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12. A tangible computer-readable medium having computer-executable instructions stored thereon for: receiving a user query at a first location; extracting terms from the user query by parsing the terms from the user query on a term-by-term basis, determining if any terms in the user query are relevant to individual slots utilized by a search facility of a second location, and for those terms that are determined to be relevant to individual slots, filling those slots with the relevant terms; assigning the user query a ranking based on a weight assigned to at least a portion of the extracted terms; sending the user query to the second location for searching if the ranking of the terms meets a predetermined threshold and searching the user query at the second location; searching the user query at the first location if the ranking of the user query does not meet the predetermined threshold; and receiving a response from one of the first location or the second location.

21. The computer-readable medium of claim 12 , wherein sending the user query to the second location for searching comprises placing the extracted terms into a predetermined URL template.

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10. The data processing system of claim 8 , further comprising: executing the computer executable instructions to direct the data processing system to respond to a determination of a file type not found, and executing the computer executable instructions by the processor to signal an error not supported; executing the computer executable instructions by the processor to notify a caller; executing the computer executable instructions to direct the data processing system to respond to a determination of a decoder file is not obtained, executing the computer executable instructions by the processor to signal an error not found; and executing the computer executable instructions by the processor to notify the caller.

8. The data processing system of claim 7 , wherein the attachment metadata generator is called responsive to receiving the request from a user modifying the document, and wherein the processor unit executes the computer-executable instructions to direct the data processing system to call the attachment metadata generator further comprises the attachment metadata generator: calling a file type identifier to determine a file type of the attachment; responsive to a determination of the file type, identifying a decoder file to form an identified decoder file; and determining whether the identified decoder file is obtained.

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12. The computer-readable medium of claim 10 , wherein the timing data is calculated in real-time separately for each of the plurality of query pages.

10. A computer-readable medium comprising a plurality of software instructions that, when executed by at least one network-connected computer-based system, perform a method of determining a user's risk of dyslexia, the instructions comprising: instructions for identifying, based on an input received from an input device of the computer-based system, an age category associated with the user; instructions for generating a plurality of query pages, each query page being generated from data received by the computer-based system from a remote server over a data communications channel and stored in a memory device of the computer-based system, and each query page comprising a plurality of non-verbal answers that are determined based on the identified age category and are selectable by the user; instructions for generating a plurality of auditory queries to be rendered via a speaker of the computer-based system, each auditory query being producible as audible sounds and generated from a sound data file corresponding to a non-verbal query, each auditory query being associated with one or more of the plurality of query pages; instructions for identifying, via the input device of the computer-based system, a plurality of electronic input selections from the user, each electronic input selection identifying a non-verbal answer from a query page; instructions for identifying, via a timer of the computer-based system, timing data associated with the plurality of electronic input selections, the timing data indicating time intervals between the rendering of each of the plurality of auditory queries and the detection of electronic input selections from the user corresponding to each of the auditory queries; instructions for assigning weighted scores to each of the electronic input selections from the user, the weighted scores being determined based on the identified age category and the time intervals, wherein time intervals above a first threshold receive a first weighting factor and time intervals below the first threshold receive a second weighting factor; and instructions for rendering, on the display screen of the computer-based system, an assessment in a graphical user interface, the assessment identifying a risk of dyslexia for the user based on whether the weighted scores exceed a predefined threshold associated with the plurality of query pages.

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8. A system, comprising: a first computing device comprising at least one hardware processor; and program instructions stored in memory and executable in the first computing device that, when executed by the at least one hardware processor, cause the first computing device to: generate audio data and video data collected by a microphone and a camera coupled to the first computing device for transmission to a second computing device, wherein the audio data embodies human speech associated with a first language; communicate the audio data and video data to at least one computing device over a network that provides at least a portion of the audio data and the video data to the second computing device through a data stream, wherein the at least one computing device is configured to: perform a language translation using the audio data where the speech associated with the first language is translated to a translation output associated with a second language; determine a time delay needed for the at least one computing device to complete the language translation where the speech made in the first language is translated to the translation output; and impose the time delay in a video signal for transmission to the first computing device; toggle an indicator in a display of the first computing device that indicates that the at least one computing device is performing the language translation in response to a signal being received from the at least one computing device; determine that a predefined amount of the speech associated with the first language has been translated to the translation output associated with the second language sufficient to prevent a discontinuity in speech segments; and in response to the predefined amount of the speech having been translated to the translation output, render the translation output and the video data on the first computing device contemporaneously as the translation output and the video data are rendered on the second computing device using the video signal.

9. The system of claim 8 , wherein the video data is rendered in a display associated with the first computing device and the second computing device after an elapse of the time delay and completion of the language translation.

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9. The method as claimed in claim 4 wherein said step of applying a grouping function g comprises: i. creating groupings of contexts from said initial set of contexts; ii. calculating a conditional entropy for each grouping of contexts; iii. selecting a grouping with a lowest conditional entropy; iv. reducing a size of said set of contexts by replacing elements which comprise the selected grouping with said grouping; and v. repeating steps (i)-(iv) until a size of said set of contexts equals the predetermined number of contexts.

10. The method as claimed in claim 9 wherein step (c) comprises determining joint, conditional, and unconditional probabilities from a large set of data files having the same file categorization criteria as the determined file categorization.

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11. The system of claim 3 , the endorsement conveyance module further comprising an endorsement validation unit to determine the validity of the endorsement and to provide validity results to an action module configured for decision making.

12. The system of claim 11 , further comprising an automated decision making process.

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15. The bilingual authoring method as set forth in claim 12 , wherein the bilingual dictionary stores source language collocations of the text portion in the source language, and the deriving of at least one proposed translation in the target language further includes: determining translations in the target language of the source language collocations using the bilingual dictionary; comparing the determined translations with the surrounding or adjacent text in the target language to identify at least one proposed translation as a determined translation in the target language of a source language collocation corresponding with the surrounding or adjacent text in the target language.

16. The bilingual authoring method as set forth in claim 15 , wherein the determining of translations further includes: identifying target language synonyms of the determined translations in the target language.

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1. A method, comprising: receiving a database query comprising a logical database table identifier, a data element, and at least one data source assurance indicator at a distributed database device within a distributed network of databases, where the at least one data source assurance indicator comprises a request to encrypt the data element received in the received query for authentication of distributed database devices that process the database query; encrypting the data element received in the received query based upon the at least one data source assurance indicator; forming a data portion of a local query response to the database query comprising data retrieved from a local physical database table mapped by a local logical database table that matches the received logical database table identifier; adding a distributed database device node identifier and the encrypted data element as an authentication portion of the local query response to authenticate the data portion of the local query response; and responding to the database query with at least the authenticated local query response.

3. The method of claim 1 , where the at least one data source assurance indicator comprises an instruction to encrypt a selected data column of the data portion of the authenticated local query response.

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10. An electronic apparatus, comprising: an input unit, receiving a speech signal; a storage unit, storing a plurality of program code segments; and a processing unit, coupled to the input unit and the storage unit, the processing unit executing a plurality of commands through the program code segments, and the commands comprising: obtaining a phonetic transcription sequence of the speech signal according to an acoustic model; obtaining a plurality of syllable sequences and a plurality of corresponding phonetic spelling matching probabilities according to the phonetic transcription sequence and a syllable acoustic lexicon; obtaining an intonation information corresponding to each of the syllable sequences according to a tone of the phonetic transcription sequence; obtaining a plurality of phonetic spelling sequences and a plurality of phonetic spelling sequence probabilities, from the language model, according to each phonetic spelling of phonetic spelling sequences and the intonation information; obtaining, from the language model, a plurality of text sequences corresponding to the phonetic transcription sequence, and a plurality of spelling sequence probabilities; generating a plurality of associated probabilities by multiplying each of the phonetic spelling matching probabilities and each of the spelling sequence probabilities; and selecting the text sequence corresponding to a largest one among the associated probabilities to be used as a recognition result of the speech signal, wherein different intonation information in the language model is divided into different semantemes, and the semantemes are corresponding to different phonetic spelling sequences.

12. The electronic apparatus of claim 10 , wherein the commands comprise: receiving the phonetic transcription sequences matching pronunciations in the speech signals; and obtaining data of a plurality of phones corresponding to the phonetic transcription sequences in the acoustic model by training according to the speech signals and the phonetic transcription sequences.

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17. The non-transitory computer-readable storage medium of claim 16 , wherein at least one of the one or more destination context labels describes a category, and wherein selecting the recommendation further comprises: adjusting the weight corresponding to the at least one of the one or more destination context labels based on user preference data indicating that the user has a preference for the category.

16. The non-transitory computer-readable storage medium of claim 14 , wherein selecting the recommendation comprises: calculating a weight for each of the one or more destination context labels, the weight of each destination context label determined from probabilities of transition rules corresponding to transitions from the current context label to the destination context label; and selecting the recommendation from the corpus of recommendations responsive to a weight of the selected destination context label.

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14. The computer readable medium of claim 13 , wherein the instructions, when executed, transform and connect the combinations of the motion primitives based on the position of the aircraft associated with constructs of the trajectory.

13. The computer readable medium of claim 12 , wherein determining that the trajectory satisfies the trajectory specification threshold includes evaluating the trajectory by transforming and connecting combinations of the motion primitives.

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10. A system for state-free generation of context-sensitive conversational responses, said system comprising: a processor configured to: receive a message generated by a user, as part of a current conversation with the user; derive, by a context derivation component implemented on the processor, context data from a set of context data sources associated with the user, wherein the context data is derived based on its correspondence with the user generated message and the current conversation; and generate a response to the user generated message, based on the user generated message and the context data, by a response generation engine implemented on the processor, wherein the response generation engine is trained on a plurality of context-message-response n-tuples extracted from at least one source of conversational data such that the response in the at least one context-message-response tuple corresponds to the generated response to the user generated message.

