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38. The system according to claim 37 wherein said system further comprises: said state rule consisting of an antecedent part and a consequent part.

43. The system according to claim 38 wherein said consequent part further comprises: an optional disjunction of at least two rule nodes.

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1. An article of manufacture including a non-transitory computer usable medium having computer readable program code embodied therein for continuous querying of a data stream, comprising computer readable program code capable of performing the operations of: initializing a query including query cycles on a query engine to query the data stream for desired information; processing the data stream as segments, wherein a size of the segments is based on a defined parameter; synchronizing the query cycles with the segments of the data stream; analyzing a first segment in a first computer memory by performing the query on the first segment using a processor to obtain a first result; persisting query state of the query and rewinding a query operation to begin a new query cycle; and analyzing a second segment in a second computer memory in the new query cycle by performing the query on the second segment using the processor and based on the first result.

5. An article of manufacture as in claim 1 , wherein the computer readable program code is further capable of sustaining a buffer across query cycles to provide a sliding query window.

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27. The apparatus according to claim 26, further comprising means for categorizing the document into one of a plurality of pre-existing categories.

26. An apparatus for highlighting and categorizing images from a document using a sequence of word tokens representing words of the document, the word tokens comprising character shape code classes, each word of the document being represented by only one word token, the apparatus comprising: means for eliminating predetermined character shape code classes from said sequence of word tokens; means for removing predetermined common function word tokens from said sequence of word tokens to form a reduced sequence of word tokens using a pattern matching technique and a stop token list; means for determining word token frequency appearance rates for the word tokens of the reduced sequence; means for ranking said frequency of appearance rates; means for determining the nth or more most frequently appearing word tokens based on the ranked frequency of appearance rates; and means for highlighting words of the document corresponding to the nth or more most frequently appearing word tokens.

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4. The method as claimed in claim 2 , further comprising creating a header row, including: setting a state of an element to header nested; checking for nested dimensions until there are no more; setting the state of the element to check header current; filling the dimension with nested fillers; determining a summary level; setting the state of the element to header done; removing the nested dimension fillers; checking all children of the element until there are no more children; setting the state of the element to check nested; determining if there are any nested elements; filling a current dimension with nested dimension fillers; setting the state of the element to check siblings; moving the MDDS iterator to the next sibling; keeping a row copy; and setting the state to check ancestor.

2. A computer-implemented method of processing a multidimensional (MD) data set produced from an execution of a multidimensional query on a MD data source, the MD data set comprising data for a report described by the report specification based on an entity/relationship (ER) schema, the method comprising: producing a result set description matching the semantics of the report specification based on the ER schema from a MD data set description describing the semantics of the MD data set using result processing information; and converting MD data set into a collection of rows of data to generate a result set of the report output as a tabular result set when the ER report specification conforms to a tabular report, wherein converting the MD data set into a collection of rows of data includes, producing respective full stacks of members, each full stack representing a row of data available for inclusion in the collection of rows of data, wherein producing given full stack of members comprises: pushing a highest-level member of a dimension onto a stack, traversing parent/child relationships within a dimension along an edge to push each member at each level onto the stack, popping a top member off the stack, and pushing all siblings of the top member onto the stack; and converting the MD data set into a cross tabulated result set when the report specification conforms to a cross-tabulated report.

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33. The apparatus of claim 31, wherein the memory device further stores data structures comprising: a first memory block programmed to store a first database comprising at least one first record comprising at least one first field containing first field data; a second memory block programmed to store a second database, unrelated to the first database, and comprising at least one second record comprising at least one second field containing second field data; a third memory block programmed to store at least one index comprising at least one index record linking the at least one first record to the at least one second record according to a fuzzy logic relationship identified by the processor and corresponding to a subjective observation programmed into the processor by the user.

31. An apparatus for searching a set of databases, the apparatus comprising: a processor programmed to operate sub-engines controlled by a search engine, the sub-engine comprising: a standard search sub-engine for performing a deterministic search integrated with an integrated sub-engine selected from a key-word search sub-engine for performing a textual search, and a query search sub-engine for performing a fuzzy logic search, the standard sub-engine and integrated engine executing substantially simultaneously in the processor to search the set of databases, the search engine invokes a first sub-engine according to criteria reflecting the results of the search of a second sub-engine; a storage device operably connected to the processor for storing a plurality of searchable databases from the set of databases, each of the searchable databases comprising a plurality of fields containing data; a memory device having a plurality of blocks of memory, the memory device being operably connected to the processor to store selected data selected from the plurality of searchable databases; and an input device operably connected to the processor for providing inputs to the processor in resonse to actuation of the input device by a user.

