-up score for each of the candidate answers based on one or more follow-up comments from posters that indicate that the respective candidate answer was correct; and scoring each of the plurality of candidate answers, wherein the scoring calculates an overall score corresponding to each of the candidate answers, wherein the overall score is based upon one or more component scores selected from the group consisting of the supporting evidence score, the answer post score, the post provider score, and the follow-up score, and wherein a selected answer has the highest overall score when compared to the other candidate answers.

13. The computer program product of claim 10 wherein the actions further comprise: identifying a plurality of follow-up postings corresponding to the identified question; analyzing each of the follow-up postings to identify a conversational move corresponding to each of the follow up postings, wherein at least one of the conversational postings is selected from the group consisting of an answer, a clarification, a rejection, or a different conversational move; and generating a contribution tree based on the follow-up postings and their identified conversational moves.

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82. The method of claim 13 , in which each vector in the set of vectors represents a corresponding query, and each feature of each vector represents a relevance of a corresponding document to the query.

13. A method of identifying pairs of similar vectors in a set of vectors, the method comprising: determining, using one or more computers, a partial similarity score for a vector x in a set of vectors and each other vector in the set of vectors, each partial similarity score representing a degree of similarity between features of the vector x and corresponding features of other vectors in the set of vectors; determining, using one or more computers, an upper bound, the upper bound being an estimate of the maximum similarity between non-processed features of the vector x and non-processed features of the other vectors, the non-processed features being features that have not been used to calculate the partial similarity scores; as long as the upper bound is greater than or equal to the similarity threshold, adding vectors to a candidate set of vectors and repeating the operations of determining a partial similarity score and determining an upper bound; when the upper bound is lower than the similarity threshold, determining partial similarity scores only for vectors in the candidate set of vectors; and identifying x and a vector y in the candidate set of vectors as similar vectors using the partial similarity score between x and y.

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31. The method of claim 1 wherein the optimization parameters are selected from the group consisting of hardware area, cost, time of execution, and power consumption.

1. A computer implemented method of developing a system architecture, performed by at least one processor of at least one computing device, comprising: defining, by the at least one processor, a plurality of resources constraints max N R1 , . . . max N Rn , for a plurality of kinds of resources R 1 . . . Rn, wherein each resource constraint maxN Ri is a maximum number of a kind of resource Ri available to construct the system architecture, wherein 1≦i≦n and n is an integer greater than 1; defining, by the at least one processor, a plurality of constraint values comprising a constraint value for each optimization parameter of at least three optimization parameters for the system architecture, wherein the at least three optimization parameters comprise a final optimization parameter; defining, by the at least one processor, a design space as a plurality of variants representing different combinations of a number of each kind of resource R 1 , Rn available to construct the system architecture, wherein each variant is a vector of the form: V n =( N R1 , . . . N Rn ) wherein N Ri 1≦i≦n represents the number of the kind of resource Ri, wherein based on the resource constraints, 1≦N Ri ≦max N Ri ; determining, by the at least one processor, a plurality of satisfying sets of variants by, for each of the optimization parameters except for the final optimization parameter: generating a universe of discourse set by sorting the plurality of variants of the design space; assigning a membership value to each variant of the universe of discourse set, wherein each membership value is within an interval [0,1], wherein, for each respective variant of the universe of discourse set, the membership value assigned to said each respective variant indicates a position of said each respective variant in the universe of discourse set; determining a satisfying set of variants from the universe of discourse set by determining a border variant of the universe of discourse set, wherein each variant of the satisfying set substantially satisfies the constraint value for the optimization parameter, wherein the border variant is the last variant of the universe of discourse set to satisfy the constraint value for the optimization parameter such that all variants to one side of the border variant in the universe of discourse set satisfy the constraint value for the optimization parameter and all variants to the other side of the border variant in the universe of discourse set do not satisfy the constraint value for the optimization parameter, and wherein the border variant is determined by performing a fuzzy search of the universe of discourse set using the corresponding membership values; determining, by the at least one processor, a set of variants based on an intersection of the plurality of satisfying sets of variants for the optimization parameters except the final optimization parameter; for the final optimization parameter: generating an ordered list of variants by sorting the set of variants; selecting a variant from the set of variants based on a position of the variant in the ordered list of variants; and developing, using at least one of the at least one processor and at least one other computer hardware, the system architecture using the selected variant.