16. The system of claim 10 , wherein the context data includes non-linguistic context data, and wherein accessing the context data further comprises: accessing the non-linguistic context data from a set of user data, the non-linguistic context data comprising at least one of preferences data, contacts data, health data, interest data, user activity data, calendar data, activities data, work data, hobby data, or daily routine data.

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13. The method of claim 10 , further comprising: determining a portion of the users for which to compute the knowledge scores and the power scores based on an input received through at least one filter control.

14. The method of claim 13 , further comprising identifying sentiments of the users regarding the topic, wherein the input received through the at least one filter control relates to the sentiments.

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5. The method of claim 1 , further comprising: performing a discourse analysis of the audio speech file, wherein the discourse analysis comprises searching for a set of terms in the audio speech file that indicates a behavior having a relevance to an expertise determination associated with the topic; and ranking the speaker as the expert in the topic based on the discourse analysis.

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

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4. The computer-implemented method of claim 2 , wherein identifying the localized image features comprises identifying a corner feature, a scale-invariant feature, a shape context feature, or a spin image feature.

2. The computer-implemented method of claim 1 , wherein identifying image features in the images comprises identifying localized image features at particular locations in the images.

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9. The system according to claim 1 , wherein the context in which the NLQ was submitted is associated data relating to characteristics of a computing device the user is using.

1. A system for providing an automated response to a user natural language query (NLQ) made in regard to a subject, said system comprising: a computing platform including communication circuitry, processing circuitry and computer executable code adapted to cause the computing platform to: (a) receive digital data representing the user NLQ; (b) assign a weight value to words in the NLQ, wherein a weight value assigned to a given word of the NLQ is inversely related to a rate of occurrence of the given word in at least one knowledgebase; (c) calculate a query specific significance value for one or more of the words in the NLQ, wherein the query specific significance value for a given word is a ratio between the weight value of the given word and a sum of weight values of a set of other words in the NLQ, such that a query specific significance value of any selected word in any selected NLQ is inversely related to a sum of weight values of words, other than the selected word, in the selected NLQ; (d) search the at least one knowledgebase for one or more candidate matches, which candidate matches include words corresponding to words in the user NLQ; and (e) score matches between the NLQ and the one or more match candidates by performing a mathematical operation using the query significance value of words in the NLQ and the query significance value of corresponding words in the one or more match candidates; (f) compare a context in which the NLQ was submitted to contexts associated with one or more of the one or more match candidates, wherein a context of a NLQ is a parameter relating to the NLQ other than the text of the NLQ.

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10. The method of claim 9 , wherein the information representing the second route sequence map comprises data representing a navigation context element of the second route sequence map, such that the user can transition from an action context element of the first route sequence map to the navigation context element, as an entry point of the second route sequence map, to navigate the second route sequence map.

11. The method of claim 10 , wherein the first route sequence map was configured and stored in the service center by the user associated with the remote device, wherein the second route sequence map was configured and stored in the service center by an administrator of the predetermined client, and wherein the user associated with the remote device is a customer of the predetermined client.

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15. The method of claim 1 , wherein the metadata keyword comprises a single word.

1. A method comprising: receiving, via a communication module, a non-linear content identifier request for non-linear content, wherein the non-linear content identifier request comprises a linear content identifier associated with linear content selected by a viewer and location data associated with the viewer; identifying, via a matching module, linear content metadata associated with the linear content identifier of the non-linear content identifier request, the linear content metadata representing at least one metadata keyword; and identifying, via the matching module, a relationship between the at least one metadata keyword and at least one non-linear content keyword bid on by one or more advertisers associated with a time slot.

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16. The system of claim 13 , wherein the computer readable program code executable by the processor to obtain the one or more keywords in the contents of the web page related to the entered keyword and the one or more categories associated with the one or more related keywords is further executable by the processor to: receive an address for the web page and a partially entered keyword; determine one or more words matching the partially entered keyword; search a storage for the one or more keywords in the contents of the web page related to each of the words matching the partially entered keyword; identify the one or more categories associated with the one or more related keywords; and return each related keyword and each associated category.

13. A system comprising: a processor; and a computer readable storage medium having computer readable program code embodied therewith, the program code executable by the processor to: activate an enhanced find operation on a web page and obtain an entered keyword to find in the contents of the web page; obtain one or more keywords in the contents of the web page related to the entered keyword and one or more categories associated with the one or more related keywords; display the one or more categories associated with the one or more related keywords with the contents of the web page; detect a selection of at least one of the one or more categories; and enhance a display in the contents of the web page of the one or more related keywords associated with the selected category, wherein the program code executable by the processor to detect the selection of the at least one of the one or more categories and to enhance the display in the contents of the web page of the one or more related keywords associated with the selected category is further executable by the processor to: detect a selection of a first category of the one or more categories; enhance a display in the contents of the web page of a first set of keywords associated with the first category; detect a selection of a second category of the one or more categories; in response to detecting the selection of the second category, remove the enhanced display of the first set of keywords and enhance a display in the contents of the web page of a second set of keywords associated with the second category.

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18. The method as recited in claim 14 , wherein said expression whose type is context-dependent comprises a lambda expression, wherein said one or more invocable operation declarations comprise (a) a first method declaration with a first function type as a parameter and (b) a second method declaration with a second function type as a parameter, wherein said determining whether a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria comprises: performing a first analysis to determine whether the first method is more specific than the second method, wherein the first analysis comprises a comparison of the respective parameter types of the first and second method declarations; and performing, in response to determining that the first analysis fails to indicate a specificity ordering between the first and second method declarations, a second analysis to determine whether the first method declaration is more specific than the second method declaration, wherein the second analysis comprises a comparison of respective function descriptor return types of the first and second method declarations.

14. A method, comprising: determining, for an overloaded operation invocation identified in source code of a computer program, whether the source code includes, as an argument to the invocation, an expression whose type is context-dependent; and in response to determining that the source code includes, as an argument to the invocation, an expression whose type is context-dependent, providing the expression as an input to an overload resolver; determining, at the overload resolver (a) whether each argument of the invocation, including the expression, is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations identified from the source code, and (b) whether a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria; in response to determining that (a) each argument of the invocation is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations in the source code, and (b) a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generating executable instructions for the invocation in accordance with the particular invocable operation declaration; and in response to determining that none of the plurality of invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate an error indication; wherein the error is generated even though each argument of the invocation is compatible with a type of a corresponding parameter indicated in a plurality of invocable operation declarations in the source code.

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8. A method of providing a query to a dialog system, the method comprising: interacting with the dialog system in a manner known to cause a behavioral test response, the behavioral test response representative of a steganographic signature embedded in the dialog system.

14. The method of claim 8 , further comprising prompting a user with the behavioral test response, the behavioral test response being a prompt of a dialog system.

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10. A computer-implemented method of documenting a design of a transformer, the method comprising: generating a metadata text file describing a circuit layout of the transformer, the metadata text file being written in a metamarkup language and comprising component elements describing components of the transformer, respectively, the component elements being arranged in a hierarchical format that corresponds to different circuit levels of the circuit layout of the transformer; analyzing the metadata text file to determine design information comprising numbers and types of the components of the transformer and their interconnectivity; opening an electronic document; and creating a drawing of the circuit layout of the transformer in the opened electronic document using the determined design information, the drawing including graphic elements representing the components of the transformer, respectively.

11. The method of claim 10 , further comprising: allocating space in the drawing for the graphic elements based on the number and the types of the components.

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16. The computing device of claim 11 , wherein to determine the delegate for responding to the audio message, the control system is adapted to access a message attribute associated with the audio message, and based on the message attribute, automatically determine the delegate without input from the delegator.

11. A computing device, comprising: a communication interface adapted to interface with a network; and a control system comprising a processor, the control system adapted to: receive, from a message server, an audio message from a prioritized list of audio messages, wherein the audio message in the prioritized list of audio messages is prioritized based on an aggregate message priority value for the audio message, the aggregate message priority value comprising a product of a first weight and a first sender designated priority of the audio message, and a product of a second weight and a first recipient prioritization attribute of the audio message; determine a delegate for responding to the audio message; determine a delegation action identifier identifying a delegation action of a plurality of delegation actions directing the delegate; and communicate a delegate identifier identifying the delegate and the delegation action identifier to the message server for delegation of the audio message to the delegate in accordance with the delegation action.

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7. The method of claim 1 , wherein one of the organizational tabs is associated with variables used in the first and second mathematical expressions and further including organizing the hierarchical tree such that variables are displayed at the parent level.

1. A method of displaying in a calculator, comprising: receiving a first mathematical expression in an expression entry area on the calculator; displaying results in a first window on the calculator, wherein the results displayed in the first window comprise a result for the first mathematical expression; displaying, in a second window on the calculator, a usage history comprising the first mathematical expression, a second mathematical expression, and results displayed in the second window, wherein the results displayed in the second window comprise the result for the first mathematical expression and a result for the second mathematical expression, wherein the usage history is displayed in a hierarchical tree such that a result for a given mathematical expression is displayed in the second window on a different hierarchical level than the given mathematical expression; and displaying organizational tabs for the second window, wherein each organizational tab is operable to display a given category of data associated with the usage history, and wherein the results in the first window and the results in the second window are displayed simultaneously.

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8. The method of claim 1 , wherein, after outputting the ranked identified features, a user can revise the speech trend analysis request.

1. A method comprising: receiving, as part of a speech trend analysis request, a set of candidate feature constraints, an objective mathematical function with respect to a speech trend to be analyzed, and a set of speech record constraints to be applied to a group of speech records; selecting a speech record from the group of speech records based on the set of speech record constraints; identifying features in the speech record based on the set of candidate feature constraints, to yield identified features; assigning, via a processor, using a statistical regression, a weight to each of the identified features, wherein a scalar value associated with each identified feature is evaluated using the objective mathematical function to yield the weight; ranking the identified features by respective weights, to yield ranked identified features; comparing the ranked identified features to a hand-picked set of alarm features, to yield a comparison; and when the comparison indicates an alarm condition has been met, outputting one of the ranked identified features associated with a speech-based trend in response to the speech as an alarm.