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1. A method for creating a stored query for remotely accessing information comprising: receiving, at said computer, a selection of a query type, wherein said query type corresponds to a query template; receiving, at said computer, a query field and query criteria, wherein said query criteria is selected from an input list having a profile and stored at said computer; creating, at said computer, said query field, said query criteria, and said query type into a Structured Query Language (SQL) statement; executing, by said computer, said SQL statement to add said query field and said query criteria to said query template; creating, by said computer, said stored query based on said query template, wherein said stored query is stored in a query database; executing, by said computer, said stored query to create a first file; categorizing, at said computer, said first file such that it is available to a pre-determined group of users; placing, by said computer, said first file in a location accessible to said pre-determined group of users, communicating, by said computer, with an intermediary device, wherein said intermediary device: remotely obtains access data including location information and authentication credentials, wherein said access data is used to locate and at least one of: grant and deny access to said secure system, using a device of one of said pre-determined group of users; transmits said access data to said secure system; receives a validation of said access data from said secure system; and, allows said access to said secure system; and performing, by said computer, an analysis of said query database, wherein said analysis is based on performance data resulting from execution of said stored query on a database, and wherein said analysis determines at least one of: database fields that are queried least often and database fields that are queried most often.

7. The method of claim 1 , further comprising sending said first file to said pre-determined group of users by way of at least one of email, web page, facsimile, text message, and postal service.

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1. A method comprising: receiving, on a network device, a telephonic communication comprising speech; transcribing, on the network device, the telephonic communication to generate a transcript; detecting, on the network device, a tone generated by a telephone within the telephonic communication; and responsive to detecting the tone, supplementing, on the network device, the transcript with additional information.

3. The method of claim 1 , wherein supplementing the transcript with the additional information comprises supplementing a portion of the transcript associated with a predetermined amount of time with the additional information.

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4. A system according to claim 1 , wherein presentation of the at least one evergreen index based upon the closest matching of the topics to the user interest.

1. A computer-implemented system according to for providing orientation into digital information; comprising: a memory; and a processor operatively coupled to the memory and configured to execute computer executable program modules, comprising: an information storage module maintaining a plurality of evergreen indexes on a server for topically-limited subject areas, each of the subject areas comprising electronically-stored digital information and, for each of the evergreen indexes, comprising: a hierarchy of stored topics; and a stored topic model matched to each of the topics in the topic hierarchy, each of the topic models comprising a pattern evaluable against the digital information, wherein the pattern identifies such digital information matching the topic model's topic; a guide generator receiving a user interest in the digital information for the subject area of at least one of the evergreen indexes; a topic model matcher evaluating each of the patterns for the identified topic models against the digital information; a visual display providing access to the digital information organized according to each of the topics in the subject area; a query evaluator receiving a query comprising topic search terms and to match the topic search terms to the topics in the topic hierarchy; and a characteristic word evaluator designating at least one of the chosen topics and the topic search terms as characteristic words, examining all of the evergreen indexes, and identifying those evergreen indexes in the visual display that comprise the characteristic words.

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5. The method according to claim 1 , wherein the method further comprises steps of: a) changing a feature in the package concepts, and b) measuring the effectiveness of the newly changed package concepts, wherein the package concepts are compared with each other along several measures, based on package effectiveness decision criteria, to determine the effectiveness, and wherein the package effectiveness decision criteria comprise comparison of conversion ratios among indices along each stage of a shopper interaction funnel, effectiveness count per shopper segment, prominent value changes induced by the newly changed feature in the package concepts.

1. A method for measuring packaging effectiveness based on video-based analysis of a plurality of persons using a control and processing system that executes computer vision algorithms on a plurality of input images transferred to the control and processing system through a means for video interface, comprising the following steps of: a) processing a behavior analysis of a person based on a path analysis of the person by executing a computer vision-based tracking algorithm on the plurality of input images to obtain information about the person's behavior with package concepts using the control and processing system, b) processing a segmentation of the person, including demographic analysis, by applying a computer vision-based demographic classification algorithm to the plurality of input images in relation to the package concepts, c) detecting an emotion change of the person, d) producing indices along various interaction stages of the person with each package concept based on the behavior analysis, the segmentation, and the emotion change detection, e) sending the indices to a module for an association of measurements and analyses, which performs a package effectiveness measurement, including a comparison of the indices among a plurality of package concepts, and f) producing comparison results of the indices in relation to the segmentation, g) organizing the measurement of the packaging effectiveness based on the segmentation and trips of the plurality of persons, wherein the segmentation comprises demographic segments, including age-range, gender and ethnicity, wherein the trips comprise a shopping pattern of said plurality of persons, and wherein the indices comprise reach to attract index, attract to engage index, and engage to motivate index.

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1. A computer-implemented method, comprising: receiving sets of duplicate keywords for an advertising account, each set of duplicate keywords including keywords having common matching text for the set, each of the duplicate keywords corresponding to an advertisement for the advertising account; presenting, by a data processing device, a duplicate keyword interface in which the sets of duplicate keywords are displayed, the duplicate keyword interface including a duplicate keyword selection interface for requesting selection of keywords from the sets of duplicate keywords based on a selection criterion; receiving, by the data processing device and through the duplicate keyword interface, a keyword selection criterion for selecting duplicate keywords; identifying, by the data processing device and based on the received keyword selection criterion, at least two different sets of duplicate keywords that each include a duplicate keyword that satisfies the selection criterion; receiving a single action request to modify an attribute value of duplicate keywords in the at least two different sets of duplicate keywords that satisfy the selection criterion; and modifying, within each particular set of the at least two different sets of duplicate keywords, the attribute value for a proper subset of the duplicate keywords in the particular set, the proper subset being only those duplicate keywords in the particular set that satisfy the selection criterion, the modification being performed in response to the single action request.