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17. The computer-readable storage medium of claim 15 , wherein nodes of the input AST match the predicate expression query if each of the plurality of predicates is true for the nodes.

15. The computer-readable storage medium of claim 14 , wherein the predicate expression query comprises a plurality of the predicates of the matching library, each predicate expressed as a function call in the first procedural programming language to a function that creates a matcher object for the predicate, the matcher object determining whether the predicate is true for given nodes of the input AST.

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1. A method comprising: storing a query that references multiple tables; analyzing operations the query specifies on the multiple tables to detect at least one of: two particular tables of the multiple tables could be dimension tables by detecting a join of the two particular tables of said multiple tables that does not comprise an equijoin, or one or more particular tables of the multiple tables could be fact tables by detecting at least one of: a minimum operation, a maximum operation, an average operation, a summation operation, an online analytical processing (OLAP) function based on a table of said multiple tables, or a group by operation based on multiple columns of a table of said multiple tables; identifying one or more candidate dimension tables of the multiple tables at least in part by determining, based at least in part on content of the query, that a particular candidate fact table of the multiple tables appears in one or more equijoins with the one or more candidate dimension tables; based at least in part on determining which of the multiple tables could be fact tables, generating an execution plan for the query, the execution plan operating on the particular candidate fact table and the one or more candidate dimension tables; wherein the execution plan, when performed, processes at least some data from at least one dimension using at least one of the one or more candidate dimension tables before processing at least some data from the particular candidate fact table; wherein the method is performed by one or more computing devices.

2. The method of claim 1 , wherein determining which of the multiple tables could be fact tables comprises determining which of the multiple tables are referenced by aggregation operators.

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10. A computer program product embodied in a non-transitory computer readable medium, the non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising: creating a voice command mapping in response to loading a user interface page at a computing system by: identifying a markup language description of the user interface page loaded at the computing system, the identification of the markup language description occurring after loading the user interface page at the computing system; and generating the voice command mapping for the user interface page loaded at the computing system, wherein the voice command mapping maps a recognized word or phrase associated with at least one operation to one or more voice commands by parsing the markup language description identified from the user interface page to identify at least one user interface object specified by the markup language description configured to perform at least one operation responsive to a keyboard, mouse, or pointing device, the parsing of the markup language description being performed after loading the user interface page at the computing system, and the parsing does not create a modified version of the user interface page, wherein the voice command mapping uses a hash map data structure to store a relationship between at least one respective word or phrase to the at least one operation; processing an utterance in response to receiving the utterance at the computing system, the computing system displaying the user interface page, by: converting the utterance into a text representation of the utterance; determining a plurality of matches between the text representation of the utterance and multiple matching voice commands based on the voice command mapping for the user interface page loaded at the computing system; and performing a confirmation of a single matching voice command from among the plurality of matches.

12. The computer program product of claim 10 , wherein a user interface object of the at least one user interface object comprises an option menu.

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15. The method in accordance with claim 9 , a modification causing the table to be modified to the modified table comprising: changing values in cells in the table.

9. The method in accordance with claim 8 , at least one of the first set of query results comprising a table, and the second set of query results comprising a modified table.

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8. The non-transitory computer-readable storage medium of claim 7 , wherein the query includes the attribute identifier.

7. A non-transitory computer-readable storage medium storing instructions, the instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to: receive a query that includes one or more terms; identify, using the one or more terms, search results; determine an attribute identifier that identifies an attribute to be used in ranking the search results, the attribute being different from a measure of relevance of the search results to the query; calculate a combined score for each search result, included in the search results, based on an attribute value associated with the attribute and a value corresponding to the measure of relevance of the search result to the query; rank the search results based on the combined score calculated for each search result to obtain a first ranking of search results; divide, based on a threshold measure of relevancy, the first ranking of search results into a first subset of ranked search results and a second subset of ranked search results; rank search results included in the first subset of ranked search results and search results included in the second subset of ranked search results based on the attribute value to obtain a second ranking of search results, each of the search results included in the first subset of ranked search results being ranked relative only to other ones of the search results included in the first subset of ranked search results, and each of the search results included in the second subset of ranked search results being ranked relative only to other ones of the search results included in the second subset of ranked search results; and provide the second ranking of search results.