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11. A system comprising: a processor; and a non-transitory computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: obtaining search query data, the search query data including a plurality of search queries submitted by users, each search query being associated with one or more responsive search results and user selection data for the one or more search results, wherein the user selection data identifies which search results were selected by users; obtaining a plurality of score improvement lists, each score improvement list being associated with a point value, each score improvement list being an ordered list of adjusters, wherein the adjusters are serially applied in order of the adjusters in the ordered list to initial scores of a group of search results to determine a final scoring of the search results; iteratively selecting pairs of score improvement lists from a pool of score improvement lists, the pool of score improvement lists including the plurality of score improvement lists; automatically for each selected pair: separately applying the ordered list of adjusters for each score improvement list included in the selected pair to one or more search results associated with a search query from the search query data, in response to the applying, identifying, for each score improvement list in the selected pair, respective ordered search results responsive to the search query, determining a winning and losing score improvement list in the selected pair from the respective ordered search results and the user selection data associated with the search query, increasing the point value associated with the winning score improvement list, and decreasing the point value associated with the losing score improvement list; repeating testing for respective pairs of score improvement lists until ending criteria are reached; and selecting one or more score improvement lists based on the respective point values after the repeated testing.

20. The system of claim 11 , wherein the user selection data includes, for each search result, a length of user time spent at a particular resource associated with the search result.

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1. A method of displaying a computer desktop and closed captioning content on a display device having a display area, the method comprising: displaying the computer desktop on the display device while the display area is unpartitioned; receiving a first instruction to display the closed captioning content on the display device; in response to receiving the first instruction, partitioning the display area into a first portion for the closed captioning content and a second portion for the computer desktop, the second portion being reduced in size with respect to the unpartitioned display area to make room in the display area for the first portion for the closed captioning content; capturing closed captioning content from a user application executing on a computer system associated with the display device and/or an operating system of the computer system, wherein the closed captioning content comprises text and is selected from the group consisting of title information for a currently active window displayed on the computer desktop, information about controls in a window displayed on the computer desktop, text typed in a document, help information for a computer desktop or user application element, alert information provided by the user application and/or the operating system, and information redirected for output by a speech synthesizer; writing at least some of the closed captioning content to a first buffer mapped to the first portion of the display area; writing at least a portion of the computer desktop to a second buffer mapped to the second portion of the display area and not to the first portion of the display area; displaying the at least some of the closed captioning content from the first buffer on the first portion of the display area, wherein the at least some of the closed captioning content displayed on the first portion of the display area is selected to facilitate a user interaction with the user application and/or the computer desktop; analyzing a context of the at least some of the text in the closed captioning content, wherein the context indicates an application type associated with the at least some of the text; replacing the at least some of the text with at least one user-defined symbol based, at least in part, on the context before displaying the closed captioning content on the first portion of the display area, wherein a same word or phrase in the closed captioning content is replaced with different user-defined symbols in association with different application types; displaying the at least a portion of the computer desktop from the second buffer on the second portion of the display area; and providing an ability to scroll the at least a portion of the computer desktop within the second portion of the display area, without causing movement of the at least some of the closed captioning content in the first portion of the display area, and without causing movement of the first portion of the display area.

5. The method of claim 1 , further comprising: receiving a second instruction to disable closed captioning; and displaying the at least a portion of the computer desktop on the unpartitioned display area.

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1. A spelling totem, comprising: an elongated, generally rectangular box-shaped member having a top end, a bottom end, a first side surface, a second side surface, a third side surface and a fourth side surface; a first letter language family that is disposed along the first side surface; a second letter language family that is disposed along the second side surface; a third letter language family that is disposed along the third side surface; and a fourth letter language family that is disposed along the fourth side surface, wherein the rectangular member includes a plurality of horizontal ridges that extend across each of the first, second, third and fourth side surfaces, said ridges functioning to create the appearance of a series of vertically aligned building blocks, and each of the first, second, third and fourth letter language families include a different single letter from an alphabet, and a plurality of letter implementations.

7. The totem of claim 1 , wherein the ridges are interposed between each of the plurality of letter implementations on each of the first, second, third and fourth letter language families.

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7. The system of claim 1 , wherein different information units associated with the website have different trust ratings.

1. A system for determining information trustworthiness, the system comprising: at least one terminal; and at least one ratings server, wherein, the at least one terminal and the at least one rating server are in communication via at least one network to: (a) receive a trust rating request for a website URL from a user, (b) generate the trust rating for the a website URL or another website URL based on collaborative filtering with user profile data and trust ratings provided by the user, wherein the user's provided trust rating for one or more website URLs is used to modify the trust rating for the requested website URL and at least one stored logical relationship between the requested website URL and at least one other website URL, wherein the logical relationship comprises at least one of the following: logically consistent, logically inconsistent and logically identical, and wherein if the logical relationship is logically inconsistent and the user trusts the at least one other website URL, then the generated trust rating will be lower than if the user did not trust the at least one other website URL; and (c) display the generated trust rating to the user.

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9. The system of claim 8 , wherein: the input interface receives at least one additional music query; the query input processor generates a deconstructed additional music query; and the query engine directs the deconstructed additional music query against a selected database containing deconstructed music pieces, identifies deconstructed music pieces that match the deconstructed additional music query, and produces search output comprising the identified music pieces arranged in a ranked list.

8. A computer system that performs music search, the system comprising: an input interface adapted to receive a music query; a query input processor adapted to generate a deconstructed music query comprising music elements of the received music query; and a query engine adapted to direct the deconstructed music query against a selected database comprising a plurality of data records, each data record being associated with a music piece and a set of music micro-elements relating to the music piece, wherein the set of music micro-elements associated with at least one data record comprises data deconstructed from the at least one musical music piece, to identify deconstructed music pieces of the database that match the deconstructed music query by generating at least one music macro-element from the set of music micro-elements associated with at least one data record, and to produce search output comprising the identified music pieces arranged in a ranked list.

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24. The computer-readable medium of claim 23 wherein said at least one identifier comprises a computer-generated separation page which is inserted between document images to delineate images belonging to different ones of said plurality of categories.

23. A non-transitory computer-readable medium for storing computer executable instructions that when executed by a computer perform a method of delineating document boundaries and identifying document types, said method comprising: automatically categorizing a plurality of document images into a plurality of predetermined categories in accordance witch classification rules for said categories; and automatically generating at least one identifier for identifying which of said plurality of document images belongs to which of said at least two categories.

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4. The method of claim 1 , further comprising determining whether initialization of the runtime plan tree is complete.

5. The method of claim 4 , further comprising performing runtime execution upon determining that the initialization of the runtime plan tree is complete.

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1. A method for generating scripts in a computer system, comprising: providing a user interface for enabling a user to perform user actions using said user interface to perform a user task; monitoring said user actions by said computer system; determining system operating environment information in accordance with said user actions; generating a script in accordance with said user actions and said determined system operating environment information for repeating said user task using said script generated in accordance with said determined system operating environment information, wherein said generating a script includes: creating a query using a combination of data representing said user actions and said determined system operating environment information and determining a plurality of previously generated scripts associated with the monitored user actions based on said query, wherein previously generated scripts are stored in a data repository; analyzing said monitored user actions; selecting a most efficient script from the plurality of previously generated scripts; and updating the selected, most efficient script responsive to the monitored user actions.

10. The method of claim 1 , further comprising generating said script in accordance with context information.

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54. The non-transitory computer readable medium of claim 40 , further including instructions to cause the processor to: permit the first user to search the electronic messages of the first user based on a file name extension type associated with attachments to the electronic messages and information tagged within the electronic messages.

40. A non-transitory computer readable medium encoded with a computer program including instructions to cause a processor to: analyze electronic messages of a first user with respect to one or more features associated with the electronic messages; associate descriptive tags with the electronic messages of the first user based on analysis results; and perform tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages; wherein the computer program further includes instructions to cause the processor to learn electronic message tagging rules based one or more of a statistical machine learning technique and a parser, and associate the descriptive tags with the electronic messages of the first user based on features associated with the electronic messages and the learned electronic message tagging rules.

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23. The apparatus according to claim 16 , wherein the hierarchically organized data document comprises data elements having an inferred logical relationship revealed by said preparsing.

16. An apparatus adapted to parse a hierarchically organized data document, comprising: a preparser configured to determine a logical tree structure of the data document, for use by a plurality of parsing processors, each of the plurality of parsing processors being configured to receive at least one of a plurality of divided sections of the data document, in dependence on the logical tree structure, wherein each section comprises at least a beginning of a logical section of the logical tree structure, with sufficient context to resolve any ambiguities wherein a set of tasks is generated by iteratively removing a remaining branch of the hierarchical skeleton which represents a largest task, and elevating the root of the subtree represented by the largest task to a next higher level, wherein a sufficient number of tasks is generated to permit efficient balancing; and a distribution control configured to distribute the plurality of sections to respective ones of the plurality of parsing processors for parsing of the sections of the data document.

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3. The system of claim 1 , wherein said at least one target language comprises a plurality of languages resulting in translation into a mixed language content.

1. A computer system comprising a plurality of networks each includes a plurality of computers for performing a method for determining a target language for automatic programmatic translation of text in a first language, comprising: creating text in the first language, the text being in a single discrete document; using an HTML ‘lang’ attribute to set at least one target language for a portion of the text which is different from the first language; and, automatically programmatically translating the portion having the first language into said at least one target language with said ‘lang’ attribute as a key for machine translation in order to produce a mixed translation of the text.

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11. The method of claim 10 and further comprising: receiving the training data as a schema and semantically annotated training text.

12. The method of claim 11 wherein generating a plurality of segmentations comprises: assigning a count to each segmentation based on occurrences of the segmentation supported by the training data.

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29. The device of claim 18 , wherein the syntax element comprises a split_cu_flag syntax element.