9. The method of claim 1 , wherein selecting in each of at least two sets of duplicate keywords a duplicate keyword that satisfies the selection criterion comprises highlighting selected duplicate keywords to indicate the selection.

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16. The data processing system of claim 10 , wherein the computer-readable program instructions, when executed by the processor, further cause the data processing system to: verify that a computer device or a user retrieving the sensitive information is authorized to access the character string.

10. A data processing system for using a unique token in online transactions involving sensitive information to control access to the sensitive information, the data processing system comprising a processor and one or more storage devices embodying computer-readable program instructions that, when executed by the processor, cause the data processing system to: register at least one entity, the registering comprising associating the at least one entity with a subscription level; in response to receipt of the sensitive information from a merchant device, generate a unique token for use in place of the sensitive information, wherein the sensitive information comprises a character string stores as encrypted data; directly associate a sub-string of a character string with the unique token so that a direct association does not exist between the unique token and the character string, the character string comprising the sensitive information and the sub-string being configured to identify the character string without revealing the sensitive information; and access the character string stored as encrypted data in storage memory using the unique token and the sub-string to retrieve the sensitive information after transmission of a request for the sensitive information from a registered entity associated with a subscription level associated with a privilege to receive the requested sensitive information.

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3. The method of claim 2 , further comprising: summarizing a collection of scanned original text using an optically recognized highlighted text within said scanned text document to generate a summarized document.

5. The method of claim 3 wherein said summarized document is rendered remotely.

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2. Method according to claim 1 , further comprising determining an accumulated goal fulfillment by adding a plurality of determined goal fulfillments.

1. A method for providing a tutorial message to a driver in a vehicle using an in-vehicle tutorial system comprising a multimodal user interface, the vehicle comprising a processing unit and a plurality of sensors arranged internally and externally of the vehicle and configured to determine a driving context for the driver, wherein the method comprises the steps of: assigning at least an area of improvement, comprising at least one tutorial task, to the tutorial system, wherein different areas of improvement are related to one of a plurality of predefined different categories of improvement; identifying, using the processing unit, a driving context using information collected using the plurality of sensors provided with the vehicle for which a tutorial task is to be performed, the driving context comprising an operational context relating to environmental, vehicle, and traffic conditions under which the vehicle is operated wherein one of the plurality of sensors arranged internally of the vehicle is adapted to measure and detect a behavior of the driver during vehicle operation; based on the tutorial task and the driving context, selecting a tutorial message for the operational context, the tutorial message encouraging a desired driving behavior; providing the selected tutorial message to the driver using the multimodal user interface, wherein the tutorial message is provided as at least a combination of two of an audio, voice, visual, and haptic output during vehicle operation and after vehicle operation; logging a driver response to the provided tutorial message; and determining a correlation between the desired driving behavior and the driver response; determining a goal fulfillment based on the correlation between the desired driving behavior and the driver response; and selecting a further area of improvement to assign to the tutorial system based on the goal fulfillment, wherein the step of determining the correlation between the desired driving behavior and the driver response comprises relating the driver response to at least one of the plurality of predefined categories of improvement and establishing a skill level of the driver as one of at least novice driver and more skilled driver, the step of selecting the further area of improvement to be assigned to the tutorial system is further based on previous assignments to the plurality of predefined categories of improvement, and the step of selecting the tutorial message is at least partially based on the skill level of the driver.

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12. The system of claim 10 , in which the predictive models are determined based on at least one of: machine learning, rules.

13. The system of claim 12 , in which the machine learning based predictive models are determined based on at least one of: statistics, decision trees, Naïve Bayes.

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5. The method of claim 4 , wherein the Janus unit can alter how the semantic unit is networked in the network of semantic units only if the Janus unit possess the corresponding privilege thereto.

6. The method of claim 5 , further comprising: representing the semantic units, their information contents, the link units and the Janus units on several storage media, and influencing the Janus units of one storage medium by the Janus units of another storage medium.

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6. The method according to claim 1 , wherein said combining any of said affix automatons comprises combining ones of the affix automatons constructed for any subset of said affix types indicated in any of said agglutination templates, provided that said subset maintains a same relative order in a result of the combining as in said agglutination template.