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19. The method of claim 11 , further comprising: determining a rate of change in the sentiment trend.

11. A computer implemented method for real-time monitoring of changes in a sentiment with respect to an input non-sentiment phrase, comprising: receiving the input non-sentiment phrase and at least one tendency parameter of the input non-sentiment phrase; identifying, in a data warehouse storage, at least one term taxonomy that includes the input non-sentiment phrase, wherein the data storage contains a plurality of phrases including sentiment phrases, non-sentiment phrases, and a plurality of term taxonomies, wherein each of the term taxonomies in the data warehouse storage is an association of a non-sentiment phrase with a sentiment phrase, wherein at least one of the term taxonomies includes the input non-sentiment phrase; computing, by a computer, a sentiment trend for the at least one of the term taxonomies including the input non-sentiment phrase; monitoring the sentiment trend to detect real-time changes in a direction of the sentiment trend for the at least one of the term taxonomies including the input non-sentiment phrase with respect to the at least one tendency parameter; and generating at least a notification when a change in the direction of the sentiment trend with respect to the input tendency parameter has occurred, wherein the at least one notification is generated in real time as the change in the direction of the sentiment trend has occurred.

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10. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving, from a separate entity, a request to generate a model, input data and a seed model; receiving a cost function associated with generation of the model, the cost function indicating an accuracy and one of speed and memory usage, wherein the cost function is formulated as: Accscore( ASR ( Xi ))= f ( Xi )→word accuracy and speed where the following definitions apply: f min( Xi )=−1* (word accuracy−β*speed), speed=(CPU time)/(audio time), β=a weighting factor to speed that provides a tradeoff between accuracy and speed Xi=a set of parameters that affect accuracy and speed, such as beam width, LM scale, MAP multiplier, maximum active arcs, duration scale; processing the input data based on the seed model and based on parameters that modify one of the accuracy and the one of speed and memory of the cost function, to yield an updated model; and outputting the updated model.

13. The system of claim 10 , wherein processing the input data further comprises building the updated model, tuning the updated model, and certifying the updated model.

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1. A compression process for executable code by a microprocessor, comprising decomposing the executable code into words, and compressing each word of executable code, wherein each word of compressed executable code comprises a predefined part of fixed length and a part of variable length whereof the length is defined by the part of fixed length, the process further comprising a step of combining all the parts of fixed length and all the parts of variable length of the words respectively into a block of parts of fixed length and into a block of parts of variable length, the respective positions of at least certain parts of variable length in the block of parts of variable length being saved in an addressing table.

4. The compression process as claimed in claim 1 , in which each of the words of the executable code to be compressed corresponds to an instruction.

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16. The system of claim 15 , wherein: the translation engine is further operable to apply a keyword translation at least one of prior to and after the translating the document data to natural language form; and the keyword translation is a separate translation from the translating the document data to the natural language form.

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

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11. The method of claim 1 , wherein the language model includes weightings for co-concurrence events between two or more words.

1. A method comprising: accessing a baseline language model that associates a respective baseline probability of occurrence with each of multiple different terms; obtaining information related to recent language usage from recent search queries that were submitted by multiple users of a search engine within a predetermined period of time; determining a quantity of occurrences of a particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; selectively modifying the baseline language model to independently revise the baseline probability of occurrence associated with the particular term based at least on the quantity of occurrences of the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time while maintaining unchanged a baseline probability of occurrence associated with a different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time by assigning a first probability to the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time that is greater than a second probability for the different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; and generating, by an automated speech recognizer using the modified language model, a transcription of one or more utterances of one or more different users of the search engine.

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17. The system of claim 15 , wherein the at least one stutter type is at least one of syllable repetition, phone elongation and silence/breath.

22. The system of claim 17 , wherein the at least one processor is further configured to detect phone elongation via detecting at least one of: fricatives exceeding a predetermined threshold, voice-bars exceeding a predetermined threshold, and vocalic sounds exceeding a predetermined threshold; wherein elongated phones include phones with or without a formant structure.