18. A device for coding video data, the device comprising: a memory configured to store the video data; and a video coder in communication with the memory, wherein the video coder is configured to: determine whether a coding unit (CU) depth of a current CU is smaller than a minimal CU depth of one or more neighboring CUs, or whether the CU depth of the current CU is greater than a maximum CU depth of the one or more neighboring CUs; select, as part of an entropy coding process, a context for a syntax element associated with the current CU stored in the memory based on information relating to CU depth of the one or more neighboring CUs relative to the current CU, wherein the information relating to the CU depth of the one or more neighboring CUs relative to the current CU includes whether the CU depth of the current CU is smaller than the minimal CU depth of the one or more neighboring CUs or whether the CU depth of the current CU is greater than the maximum CU depth of the one or more neighboring CUs, wherein the syntax element represents whether the current CU is split into sub-CUs; and entropy code the syntax element based on the selected context.

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16. An article comprising at least one machine-readable storage medium containing instructions that when executed cause at least one processor in a database system to: receive a database query containing a predicate expression that invokes a user-defined routine; receive a statement that sets the indicator to one of a first value and a second value; construct a first representation of the predicate expression in response to the indicator having the first value; and construct a second, different representation of the predicate expression in response to the indicator having the second value.

22. The article of claim 16 , wherein the instructions when executed cause the database system to further use at least one of indexing and statistics in generating a query plan for the database query in response to categorization of the predicate expression that is represented by the second representation.

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12. The method of claim 11 , wherein simplifying the intermediate representation comprises replacing a probabilistic distribution in the intermediate representation with simpler distributions having an approximate expected value.

11. The method of claim 8 , further comprising simplifying the intermediate representation using one or more statistical rules.

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2. The computer-implemented method of claim 1 , further comprising: receiving a second sensory input from the one or more sensors; determining that the second sensory input corresponds to a sub-consciousness module; selecting a second action corresponding to the second sensory input; and performing the second action in response to the second sensory input.

4. The computer-implemented method of claim 2 , wherein selecting the second action corresponding to the second sensory input comprises: selecting a list of potential responses according to a characteristic of an artificial personality associated with the machine; and selecting the second action from the list of potential responses.

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3. The method of claim 1 , further comprising analyzing terms in the textual data in view of a known sentiment of the textual data, wherein terms having a relatively high correlation with the known sentiment are selected as additional identifiers, and associating the additional identifiers with the target classifier.

4. The method of claim 3 , wherein the known sentiment is available for a limited amount of opinion data.

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16. The printing apparatus according to claim 13 , wherein said conditions comprise functions that evaluate to true or false.

13. A printing apparatus comprising: a processor; a printing engine operatively connected to said processor, wherein said printing engine prints markings on items; a computerized storage device operatively connected to said processor, wherein said storage device maintains one or more print product type descriptions, wherein each of said print product type descriptions comprise one or more product type classification rules, wherein each of said product type classification rules comprises one or more conditions to be satisfied and a product type classification action to be taken by said printing engine if said conditions are satisfied, wherein said each of said conditions comprises one or more sub-conditions; a mapping engine operatively connected to said processor, wherein said mapping engine automatically constructs a map between constructs and said sub-conditions in a Web Ontological Language (OWL), wherein said OWL comprises an ontology, wherein said ontology comprises one or more classes corresponding to said product type classification rules, wherein each of said classes comprises one or more class restrictions corresponding to said conditions, wherein each of said class restrictions comprises one or more of said constructs corresponding to said sub-conditions; a converter automatically converting said printing rules into new OWL classes in a process comprising: creating a new OWL class for each corresponding product type classification rule; adding said new OWL class to said OWL ontology; for each condition of said corresponding product type classification rule, extracting sub-conditions; for each said sub-condition extracted, creating new constructs for said new OWL class using said map; and adding new class restrictions to said new OWL class, wherein each of said new class restrictions relates to a corresponding condition of said corresponding product type classification rule; and an interface operatively connected to said processor, wherein said interface receives instructions to initiate operations of said mapping engine and said converter and to output said new OWL classes; wherein said adding of said new class restrictions comprises, for each given condition, creating a conjunction of all said new constructs associated with sub-conditions of said given condition, such that said conjunction of all said constructions forms a new class restriction corresponding to said given condition.

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8. The storage medium as claimed in claim 7 , the method further comprising: recording set delivery periods set for translations of original texts in association with actual delivery periods of the translations of the original texts; calculating an average of differences between the set delivery periods and the actual delivery periods; and if the average of differences is greater than a predetermined threshold, modifying the coefficients in the coefficient table.

7. A non-transitory computer-readable storage medium storing program code for causing an apparatus, which includes a translation memory storing previously translated sentences in association with source sentences, to perform a method, the method comprising: reading, from a storage unit of the apparatus, an original text including original sentences to be translated, a coefficient table defining coefficients associated with matching rates, and a delivery period table defining values indicating numbers of days and associated with total numbers of words; comparing the original sentences with the source sentences in the translation memory and thereby calculating the matching rates of the original sentences to the source sentences; counting a number of words in each of the original sentences after the matching rates are calculated and thereby obtaining numbers of words for the respective matching rates; adjusting the numbers of words of the respective matching rates by multiplying the numbers of words by the corresponding coefficients defined in the coefficient table; adding the adjusted numbers of words of the respective matching rates to obtain a total number of words of the original text; and obtaining one of the values corresponding to the obtained total number of words from the delivery period table and setting the one of the values as a delivery period for a translation of the original text.

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2. A method as recited in claim 1 , further comprising extracting the first textual entity and the second textual entity from the query input.

1. A method comprising: receiving a query input via a computing device, the query including at least a first textual entity and a second textual entity; generating a candidate set of images based at least in part on the query input, the candidate set of images including at least a first set of images associated with the first textual entity and a second set of images associated with the second textual entity; receiving a first selection of a first image from the first set of images; receiving a first indication of placement of the first image on a canvas via a user interface of the computing device; receiving a second selection of a second image from the second set of images; receiving a second indication of placement of the second image on the canvas via the user interface; creating, based at least in part on the canvas, a query image for performing a visual search, the query image including a first image patch and a second image patch, the first image patch corresponding to the first image and the second image patch corresponding to the second image, wherein the relative positions of the first image patch and the second image patch within the query image are based at least in part on relative positions of the first image and the second image on the canvas; and performing the visual search using the query image.

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3. A command inputting method used when inputting characters using software for Kana (Japanese character)-to-Chinese character conversion comprising the steps of: receiving a string comprising a plurality of characters through a keyboard; retrieving first Chinese character information or second Chinese character information corresponding to the character string by looking up the string in a Chinese character dictionary in which the first Chinese character information, comprising at least one Chinese character correlated to a character string, and the second Chinese character information, comprising a command and at least one Chinese character correlated to a character string, are previously stored; displaying the retrieved first Chinese character information or second Chinese character information as candidates for conversion in a list; receiving input for selecting a desired Chinese character or a command from the first Chinese character information or second Chinese character information displayed in a list; determining which of a Chinese character or a command has been selected or not according to a result of selection in said selecting step; replacing, when it is determined in said determining step that a Chinese character has been selected, the string with at least one corresponding Chinese character and displaying the at least one Chinese character; and executing the corresponding command when it is determined in said determining step that a command has been selected.

6. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion according to claim 3 further comprising the steps of: generating second Chinese character information that specifies a series of processing steps for the first Chinese character information in said Chinese character dictionary; and changing a command for the second Chinese character information in said Chinese character dictionary to a macro command.

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1. A language processing system for translating an input statement of a selected source language into a lower-level machine-oriented language comprising: (a) input means for inputting an input statement written in the selected source language of a computer; (b) storage means for storing a first table for storing keywords of grammer of said selected source language and characteristics of the keywords and for storing characteristics of variables used in a program coded by said selected source language; a second table for storing information of control procedures for interpreting the input statement to translate the input statement into a lower-level machine-oriented language, said information being predetermined and based on syntax/grammer of the selected source language; (c) control means for controlling translation processing of an input statement written in the selected source language from said input means, said control means including searching means responsive to said input statement for searching said first table to obtain a location therein at which a desired keyword variable is stored and to obtain an attribute associated with said keyword variable; comparing means for comparing said attribute from said searching means with a corresponding attribute stored in said second table to check whether the syntax of the input statement meets the grammer of said selected souce language; and converting means responsive to a determination of a match between said attributes as a result of the comparison by said comparing means, for converting said input statement into a lower-level machine-oriented language based on a predtermined conversion rule.

3. The system according to claim 1 wherein said second table stores information of a precessing procedure for checking whether or not the attribute of an input statement word including one of a keyword, variable numerical value and delimiter matches with the selected source language syntax and information of a processing procedure to be executed when the attribute of the word matches with the selected source language syntax and a processing procedure to be executed when the attribute of the word does not match with the selected source language syntax, following the result of said matching check.

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7. A system comprising: program code comprising: an object management system to call a constructor to register an interface to a description of a persistent class; and a database management system kernel to access the registered interface to determine an internal structure of the persistent class, to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object, to determine, based on the determined internal structure, members of the persistent database object that are filled with default values, to store the persistent database object in a database, to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database, to read the persistent database object from the database after the storing of the persistent database object in the database, to populate the determined members of the persistent database object with the default values after the reading of the persistent database object from the database, to define an index associated with one or more members of the instance based on the determined internal structure and to verify referential integrity of the instance; and at least one processor to execute the program code.

9. The system according to claim 7 , the database management system kernel further to define a key associated with one or more members of the instance based on the determined internal structure.

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3. The method of claim 1 , wherein the querying further comprises: conducting a search of the resources serving as query objects.