1. A method for constructing an automaton for automated analysis of an agglutinative language, the method comprising: constructing, using a processor of a computer, an affix automaton for each of a plurality of affix types of the agglutinative language, wherein each of said affix types is associated with one or more affixes associated with a morphological concept; combining, using the processor of the computer, any of said affix automatons to form a plurality of template automatons, where each of said template automatons is patterned after any of a plurality of agglutination templates of any of said affix types for said agglutinative language; combining, using the processor of the computer, said template automatons into a master automaton; receiving, by the processor of the computer, a word in the agglutinative language as an input for analysis; executing the master automaton to perform a morphological analysis of the received word, using the processor of the computer; and responsive to the executing, producing an output that indicates an expected part of speech for the word based on which of said template automatons were traversed within said master automaton during the executing.

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1. A computer implemented method for the display of radiology, clinical, pathology, and laboratory reports as a single comprehensive medical report on a non-transitory computer-readable medium in a text, graphical or tabular format to assist in a proper diagnosis of a patient, the method comprising executing on a processor the steps of: optimizing a keyword search within a keyword searchable database of text data representing the radiology, clinical, pathology, and laboratory reports; restructuring and parsing the text data in the database to create spreadsheets corresponding to specific patient information taken from the radiology, clinical, pathology, and laboratory reports, wherein this step further comprises executing on a further processor the steps of: using a find/replace function to delete tabs, paragraphs, and colons in text; rebuilding paragraphs, or text data (or alphanumeric string), corresponding to specific patient information taken from the radiology, clinical, pathology, and laboratory reports, to create rows within a spreadsheet; reprocessing the same string of text data (or alphanumeric string) to create delimiters as placeholders for parsing the data into separate cells on the same row, each cell corresponding to one of the radiology, clinical, pathology, and laboratory reports; uploading and importing the rebuilt and processed text data (or alphanumeric string) into a spreadsheet application; directing the spreadsheet application to select the appropriate delimiters and text style; directing the spreadsheet application to select the appropriate pre-defined alphanumeric strings and text style; directing the spreadsheet application to batch replace pre-defined alphanumeric strings to allow standardization of report format; dynamically restructuring and parsing reports into text data (or alphanumeric string) (or alphanumeric strings) within cells across columns whereby the source text data (or alphanumeric string) is matched to a given row and the column content is matched as described by the column headings; dynamically enabling the “shrink to fit” feature and applying said feature to the text data (or alphanumeric string) (or alphanumeric strings) within a spreadsheet or database; dynamically using the “shrink to fit” feature when enabled as applied to text data (or alphanumeric string) (or alphanumeric string(s)) to analyze a spreadsheet or database efficiently; dynamically enabling the “fill color” feature, or background cell color, and applying said feature to all cells, and specifically only those cells, containing text data (or alphanumeric string) (or alphanumeric strings) within a spreadsheet or database; identifying cells within a spreadsheet or database by color coding to enable downstream processing or visual programming; associating cells containing text data (or alphanumeric string) (or alphanumeric strings) using said color coding; assigning a given background cell color to identify or classify the text data (or alphanumeric string) (or alphanumeric string(s)) contained within said cell; assigning a given background color to identify or classify the absence of text data (or alphanumeric string) (or alphanumeric string(s)) contained within cell; dynamically comparing the background color of a cell to another cell to generate or derive knowledge or understanding; matching of text data (or alphanumeric string) (or alphanumeric string(s)) contained within a cell, row, and/or column to a descriptive header term within a spreadsheet or database; classifying of text data (or alphanumeric string) (or alphanumeric string(s)) contained within a cell, row, and/or column to a descriptive header term within a spreadsheet or database; removing of any protected health information from said database in situations where de-identified patient data is required; and, dynamically applying the said methods to successive cells, rows, and/or columns of text data (or alphanumeric string(s)) in a spreadsheet or database; creating and applying a natural language processing engine to the database of spreadsheets for identification and translation of medical terminology contained in the spreadsheets; and applying a comprehensive automated analyzer to the natural language processed database of spreadsheets to identify and collate related medical information, wherein a result from the automated analyzer can then be viewed as the single comprehensive medical report in the text, graphical or tabular format on one of a computer or hand-held device to assist in a proper diagnosis of the patient.

4. The method according to claim 1 , wherein the step of optimizing a keyword search within the keyword searchable database further comprises the step of uploading the optimized results (records or reports) to a server for further processing.

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18. The computer-readable medium of claim 16 , the acts further comprising: receiving the query from a client computing device; and responsive to receiving the query, selecting the segment-specific ranker for ranking search results based upon the query.

19. The computer-readable medium of claim 18 , the acts further comprising: receiving a second query from a second client computing device, wherein the second query has a second subset of query attribute values that are different from the query attribute values; and selecting a general purpose ranker for ranking search results based upon the second query, wherein the general purpose ranker is selected rather than the segment-specific ranker.

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13. The diabetes management module of claim 11 wherein the membership module further operates to input the modified data entry into the logbook, wherein the data entry is not associated with the given structured collection procedure.