1. A method, comprising: receiving a user selection specifying a medium to be automatically created, the medium having a plurality of content components, based on user-selected criteria, and is selected from a list including at least one of a webpage, blog, tweet, instant message, or social media application; employing a keyword search based at least in part on the user selection of the medium and criteria; responsive to receiving the user's selection of the medium to be automatically created and the associated criteria, querying at least one of local environment resources and remote environment resources to identify content relevant to the medium that the user wishes to generate, wherein the querying comprises at least one of identifying suitable resources in a networking environment and searching the identified resources; selecting, by a user from a dropdown list, the identified resources; receiving and processing a response, by a processor, to the query from the at least one of the local environment resources, the remote environment resources, and the identified resources; and generating the medium, including formatting and structuring a layout of the medium based on the processed response by supplying content to the medium components without the user's further involvement, wherein the query response is used to supply the content and the supplied content is based on the user's selected criteria.

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3. The computing device of claim 1 , wherein the instructions, when executed, further cause the computing device to: receive a selection of a text input field being displayed on the interface; receive a selection of a word from of the selectable list; and populate the text input field with the word, wherein the text input field includes at least one of a title field, a product description field, a product search phrases field, a keyword search field, a price field, a quantity field, or a quality field.

4. The computing device of claim 3 , wherein the instructions, when executed, further cause the computing device to: receive an indication that input to the text input field is complete; and generate a product listing using entries in the text input field.

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8. The computer-based user interface according to claim 7 wherein: the dialog control element is configured for modifying information associated with creating and/or destroying controls in the dialog according to the user interaction.

7. The computer-based user interface according to claim 6 wherein: the dialog control element is configured for enabling a user to interact with the dialog, the interactions comprising modifying the scalar controls and vector controls, and adding and/or removing deleting objects from a selected vector property respectively adds and deletes user interface controls and respectively creates and deletes portions of the recursive data structure.

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1. A computer system comprising: a processor; and memory coupled to the processor and having stored therein instructions that, if executed by the computer system, cause the computer system to perform operations comprising: providing, in a database, a plurality of entity table types relevant to a domain type, wherein each entity table type includes a respective entity table name field and at least one respective data item field; populating the respective entity table name fields and the respective data item fields by automatically: extracting a plurality of data items from a plurality of data sources; determining respective confidence values for the extracted data items based on a plurality of pre-determined confidence values, wherein the pre-determined confidence values, wherein a respective predetermined confidence value is provided for each respective entity table name and each respective data item according to which data source of the plurality of data sources provided the respective entity table name and the respective data item; and integrating the extracted data items into respective entity table name fields and data item fields based on the respective confidence values for the extracted data items; determining relationship types between at least some data items of the plurality of data items that are integrated into a plurality of tables in the database, wherein the relationship types are based on respective data sources from which the data items have been extracted, the relationship types including at least two of the following: a first relationship type, a second relationship type, a third relationship type, and a fourth relationship type, wherein: the first relationship type is between first and second data items extracted from a first structured data source, the second relationship type is between data items extracted from different structured data sources, wherein the second relationship type is based on a plurality of respective first relationship types, the third relationship type is between a data item extracted from a second structured data source, and an entity table including, as entity table data items, attributes about a first unstructured data source, and wherein the data item extracted from the second structured data source is mentioned in the first unstructured data source, and the fourth relationship type is between two data items that: have been integrated from different structured data sources, and are both mentioned in a second unstructured data source; and storing the relationship types in a computer system memory.

10. The computer system of claim 1 , wherein the pre-determined confidence values indicate reliability of each of the data sources based on at least one of an internal review of the data sources and an external review of the data sources, wherein the internal review is performed by reviewers selected from the group consisting of: reviewers comprising users of a system implementing the operations, and reviewers comprising developers of a system implementing the operations; wherein the external review is performed using a third party reliability standard; and wherein the operations further comprise: comparing a first confidence value indicating reliability of a third data item stored in a data item field to a second confidence value indicating reliability of a data source having a fourth data item for the data item field; updating the database by integrating the fourth data item into the data item field if the second confidence value is greater than the first confidence value; associating time stamps with the extracted data items; and using the time stamps for the third and fourth data items to determine which of the third and fourth items is more recent if the first and second confidence values are the same, wherein the more recent of the third and fourth data items is integrated into the data item field in the database if the first and second confidence values are the same.

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16. A system comprising one or more machine-readable media that store thereon a first translator for translating a first computer language into a second computer language, and a second translator that converts the second language into active element instructions, which are instructions that are implemented by an active element machine and which indicate settings of parameters of components of the active element machine, which is a man-made machine that includes at least a multiplicity of man-made computing elements, and a multiplicity of man-made couplings communicatively connecting the multiplicity of man-made computing elements to one another, such that the man-made couplings are capable of transmitting messages between the multiplicity of man-made computing elements; one of the settings of the parameters including an indication of a time when the active element instruction will be implemented.

19. The system of claim 16 , wherein the second computer language is associated with a register machine.

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2. The method of claim 1 , further comprising extracting at least one textual feature from the document or the extracted graphic, extracting at least one visual feature from the extracted graphic, and classifying the extracted graphic based on the at least one extracted textual or visual feature.

3. The method of claim 2 , wherein extracting the at least one textual feature includes extracting at least one of: text residing within the document containing the extracted graphic; text residing within the extracted graphic itself; text residing in metadata associated with the extracted graphic; and text residing in metadata associated with the document.

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28. A method performed by one or more devices, the method comprising: determining, by one or more processors of the one or more devices, an amount that a rank of a document changes over time; determining or adjusting, by one or more processors of the one or more devices, a score for the document based on the amount that the rank of the document changes over time; and ranking, by one or more processors of the one or more devices, the document with regard to at least one other document based on the score.

29. The method of claim 28 , further comprising: employing measures to prevent the rank of the document from changing at more than a predetermined rate.

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4. The computer-implemented method of claim 3 , wherein the identifying the target law firm entity comprises: i. identifying records using the database system using at least a portion of the received first information, the identified records representing one or more possible spellings of a name of the law firm entity; ii. ranking the identified records based on a number of patent documents corresponding to each spelling of the name of the law firm entity; iii. providing the identified records to the user in a ranked order; iv. receiving second information from a user via a computer network, wherein the second information identifies the law firm entity and wherein the second information comprises selection of the identified records, the selected identified records representing different spellings of the name of the law firm entity, which correspond to the law firm entity.

3. The computer-implemented method of claim 2 , further comprising identifying the target law firm entity based on the first information.

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19. The system of claim 17 , wherein the processing electronics are further configured to automatically generate the model information upon receiving a signal indicating the end of a paragraph.

20. The system of claim 19 , wherein the processing electronics are further configured to automatically generate updated model information upon receiving a signal indicating the end of a second paragraph, and to render a synthesized image sequence based on the updated model information.

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23. The apparatus of claim 21 , wherein the buffer is configured to preload the text subtitle stream including style segment encapsulated into the PES packet which comprises at least one transport packet.

24. The apparatus of claim 23 , wherein the buffer is configured to preload the text subtitle stream including style segment encapsulated into the PES packet including transport packets which have a same packet identification (PID) value.

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3. The method of claim 1 , further comprising: receiving, by the IoT platform, the appliance data; determining, by the IoT platform, the identity of the appliance based on the appliance data; and transmitting, by the IoT platform to the communication module, the appliance-specific data based on the identity of the appliance.

5. The method of claim 3 , wherein the determining of the identity of the appliance further comprises: parsing the appliance data using a rule stored in a data store to locate a desired data relative to a known location in the appliance data; and translating the desired data according to a schema specified by the rule.

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61. The method according to claim 55 , wherein said amended portion of text-based data is amended by performing at least one of the group consisting of adding data to one of said plurality of portions of text-based data, deleting data from one of said plurality of portions of text-based data, and modifying data of one of said plurality of portions of text-based data.

55. A method for electronically managing text-based data, the method comprising: dividing said text-based data into a plurality of portions of text-based data; amending at least one of said plurality of portions of text-based data; storing at least one of said plurality of portions of text-based data; storing said amended portion of text-based data; providing a plurality of attributes, wherein at least one of said plurality of attributes defines at least in part a manner in which at least one of said plurality of portions of text-based data and said amended portion of text-based data can is organizable and linkable in a multidimensional space; associating at least one of said plurality of portions of text-based data and said amended portion of text-based data with at least one link comprising at least one of code or markup language enabled at least in part by at least one of said plurality of attributes; enabling a user to search at least one of said plurality of portions of text-based data and said amended portion of text-based data using at least one of said plurality of attributes; and allowing the results of said search be available to a user by: providing at least one of said plurality of portions of text-based data or said amended portion of text-based data in response to said search; and providing one or both of (I) text, or (ii) one or more selectable links representing at least one additional attribute.

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2. The method of claim 1 , further comprising responsive to applying all of the plurality of sub-pipelines, storing fully ingested new content in the corpus of information.

1. A method, in a data processing system, for partial ingestion of content, the method comprising: identifying a set of features that contribute to generating candidate answers for input questions; identifying a set of annotation engines in the ingestion pipeline that contribute to each of the set of features and at least one annotation engine on which the one or more annotation engines depend; generating a sub-pipeline for each set of annotation engines to form a plurality of sub-pipelines of annotation engines; receiving new content to be ingested into a corpus of information; applying the plurality of sub-pipelines of annotation engines against the new content in order of effectiveness, wherein the plurality of sub-pipelines include all annotation engines of an ingestion pipeline and wherein each sub-pipeline within the plurality of sub-pipelines generates one or more intermediate output objects; and providing access to the one or more intermediate output objects, wherein the one or more intermediate output objects represent the partially ingested new content.

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21. A method of encoding a data string into a symbol, the method of encoding comprising the steps of: receiving the data string comprising a plurality of character codes selected from a first set of character codes, wherein the first set of character codes map to a first set of data characters, and wherein a second set of data characters form a subset of the data characters in the first set of data characters; parsing the data string to remove all character codes corresponding to the data characters contained in the second set of data characters; converting each of the character codes in the parsed data string into a first defined number of symbol values, and converting the character codes parsed from the data string into a second defined number of symbol values, where the second defined number of symbol values is greater than the first defined number of symbol values; and outputting the converted symbol values corresponding to the parsed character codes and the converted symbol values corresponding to the parsed data string.

23. The method of claim 21, further comprising the steps of: receiving a string comprising a plurality of data characters, the data characters selected from the first set of data characters and the second set of data characters; determining a plurality of character codes corresponding to the plurality of data characters, the character codes selected from the first set of character codes; and outputting the plurality of character codes as the data string.

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8. The method of claim 1 , wherein the displaying includes adjusting an aspect of a background of a first element of the stylized information relative to an aspect of a background of a second element of the stylized information.

1. A method for preserving an original appearance of stylized information and breaking the stylized information at an element boundary, the method comprising: acquiring an image including stylized information, wherein the stylized information includes a plurality of elements, and the plurality of elements includes one or more words that are arranged in an arced line; distinguishing each of the elements of stylized information in the image from one another; identifying at least one element boundary for each of the elements of stylized information, wherein an element boundary indicates a division between successive elements of the stylized information; displaying a representation of each of the elements of stylized information in the image on a display by placing the elements of stylized information, one element after another element, by breaking the stylized information at an element boundary; and rotating a first word in the arced line relative to a second word in the arced line to display the first word and the second word in one or more non-arced lines, wherein: the displayed elements comprise bordering elements, the bordering elements are elements sharing a boundary, and the displaying comprises smoothing representations of boundaries between bordering elements.

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8. A computer program product, comprising a computer-readable hardware storage device having a computer-readable program code stored therein, said program code configured to be executed by a processor of a computer system to implement a method for automatically deriving a context of a business rule when inferring the business rule from an information source, the method comprising: a processor of a computer system inferring the business rule as a function of a first element of information comprised by a first information source; the processor identifying a next element of information that is associated with a first context of the first element of information, wherein the first context associates the first element with a first context-dependent characteristic of the first element, and wherein the next element of information is comprised by a next information source that is distinct from the first information source; the processor modifying the business rule as a function of the next element of information; the processor attempting to recognize a further element of information that is associated with a next context of the next element of information, wherein the next context associates the next element with a next context-dependent characteristic of the next element, and wherein the further element of information is comprised by a further information source that is distinct from the first information source; the processor, if successfully recognizing the further element of information, updating the business rule as a function of the further element of information; and the processor iteratively repeating the attempting to recognize and the updating until the processor fails to recognize the further element, where the processor in each iteration initially resets values of the next element and the next information source respectively to those of the further element and the further information source that had been recognized by the processor in the previous iteration, and where the processor in each iteration attempts to recognize new values of the next context, the next context-dependent characteristic, the further element, and the further information source as functions of the reset values of the next element and the next information source.

13. The computer program product of claim 8 , wherein the first context and the next context are functions of a one or more contextual parameters, and wherein a contextual parameter of the one or more contextual parameters is selected from the group comprising: an element of information comprised by the first information source; an element of information comprised by the next information source; an element of information comprised by the further information source; a characteristic of an element of data associated by the business rule; a performance schedule associated with the business rule; a business function associated with the business rule; and a characteristic of a software application upon which a performance of a function associated with the business rule depends.

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9. The computer program product of claim 6 , wherein the temporary dictionary includes at least one of: one or both words and phrases that were entered into a field of the first application; one or both words and phrases that were included in the contents of information that appeared in the first application; and one or both words and phrases that are included as part of a description of the first application.

6. A computer program product for generating an auto-correct dictionary, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to analyze contents of information accessed by a user via a first application, wherein: the contents of information include at least one of words and phrases that appear in the first application; program instructions to identify at least one of the words and the phrases that appear in the first application and are not included in a first dictionary; program instructions to generate a temporary dictionary based, at least in part, on at least one of the words and the phrases identified in the first application that are not included in the first dictionary; and program instructions to use the temporary dictionary to carry out auto-correct operations on text included in a second application.

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28. The computer implemented method of claim 27 wherein the set of controls include a command control for generating code related to a grammar for one of navigation in the markup, help with a task, and repeating an audible prompt.

27. The computer implemented method of claim 26 wherein creating the dialog includes activation of the answer control through the question control.

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10. A method comprising: determining, by utilizing instructions from memory that are executed by a processor, an average of occurrence counts for a plurality of terms associated with a program in a program guide; calculating, for the program, a relevance ranking score, wherein the relevance ranking score is computed by multiplying the average of occurrence counts for the plurality of terms by a number of times the program is listed in the program guide; adjusting the relevance ranking score for the program based on a user profile; and generatin, for display on a display device, a sorted list of programs including the program, wherein the sorted list is sorted based on the relevance ranking score for the program.

14. The method of claim 10 , further comprising providing the sorted list of programs in response to receiving search criteria.

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29. A system for resolving contradicting output data from an Optical Character Recognition (OCR) system, wherein the output data comprises at least one word with at least one uncertainly recognized character, wherein the at least one uncertainly recognized character is reported in the output data together with probable alternatives for the at least one uncertainly recognized character, and the words wherein this at least one uncertainly recognized character has been encountered in an image of a text being processed by the OCR system, the system comprises: a system component using an Internet search engine with search arguments established according to a search strategy comprising: a) the system component provides initial search arguments by forming spelling alternatives for the words comprising the at least one uncertainly recognized character by substituting the at least one uncertainly recognized character with the reported probable alternatives for the at least one character, one by one, and in possible combinations in each encountered word, or by removing a character, thereby forming a plurality of spelling alternatives, and then measuring and recording number of hits for search results of each respective spelling alternative that has been formed in this manner, b) the system component compares the measured number of hits for each of the spelling alternatives with an upper predefined relative threshold level and a lower predefined relative threshold level, wherein each of the respective comparisons of the plurality of measurements falls into one of three possible outcomes: i) if the measurement of a spelling alternative is above the predefined relative upper threshold level, the corresponding spelling alternative for this measurement is the correct spelling alternative for the word, and terminate the Internet search, ii) if the measurement of a spelling alternative is below the lower predefined relative threshold level, the corresponding spelling alternative for this measurement is deemed non-existing, and the word with this spelling alternative is discarded from further investigations, and continue with other spelling alternatives that has been formed as search arguments for the Internet search engine, iii) if the measurement of a spelling alternative falls between the upper relative threshold level and the lower relative threshold level, exit the Internet search engine and modify the search strategy providing further search arguments as a combination of members of the remaining spelling alternatives and other words encountered in the document, other character alternatives for the at least one uncertainly recognized character, phrases, adapting the upper relative threshold level, adapting the lower relative threshold level, and/or other information related to the output data from the OCR system, before continuing using the search strategy providing further measurements and comparisons for resolving the contradicting output data, c) the system component is processing step b) a number of predefined times, or until there is only one spelling alternative left, whatever occurs first, providing an iteration amongst a plurality of different search arguments used in the search strategy before terminating step b), and using the remaining spelling alternative having the highest measurement above the upper relative threshold level as the correct spelling alternative.

37. The system according to claim 29 , wherein the system component comprises a unit using at least one preceding word further away relative to the word under investigation which comprise a number of characters above a predefined threshold in combination with the word under investigation as the spelling alternative.

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14. A computer readable storage medium containing an executable program for building an automated assistant, where the program is configured to cause a processor to perform a method comprising: interfacing a service-oriented architecture comprising a plurality of services to an execution environment comprising an active ontology, wherein the active ontology models a domain and comprises a logical arrangement of a plurality of active processing elements, wherein each active processing element is configured to receive at least one fact relating to the modeled domain and to perform at least one action responsive to at least one received fact; and registering at least one of the plurality of services for use in the domain, by specifying at least one of: one or more active processing elements that the at least one of the plurality of services can accept; and one or more active processing elements that the at least one of the plurality of services cannot accept; wherein the active ontology filters requests for services to the at least one of the plurality of services in accordance with the one or more active processing elements specified by the at least one of the plurality of services.

19. The computer readable storage medium of claim 14 , wherein the service-oriented architecture is interfaced to the active ontology via a service broker.

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14. The system of claim 11 where the deriving includes: modifying the quality of result statistic based on a level of certainty for each of the generated one or more queries.

11. A system comprising: a computer-readable storage device including instructions; and one or more data processing apparatuses configured to execute the instructions and perform operations, comprising: receiving a user-submitted query; generating an initial ranking of one or more documents responsive to the user-submitted query, the one or more documents including a first document responsive to the user-submitted query; determining that the user-submitted query does not match any record in a model of queries and documents, the model comprising a plurality of records, each record specifying an association between a respective query, a respective document, and respective click data aggregated for all users that select the respective model document in response to the respective model query; in response to determining that the user-submitted query does not match any query in the model, forming one or more variants of the user-submitted query to generate one or more other queries that each match a respective record in the model, each of the one or more other queries being different from the user-submitted query; deriving a generalized quality of result statistic for the first document responsive to the user-submitted query from respective data associated in the model with one or more of the other queries, wherein: the respective data for a given other query of the one or more of the other queries is associated with the matching respective record in the model and specifies aggregate user behavior for the first document when the first document was referenced in search results for the given other query, and the user behavior in selection of a reference to the first document in the search results for the given other query; and providing the generalized quality of result statistic as input to a subsequent document ranking process for the user-submitted query that generates, using the generalized quality of result statistic for the first document responsive to the user-submitted query, a subsequent ranking of the one or more documents responsive to the user-submitted query.

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3. The method of claim 1 , further comprising pushing the index update event into a message queue provided by a message provider.

5. The method of claim 3 , further comprising, in response to a notification from the message provider, retrieving the index update event from the message queue by the master search node and updating the master search index.

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1. A method for using at least one computer having a memory containing a font and a processor adapted to execute computer-executable instructions, to generate a print compound conserving font having at least one glyph comprising positive space defining an outline of the glyph against a background of negative space, the method comprising, for at least one glyph in the font in the memory of the computer: (a) retrieving the glyph from the memory; (b) adding at least one shape comprising negative space to the glyph, within the outline of the glyph; (c) adding at least one shape comprising positive space within at least one shape comprising negative space, the at least one shape comprising positive space having a smaller size than the corresponding shape comprising negative space; and (d) storing the glyph in the computer memory.