11. A diabetes management application residing on a portable computing device, comprising: a structured test module operable to administer a given structured collection procedure to the user of the portable computing device, where the given structured collection procedure specifies one or more collection events for obtaining blood glucose measures for a patient; a logbook configured to store data entries related to diabetes care of the patient, the logbook implemented in a data store on the portable computing device; an input module configured to present a given data entry to the user on a display of the portable computing device and receive modifications to values of the given data entry from the user, where the given data entry is retrieved from the logbook and includes a blood glucose measure and a time at which the blood glucose measure was taken, a membership rule set that defines rules for associating data entries received from the user with structured collection procedures including adherence of date and time and adherence to a previous data entry, where the membership rule set is stored in a data store on the portable computing device; and a membership module configured to receive the modified given data entry from the input module and evaluate the modified given data entry in relation to the given structured collection procedure using the membership rule set, where the input module, the structured test module and the membership module are executed by a computer processor residing on the portable computing device.

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17. The apparatus of claim 16 , wherein the memory is a volatile memory and the normalization cache is generated on-the-fly for each generation of a name-based speech grammar.

16. An apparatus, comprising: a processing unit; a memory to store a normalization cache; a name normalizer executing on the processing unit to: receive a name for normalization during a name-based speech grammar generation; check a normalization cache for the received name; normalize the received name and add the normalization result to the normalization cache, when the received name is not in the normalization cache; retrieve the normalization result from the normalization cache; provide the normalization result to a next process in the name-based speech grammar generation; a plurality of normalization caches, where each normalization cache corresponds to a different culture; and the name normalizer further to provide a normalization result in a culture to the next process in a name-based speech recognition grammar generation specific to that culture.

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16. The system of claim 1 , wherein the administrative toolkit further comprises a user management module configured to establish a plurality of access levels and further configured to control user access based upon rights given to the plurality of access levels.

1. A computer-implemented system including a computer processor configured to create an advertisement, the system comprising: a. an administrative toolkit configured to facilitate a template creator at a first location to create a template comprising a plurality of template portions, and to input content components to populate the template, the administrative toolkit comprising: i. a template definition and editing module configured to: 1. create the template at a development site accessible to the template creator and not accessible to an end user; and 2. establish rules governing content to be placed in one or more of the template portions; and ii. a template inventory management module configured to move a copy of the template from the development site to a production site accessible to the end user, thereby updating the production site; and b. an end-user interface configured to facilitate the end user at a second location to: i. access the copy of the template over an information exchange network after the copy of the template has been moved to the production site; and ii. populate one or more of the portions with content in accordance with the rules established by the template creator, whereby the end user can create a customized advertisement that conforms to standards set by the template creator, wherein: the administrative toolkit is different and separate from the end-user interface.

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4. The system of claim 1 , the interpolation component interpolates the original trajectory to a two-dimensional grid and performs a “rubber sheet” displacement technique to warp the handwriting.

5. The system of claim 4 , the displacement component performs a “rubber rod” displacement technique on the interpolated trajectory, which enforces rigidity constraints on the interpolated trajectory after application of the rubber sheet displacement technique resulting in a normalized handwriting.

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15. The computer-implemented method of claim 1 wherein the portion of the content selected comprises a misspelled word.

1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user.

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1. A computer-implemented method, comprising: obtaining, at a computing device having one or more processors, a parsable content feed from at least one server associated with a social network comprising a plurality of users, the parsable content feed comprising at least one of (i) user-generated text posts on the social network and (ii) user-generated text comments to posts on the social network; obtaining, at the computing device, a set of preferred languages for a user operating the computing device, the user being one of the plurality of users; identifying, at the computing device, a text portion in the parsable content feed, the text portion being a sub-portion of text of the parsable content feed; obtaining, at the computing device, a detected language for the text portion; comparing, at the computing device, the detected language to the set of preferred languages for the user; when the detected language does not match any of the set of preferred languages, displaying, by the computing device and proximate to the text portion in the parsable content feed, a clickable icon configured for displaying a machine translation of the text portion and the text portion, the machine translation of the text portion being to one of the set of preferred languages for the user; and displaying, by the computing device and in response to a user selection of the clickable icon, the machine translation of the text portion and the text portion in the parsable content feed.

4. The computer-implemented method of claim 1 , wherein the displaying of the machine translation of the text portion is after the text portion in the parsable content feed.

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5. The method of claim 4 , wherein the preferences include a preference of the user for a first media content application over a second media content application.

4. The method of claim 1 , further comprising: obtaining the set of instructions in accordance with preferences associated with the user of the computing device.

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2. The method of claim 1 , wherein the document includes a website.

1. A method, comprising: receiving a document; conducting a stopwords analysis of stopwords in the document, wherein conducting the stopwords analysis includes conducting stopwords analysis of introductory level stopwords suggesting introductory content and advanced level stopwords suggesting advanced content; conducting a reading level analysis of the document; conducting a feature analysis of the document; generating a stopwords score based on the stopwords analysis; and generating a document familiarity level based on the stopwords score, the reading level analysis, and the feature analysis, wherein generating the document familiarity level includes implementing a familiarity level classification function that incorporates weighting coefficients for each of the stopwords analysis, reading level analysis and the feature analysis.

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53. The method of claim 51 , wherein one or more of the price parameter and the performance parameter is adjusted based on a type of electronic content item.

51. The method of claim 50 , wherein the performance parameter is automatically adjusted based on one or more of predetermined time passed and predetermined number of clicks.

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9. The method according to claim 8 , said automatically identifying relationships in a medical ontology between medical concepts in said first set of medical concepts and said second set of medical concepts further comprising: identifying causation of medical conditions and treatments for medical conditions based on said medical concepts.

8. A method comprising: analyzing an electronic medical record (EMR) comprising structured data and unstructured data; annotating contents of said unstructured data and said structured data to produce annotations; using said annotations to create concept unique identifiers (CUIs), said analyzing comprising: automatically identifying a first set of medical concepts from said unstructured data in said EMR; automatically identifying a second set of medical concepts from said structured data in said EMR; and automatically identifying clinically relevant semantic relationships in a medical ontology between medical concepts in said first set of medical concepts and said second set of medical concepts in said EMR based on statistical associations between said CUIs; producing a score for relevant information from said EMR that is semantically related to a query based on strength of said clinically relevant semantic relationships between said first set of medical concepts and said second set of medical concepts; prioritizing a display of said relevant information based on said score; storing relationship information as a data structure in a computerized device; and providing, in response to said query, said relevant information.

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15. A non-transitory computer-readable medium storing software having stored thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: inputting, by a computing device, speech data that corresponds to a particular utterance of a particular speaker to a neural network having parameters trained based on propagation between an input layer and an output layer through one or more hidden layers located between the input layer and the output layer, wherein the one or more hidden layers were trained using utterances of multiple speakers, and wherein the multiple speakers do not include the particular speaker; generating, by the computing device and in response to inputting the speech data that corresponds to the particular utterance to the neural network, a representation of activations occurring at a particular layer of the neural network that was trained as one of the hidden layers located between the input layer and the output layer; comparing, by the computing device, the generated representation of activations occurring at the particular layer of the neural network in response to the speech data that corresponds to the particular utterance with a reference representation of activations occurring at the particular layer of the neural network in response to speech data that corresponds to one or more past utterances of the particular speaker; based on comparing the generated representation and the reference representation, determining, by the computing device, that the particular utterance was likely spoken by the particular speaker; and providing, by the computing device, access to the computing device based on determining that the particular utterance was likely spoken by the particular speaker.

17. The non-transitory computer-readable medium of claim 15 , wherein the operations comprise: obtaining, by the computing device access to the neural network; for each of multiple utterances of the particular speaker: inputting, by the computing device, speech data corresponding to the respective utterance to the neural network; and generating, by the computing device, a representation of activations occurring at the particular layer of the neural network in response to the speech data corresponding to the respective utterance; combining, by the computing device, the generated representations of activations occurring at the particular layer of the neural network in response to speech data corresponding to each of the multiple utterances of the particular speaker; and using, by the computing device, the combination of generated representations of activations occurring at the particular layer of the neural network in response to speech data corresponding to each of the multiple utterances of the particular speaker as the reference representation.

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1. A method of natural language utterance processing, the method being implemented in a computer system that includes one or more physical processors executing one or more computer program instructions which, when executed, perform the method, the method comprising: receiving, at the computer system, from a first user device, a natural language utterance; performing, at the computer system, speech recognition to determine one or more words of the natural language utterance; receiving, at the computer system, from a second user device, a non-voice user input that relates to the natural language utterance, wherein the first user device and the second user device are associated with a user and are independently operable of one another and of the computer system; processing, at the computer system, the non-voice user input to determine context information for the one or more words; determining, at the computer system, one or more interpretations of the one or more words based on the context information; generating, at the computer system, a user request related to the natural language utterance based on the one or more interpretations; selecting, at the computer system, at least one user processing device to process the user request such that the selection of the user processing device is based on a determination that content related to the user request resides at the user processing device, wherein the user processing device comprises the first user device, the second user device, or a third user device independently operable of the computer system; and transmitting, by the computer system, the user request to the user processing device to invoke the user processing device to process the user request.

11. The method of claim 1 , further comprising: determining, at the computer system, additional context information based on one or more of the natural language utterance or the non-voice user input, wherein the selection of the user processing device is based on the additional context information.

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2. The speech dialog control module of claim 1 , where the input signal is a speech signal.

3. The speech dialog control module of claim 2 , where the input device comprises a speech detecting unit.

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13. The logic set forth in claim 10 , wherein the predefined keyword is a name of a selected participant of the sub-group meeting; and wherein the alert is sent to the selected participant.

10. Logic encoded in a non-transitory tangible computer readable medium for execution by a processor, and when executed operable to: mix input streams received from participants of a conference call and distribute mixed streams to the participants, a first stream is provided at a first volume to participants of the conference call having a sub-group meeting and a second stream is provided at a second volume to remaining participants of the conference call; search selected input streams for a predefined keyword; and issue an alert to at least one participant in the sub-group meeting responsive to detecting the predefined keyword, wherein the predefined keyword detected in the second stream is played as the alert at a third volume that is higher than the second volume.