4. The method of claim 1 , wherein in step (c), the at least one shape comprising positive space is geometrically dissimilar from the corresponding shape comprising negative space.

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4. The information providing device according to claim 1 , further comprising: an interface for connecting to crowdsourcing human translation; and a quotation processing unit configured to execute processing of quoting cost of translating the posted document in a list of translation languages by the crowdsourcing human translation.

5. The information providing device according to claim 4 , further comprising: a machine translation unit configured to translate the electronic document into another language by machine translation and to generate an electronic file of the resultant translation, wherein one of the crowdsourcing human translation and the machine translation is selectable, and wherein the code image issuing unit includes, in the code image, an image indicating whether the translation has been performed by the crowdsourcing human translation or by the machine translation.

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6. The method of claim 5 , wherein the step of determining the phone number comprises the step of the computer parsing words in the voice mail message after the detected trigger word.

5. The method of claim 1 , wherein the step of parsing the plurality of words of the voice mail message comprises the step of detecting by the computer system a trigger word in the voice mail message.

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14. A computing system, comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the computing system to: upon receiving a request from a user to view a markup document, determining a difference between a version of the markup document previously presented to the user; and a current version of the markup document; accessing user activity tracking information to determine portions of the markup document that were previously displayed to the user; based on the determined difference between versions and the user activity tracking information, determine one or more portions of the current version that have not been displayed to the user; based on the difference information and the user activity tracking information, determining portions of the current version of the markup document that have not previously been displayed to the user; providing the markup document for display to the user at a client system, content of the markup document being modified to include one or more intra-page bookmarks, such that the portion that was not previously displayed to the user is distinguished from the portion that was previously displayed in a manner enabling the user to locate and view the portion that was not previously displayed to the user; enabling the user to manually insert the one or more intra-page bookmarks in the markup document allowing the user to start at a desired location after closing the markup document; and enabling the user to selectively choose to display the one or more intra-page bookmarks.

16. The computing system of claim 14 , further comprising: enable the user to use the one or more intra-page bookmarks to view the one or more portions of the current version of the markup document that were not previously displayed to the user.

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7. The method of claim 4 , wherein the category link dump comprises human-specified concept relations and the articles dump comprises article content and redirect links.

4. The method of claim 1 , wherein the data set comprises a category link dump and an articles dump from an Internet encyclopedia.

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13. The collection of claim 11 , wherein: said XPath discovery algorithm generates an XPath based on the DOM tree received from the user interface and communicates that XPath to the results editor.

15. The collection of claim 13 , wherein: the results editor receives XPath expressions from the XPath discovery algorithm and accepts input from the user interface to identify the nature of the selected text.

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2. The terminal according to claim 1 , wherein the estimating unit comprises a style estimating unit which estimates the speech style in accordance with the feature quantity.

3. The terminal according to claim 2 , wherein the converting unit converts the speech signal into the converted speech signal in accordance with the feature quantity detected by the first detecting unit.

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14. One or more computer-readable storage media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors to perform operations comprising: receiving an input query transmitted over a network; determining an input query pattern associated with the input query; accessing a library comprising one or more query patterns associated with one or more predefined search task categories by one or more transition probabilities, each of the one or more predefined search task categories associated with a task to be accomplished; classifying the input query pattern into one or more search tasks according to the one or more predefined search task categories, the classifying based at least in part on a lookup of the input query pattern in the library and identifying one or more tasks to be accomplished associated with the one or more predefined search task categories associated with a query pattern of the one or more query patterns similar to the input query pattern; and determining a search result based at least in part on the classified one or more search tasks, the search result based at least in part on the identified one or more tasks to be accomplished.

18. The one or more computer-readable storage media of claim 14 , wherein the input query is a search query transmitted over a network.

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1. A speech interactive system implemented in a computer system having at least a processing device, a storage device, a text input device, a speech input device and an output device, comprising: a target information receiving module implemented by said processing device and including said text input device for receiving target information and setting corresponding target text sentence information; an interactive mode setting and speech processing module implemented by said processing device and including said speech input device for receiving a speech signal, setting an interactive mode, determining target text sentence information for said speech signal, and outputting an assessment for a target text sentence; an interactive information update module implemented by said processing device for updating information in an interactive information recording table stored in said storage device according to said assessment for said target text sentence and a timing count; a decision module implemented by said processing device for deciding an output response for said target text sentence information according to said interactive mode and said information in said interactive information recording table; and an output response module implemented by said processing device and including said output device for outputting response information according to said output response and said information of said interactive information recording table.

5. The system as claimed in claim 1 , wherein when said speech signal is inputted to said interactive mode setting and speech processing module and said target information is provided to said interactive mode setting and speech processing module, said interactive mode is set as a teaching mode.

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50. The system according to claim 30 , wherein the dynamically typed language environment is MATLAB®, the time-based graphical modeling environment is SIMULINK®, or the state-based diagram environment is STATEFLOW®.

30. The design tool according to claim 29 , wherein the textual computing environment includes at least one of a C environment, a Python environment, a Javascript environment, a hardware description language environment, an Octave environment, or a dynamically typed language environment, and the graphical computing environment includes at least one of a time-based graphical modeling environment, a block-based environment, a chart-based environment, a state-based diagram environment, a data flow diagram environment, an entity flow network diagram environment, an electronic design automation environment, a Schematic Layout environment, or a Unified Modeling Language environment.

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10. The method of claim 3 wherein said single markup language element comprises an attribute identifying a variable for storing a result of said mathematical operation.

3. A method comprising, at a wireless communication device having a processor in communication with machine-readable memory storing machine-executable virtual machine software, executing said software to cause said device to: receive a single markup language element defining a mathematical operation to be performed upon specified numerical operands; and create, based on said single markup language element, an instance of an object-oriented class representative of the mathematical operation, said object-oriented class containing instructions for performing said mathematical operation, wherein said single markup language element comprises, for each of said operands of said mathematical operation, a separate attribute identifying said operand, wherein said numerical operands are floating point operands and wherein said single markup language element comprises an attribute indicating a desired number of decimal places to be displayed to the right of a decimal point of a floating point result of said mathematical operation, and wherein said performing said mathematical operation comprises rounding a least significant digit of said floating point result that is to be displayed in accordance with said desired number of decimal places based on a value of a most significant digit of said floating point result that is not to be displayed in accordance with said desired number of decimal places.

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10. The information processing system of claim 9 , wherein: the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from a cognitive graph nexus; the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph nexus; the third cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third cognitive graph vector away from the cognitive graph nexus; the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices; the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices and data within a third; and the refining further comprising limiting the third set of data to data within a third certain index of the third cognitive graph vector indices.

9. The information processing system of claim 7 , further comprising: associating a third set of data within the cognitive graph with a third cognitive graph vector of the plurality of cognitive graph vectors; and, wherein the refining the cognitive insights based upon the limitation relating to one of the plurality of cognitive graph vectors further comprises identifying a limitation on one of the first, second and third cognitive graph vectors and refining another of the first, second and third cognitive graph vectors based upon the limitation of one of the first, second and third cognitive graph vectors.

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11. The method of claim 10 , further comprising the step of setting α to a value of 1.

10. The method of claim 9 , wherein the step of additive smoothing comprises the steps of: computing a smoothed probability ^P ij of an open bigram c i c j in the input sequence S 1 with the formula P ^ ij = p ^ ⁡ ( c i ⁢ c j | S 1 ) = X ij + α ∑ k = 1 M ⁢ ∑ l = 1 M ⁢ X kl + α ⁢ ⁢ U , where α is a parameter that controls intensity of the smoothing and U is a number of unique open bigrams that occur in at least one of the input sequence and the known sequence.

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1. A method comprising the steps of: receiving a hash level indicating a particular depth in a first document and a second document, wherein: the first document comprises a first plurality of nodes, wherein one or more nodes of the first plurality of nodes are at a depth that is greater than the particular depth; and the second document comprises a second plurality of nodes, wherein one or more nodes of the second plurality of nodes are at a depth that is greater than the particular depth; based on the hash level, identifying a first subset, of the first plurality of nodes, that do not include any nodes, in the first plurality of nodes, that are at a depth that is greater than the particular depth, wherein the first subset includes at least two nodes that are at the same depth; based on the hash level, identifying a second subset, of the second plurality of nodes, that do not include any nodes, in the second plurality of nodes, that are at a depth that is greater than the particular depth, wherein the second subset includes at least two nodes that are at the same depth; for each node included in the first and second subsets, computing a hash value based on said each node and one or more descendants of said each node; performing a plurality of comparisons between hash values of different nodes that are only in the first and second subsets; based on the plurality of comparisons, generating an edit script; wherein the method is performed by one or more computing devices.

6. The method of claim 1 , wherein the hash value for a node is generated based on a name or content of the node, one or more attributes of the node, and hash values of all immediate children of the node.

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9. The method of claim 8 , wherein the entity mentions refer to entities that have social accounts registered at the heterogeneous online social environments.

8. A method for converting entity mentions in a feed item to online social environments specific identifiers for cross posting on heterogeneous online social environments, the method including: receiving a feed item that includes an entity mention; resolving the entity mention using a lookup to find tag formats specific to heterogeneous online social environments; encoding the tag formats in different instances of the feed item; and automatically cross posting to the heterogeneous online social environments associated with the entity mention using the tag formats compatible with the heterogeneous online social environments.

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8. The apparatus of claim 6 , wherein presenting the graphical representation of the question strength score comprises presenting the graphical representation in real time as a user inputs the question text into the user interface.

6. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive question text comprising at least a portion of a question to be submitted to a question answering system in a user interface; determine a question strength score for the question text, wherein the question strength score represents a likelihood the question text will result in a correct answer with high confidence; present a graphical representation of the question strength score in the user interface; generate a question forming tip for rephrasing the question text based on the comparison of a natural language processing structure of the question text and a question type of the question text to known good structures and types in a question history; and present the question forming tip in the user interface.