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1. A system, comprising: a computer processor; and a memory containing a program that, when executed on the computer processor, performs an operation comprising: receiving first and second queries for processing by a natural language processing (NLP) system; identifying first and second data sources related to the first and second queries, respectively, by associating one or more elements of the first and second queries to the first and second data sources; and upon determining that the first related data source is not in a corpus of the NLP system, ingesting the first related data source into the corpus, wherein the corpus includes a data store comprising information from one or more data sources formatted and stored into one or more objects; and upon determining that the second related data source is in the corpus of the NLP system: before searching the second related data source for at least one answer to the second query, determining a time-sensitivity value associated with the second query indicating a degree to which an accurate answer to the second query is dependent on a staleness of the second related data source, and upon determining that the time-sensitivity value satisfies a staleness threshold, re-ingesting the second related data source into the corpus.

4. The system of claim 1 , wherein determining the time-sensitivity value associated with the second query further comprises: performing a concept mapping to assign a concept to at least one element in the second query; upon determining that the concept is related to duration or time, assigning the time-sensitivity value based on duration or time specified in the concept; and upon determining that the concept is dependent on time by matching the concept to a pre-defined list of time-dependent concepts, assigning the time-sensitivity value based on the time dependency of the concept.

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10. A system for capturing information from a live conversation between an operator and a customer, comprising: a context designator executing on a processor and configured to: designate a context for the live conversation between the operator and the customer wherein the context is a form viewed on a computer screen and actively in use by the operator; obtain a visual cue setting from the operator during the live conversation, wherein the operator sets the visual cue by physically moving a cursor to an information field in the form; monitor the live conversation in response to setting the visual cue, wherein the visual cue triggers the conversion of the live conversation to text; a speech recognition engine executing on the processor and configured to recognize the live conversation as a text portion after converting the live conversation to text; and a document completion engine executing on the processor and configured to: interpret one or more cues in the live conversation, wherein the one or more cues comprises at least the visual cue; relate the one or more cues to the information field associated with the context for the live conversation; and store information obtained from the text portion into the information field within the context, wherein the information obtained from the text portion comprises at least one word spoken after the one or more cues.

14. The system of claim 10 , wherein the information field is designated as a particular type of information, and wherein the particular type of information is at least one selected from a group consisting of a number, a date, a phrase, a formatted number, and a formatted phrase.

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15. A system comprising: one or more processors; one or more memory units coupled to at least one of the one or more processors; and instructions comprised in at least one of the one or more memory units, the instructions, when executed at least in part by at least one of the one or more processors, configured to perform a method of programming an entity in an environment with a rule set: respective rules grouped according to at least one rule group having a rule group name; at least one group designated as a start rule group for the entity; the entity configured to accept input from an entity controller; at least one rule specified according to a rule-based programming language comprising: at least one language condition, comprising: at least one entity controller input condition; and at least one environment test comprising: a sensory condition comprising at least one of: an entity type condition; an entity status condition; an entity possessory condition; an entity sensory input condition; and an environment status condition; a language verb parameter representing a sensory object; and at least zero language adjectives representing the sensory object; at least one language verb, comprising at least one rule group transition verb; at least one language verb parameter, comprising: names associated with the respective rules; and a sensory object reference representing the sensory object of the language condition of the at least one rule; at least one language adjective; and at least one Boolean logic connector; the at least one rule comprising a rule priority, at least one language condition representing an action condition, at least one language verb representing an action, and at least one language verb parameter representing an action object; the entity comprising a rule group identifier; and the method comprising: receiving the rule set comprising the at least one rule; and programming the entity to: upon initialization of the entity, set the rule group identifier to one of the start rule groups; and for a rule cycle, to: evaluate one or more action conditions of respective rules of the one of the start rule groups identified by the rule group identifier and in descending priority order, within the environment to identify a satisfied rule having satisfied action conditions according to Boolean logic connectors of the satisfied rule; upon identifying a first satisfied rule, perform the first satisfied rule within the environment; and upon failing to identify a second satisfied rule, remain idle for the rule cycle.

16. The system of claim 15 , at least one rule comprising at least two action conditions joined by a Boolean logic connector.

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7. The method of claim 1 , wherein determining the normalized relevance scores for the input query text corresponding to the multiple domains comprises, for a domain of the multiple domains: sequencing the input query text into at least one sequence of substrings; tokenizing the at least one sequence of substrings into a set of token sequences comprising at least one token sequence with respect to the domain based on the ontology of the query model for the domain; obtaining a set of normalized relevance measures with respect to the domain, each normalized relevance measures corresponding to one token sequence of the set of token sequences of the domain based on trigrams appearing in the one token sequence and the trigram corpus of the domain; and determining, as one of the normalized relevance scores for the input query text corresponding to the multiple domains, a normalized relevance score with respect to the domain for the input query text based on the set of normalized relevance measures with respect to the domain.