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47. A system comprising one or more computers programmed to perform operations comprising: receiving a keyword; retrieving document-based information to be used in selecting a meaning for the keyword from a database, where the database associates each of a plurality keywords with information related to the keyword, and the document-based information is related to the keyword; determining one or more document term meanings of the document-based information, the determining comprising, for one or more documents in the document-based information, selecting one or more meanings for terms in the document from meanings associated with the terms in a computer-readable data collection that includes terms and associates at least one meaning with each term, and then determining one or more document term meanings of the document from the one or more meanings for terms in the document; determining, in the system, a plurality of keyword meanings of the keyword by selecting a plurality of meanings from meanings associated with the keyword in the computer-readable data collection; determining, in the system, a strength of relationship between each candidate keyword meaning and each document term meaning of the document-based information, and determining a respective selection probability for each candidate keyword meaning from the strengths; selecting a keyword meaning from the plurality of candidate keyword meanings according to the respective selection probability of each candidate keyword meaning; matching the keyword to web page content associated with a web page; determining a semantic sub-space defined by a radius of semantic distance from the keyword meaning, identifying an advertisement having an advertisement meaning that falls within the semantic sub-space, and matching the keyword to the advertisement; associating, in the system, the advertisement with the web page content; and outputting the advertisement when the web page is displayed.

48. The system of claim 47 , wherein the document-based information comprises text of advertisements associated with advertisers who have bid on the keyword.

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4. The method according to claim 3 , wherein, the step of loading the language resource file corresponding to the read interface language and displaying the character string in the loaded language resource file on the interface of the software comprises: invoking the language resource file corresponding to the interface language recorded by the current language configuration option; analyzing out each character string corresponding to a description of the software interface and recorded by the language resource file; and displaying the analyzed character string on the interface of the software.

5. The method according to claim 4 , further comprising: when an operation instruction for switching the interface language of the software sent by a user is received, analyzing the interface language needing to be switched to that is instructed by the operation instruction; updating a record of the current language configuration option in the configuration file of the software by using the analyzed interface language; loading the language resource file corresponding to the analyzed interface language; refreshing the interface of the software, and displaying the character string in the loaded language resource file on the interface of the software.

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2. The method of claim 1 , wherein the distance field is a regularly sampled distance field.

1. A method for embedding symbols of a message into a document containing a set of glyphs, comprising: representing a glyph in a document as a distance field; representing a symbol in a message to be embedded in the document as a modification of a subset of values in the distance field; and modifying the subset of values in the distance field according to the modification to produce a modified glyph in a modified document, wherein the symbol in the message is embedded in the modified glyph, wherein steps of the method are performed by a processor.

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2. The method of claim 1 , further comprising determining a domain in which the requesting web property is located.

3. The method of claim 2 , wherein identifying advertisements comprises identifying advertisements for which presentation of the advertisements with a web property is conditioned, by the placement criteria for the advertisements, on the web property being in the domain.

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6. A computer-readable physical storage medium that stores instructions executable by at least one processing device, comprising: instructions that, when executed, cause the processing device to: receive a first set of identification information identifying one two or more input documents for which a first generation relatedness score is sought; use said first set of identification information to access a stored computer-accessible index to produce a second set of identification information identifying one or more citationally related documents, said one or more citationally related documents being citationally related to said at least two or more input documents at a first or higher generation citational relationship; assigning a first generation relatedness score to said two or more input documents, said first generation relatedness score being calculated at least in part by counting a number of shared citational relationships occurring between said two or more input documents and said one or more citationally related documents at second generations or higher, said first generation relatedness score being statistically calculated to indicate whether a first generation citational relationship exists between said two or more input documents, wherein first generational relationships exist between documents when a first document directly cites to a second document, wherein second generational or higher relationships exist between the first document and a third documents when the first document cites to one or more intervening documents that cite to the third document; and output the first generation relatedness score between said two or more input documents.

9. The computer-readable physical storage medium of claim 6 , wherein said instructions, when executed additionally cause the processing device to display on a computer display module said first generation relatedness score of said two or more input documents.

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3. The method of claim 1 wherein the recommender system is selected from the group consisting of: a set-top box, a personal communications device, a mobile telephone, a personal digital assistant, a personal computer, a tablet computer, a gaming console, a head-end server, a server, and a plurality of servers.

1. A method for associating a second media content item with a first media content item, wherein the first media content item comprises a first audio/video content and the second media content item comprises a second audio/video content, the method comprising: receiving, by a recommender system, a first map of a first delimited segment of the first media content item, the first map comprising a first sentiment-state keyword associated with the first segment and a first temporal delimitation of the first segment; receiving, by the recommender system, a second map of a second delimited segment of the second media content item, the second map comprising a second sentiment-state keyword associated with the second segment and a second temporal delimitation of the second segment; comparing, by the recommender system, the first and second maps; and if a result of the comparison is a favorable result for a temporal extent associated with the first and second temporal delimitations, then associating, by the recommender system, the second media content item with the first media content item.

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10. The system according to claim 9 , wherein said computer processor identifies at least one node that has a locked parent node, and wherein said source control processor locks the at least one node that has a locked parent node, the locking of the at least one node that has a locked parent node includes disallowing revisions to the at least one node that has a locked parent node.

9. A system for source control in a program, the program comprising a plurality of hierarchical nodes for execution of a plurality of processes, the hierarchical nodes comprising parent nodes and child nodes, said system comprising: a graphical user interface for selection of a process of the plurality of processes by a user, the selected process including less than all of the files in the program; a computer processor for identifying nodes in the selected process and identifying at least one node that shares a parent with a node in the selected process; a source control processor for locking the nodes in the selected process, the locking of the nodes in the selected process includes disallowing revisions to the nodes in the selected process, said source control processor locks the at least one node that shares a parent with a node in the selected process, the locking of the at least one node that shares a parent with a node in the selected process includes disallowing revisions to the at least one node that shares a parent with a node in the selected process, wherein said source control processor only locks the files in the selected process and the at least one node that shares a parent with a node in the selected process such that revisions are allowed to files not in the selected process and files that do not share a parent with a node in the selected process.

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28. The method of claim 22 , further including processing the usage data to identify application usage data and location data including real-time location data and to correlate the application usage data and the real-time location data to identify a place where at least one of the applications was used.

29. The method of claim 28 , further including providing an advertisement to the wireless device based on the place.

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36. The record management system of claim 30 , wherein the computing device further displays said electronic document in a workspace having a plurality of editor window panes that have a visible and logical association with the individually numbered insertion points that are present within the document, wherein said workspace displays the content of said electronic document in an additional window pane with the dictation insertion points highlighted.

30. An electronic medical record management system for generating an electronic medical document based on a specific context from among a plurality of contexts within which an event may be documented, the system comprising a server coupled to one or more workstations, wherein a computing device of the server or one of the one or more workstations: provides one or more headings and a selection of available subheadings corresponding to each of the one or more headings; receives input signals from one or more authors to enter content for association with one or more of the selection of available subheadings corresponding to at least one of the one or more headings; converts each of the one or more available subheadings for which an input signal to enter content has been received into a corresponding one of one or more selected subheadings to be associated with a position within a structural hierarchy; receives input signals from the one or more authors to associate one or more of a plurality of contexts with the entered content and/or selected subheadings and corresponding headings; defines outlines for presenting the content to the one or more authors in an electronic medical document; and generates the electronic medical document including the content and the associated selected subheadings and headings that are associated with a specific context from among the plurality of contexts.

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52. The apparatus of claim 48 wherein the scanner identification information is stored at least partially in hardware.

48. The apparatus of claim 44 wherein the public/private key pair includes scanner identification information.

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5. The method of claim 1 , wherein the personal speech model components are personal language model components.

1. A method for updating a first speech model in a speech recognition system, comprising: receiving from a user device of a user, the user device comprising a personal speech model trained for the user through previous speech recognition operations, one or more personal speech model components of the personal speech model trained for the user through previous speech recognition operations, the one or more personal speech model components describing personal speech characteristics of the user; updating the first speech model using at least some of the one or more personal speech model components, by modifying at least one speech model component of the first speech model and/or adding at least one speech model component to the first speech model; and performing speech recognition on user speech using the first speech model updated with the at least some of the one or more personal speech model components.

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1. A computer-implemented method for offering suggested queries, comprising: receiving, by a computer, a keyword or phrase for a search query; searching, by the computer, electronic content of product review information for content related to the keyword or phrase; extracting, by the computer, word combinations from the content, wherein the extracted word combinations are at least two word phrases that are repeated a predetermined number of times in the content; combining, by the computer, one or more words from each extracted word combination with one or more words from other extracted word combinations to form composite phrases; identifying, by the computer, each of the composite phrases that are repeated a predetermined number of times in the content; ranking, by the computer, the identified composite phrases based on a number of occurrences of each of the identified composite phrases in the content; selecting, by the computer, query suggestions from the ranked composite phrases by selecting a defined quantity of query suggestions in order of the ranking; and presenting, by the computer, the selected query suggestions.

3. The computer-implemented method of claim 1 , wherein the word combinations extracted by the computer are word combinations comprising three or more words.

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17. The system of claim 16 , wherein the system further comprises an interface for monitoring the progress of the customized ring and the interface includes a ring image panel and displaying the text comprises displaying the text on the ring image panel.

16. A system for displaying customized bezel text of a customized ring, the system comprising: a computing device having computer implemented instructions stored thereon for receiving and storing custom bezel text input, the instructions comprising a text mapping module configured for performing a plurality of dynamic operations, the dynamic operations comprising: receiving bezel parameters; mapping the text in a two dimensional space; mapping the text in a three-dimensional space defined by bezel geometry; transforming the three-dimensionally mapped text into code for displaying the text on a screen; and displaying the text on a screen.