13. The method of claim 7 , wherein determining the normalized relevance measure with respect to the domain for the input query text comprises determining as the normalized relevance measure for the input query text a maximum relevance measure among the set of normalized relevance measures with respect to the domain each corresponding to one token sequence of the set of token sequences.

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10. The method of claim 8 , further comprising: retrieving a textual description for said face-specific video segments from a database using said processor; and displaying said textual description along with said representative image on said electronic display.

8. The method of claim 1 , further comprising: displaying on said electronic display a representative image for at least one video frame in said face-specific set of video frames for said at least one detected human face.

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10. A computing system comprising: a memory comprising instructions executable by one or more processors; and the one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: receive a search query from a client system of a first user of a social-networking system; identify one or more web pages responsive to the search query; determine, for each identified web page, from interaction data associated with the identified web page, a number of relevant interactions from among interactions with the identified web page by users of the social-networking system, wherein the relevant interactions are the interactions made by a subset of the users of the social-networking system having a type of relationship with the first user matching a setting of an application server of the social-networking system; rank one or more links to one or more of the identified web pages, respectively, based at least in part on the determined number of relevant interactions with the identified web page corresponding to the links; and send instructions for presenting a search-results page to the client system of the first user responsive to the search query, the search-results page comprising one or more links to one or more of the identified web pages, respectively, the links being presented in ranked order.

13. The system of claim 10 , wherein ranking the one or more links based at least in part on the number of relevant interactions comprises ranking the one or more links based on a number of times the link has been clicked by the second users divided by a number of times the link has been presented to the second users.

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2. The method of claim 1 , further comprising receiving, by the processor, an anonymity level value k, wherein each cluster in the plurality of clusters comprises at least k number of graphs.

1. A method, in a data processing system having a processor, for anonymizing data comprising a plurality of graph data sets, comprising: receiving, by the processor of the data processing system, input data comprising a plurality of graph data sets, wherein each graph data set comprises data for generating a separate graph from graphs associated with other graph data sets; performing, by the processor, clustering on the graph data sets to generate a plurality of clusters, wherein at least one cluster of the plurality of clusters comprises a plurality of graph data sets and wherein other clusters in the plurality of clusters comprise one or more graph data sets; determining, by the processor, for each cluster in the plurality of clusters, an aggregate property of the cluster; generating, by the processor, for each cluster in the plurality of clusters, synthetic data representing the cluster, from the determined aggregate properties of the clusters; and executing, by the processor or another computing device, one or more applications on the synthetic data to perform an operation on the synthetic data while preserving a privacy aspect of the input data.

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11. A method for identifying similarity between query samples and stored samples in an efficiently maintained reference library, the method comprising: receiving, by processing circuitry comprising at least one storage device and processor, a plurality of binary reference samples; processing, by the processing circuitry, each reference sample of the plurality of reference samples via operations including: assigning each reference sample a respective unique identifier; producing a reference sample fingerprint for each reference sample; and registering each respective unique identifier to reference sample fingerprint pair in a reference library via operations including: scoring the reference sample fingerprint with each previously stored fingerprint in the reference library to produce a first matching score; if the first matching score meets or exceeds a first threshold for a previously stored fingerprint, determining the reference sample fingerprint to be a duplicate of the previously stored fingerprint, and recording only a unique identifier associated with the reference sample fingerprint in the reference library, the unique identifier being marked as a duplicate of the previously stored fingerprint; and otherwise, if the first matching score is less than the first threshold for each previously stored fingerprint, storing a corresponding reference sample unique identifier to reference sample fingerprint pair in the reference library; receiving, by the processing circuitry, a binary query sample; processing, by the processing circuitry, the binary query sample via operations including: producing a query sample fingerprint from the binary query sample; scoring the query sample fingerprint with each previously stored fingerprint in the reference library to produce a second matching score; and for each previously stored fingerprint for which the second matching score meets or exceeds a second threshold, reporting a corresponding reference sample unique identifier associated with the previously stored fingerprint and the second matching score.

19. The method of claim 11 , wherein each of the reference samples is a passage of text.

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14. The system of claim 10 , wherein the processor is further configured to: calculate a plurality of query song jumpcodes by: (a) calculating a jumpcode in the time window; (b) moving the time window forward through the portion of the song; and repeating (a) and (b) until the time window moves through a threshold amount of the portion of the song.

10. A system for identifying a cover song from a query song, the system comprising: a hardware processor that: generates a beat-synchronized chroma matrix of a plurality of chroma vectors each having a plurality of chroma bins for a portion of the query song; identifies landmarks in the beat-synchronized chroma matrix, wherein a first prominent pitch at a first time in the portion of the query song and a second prominent pitch in the portion of the query song each correspond to an identified landmark; calculates a query song jumpcode based on differences between successive pairs of the identified landmarks in a time window of a size less than the size of the portion of the song identifies a plurality of reference song jumpcodes for a reference song, wherein each of the reference song jumpcodes is based at least in part on a change in prominent pitch between two times in a portion of the reference song; determines if the query song jumpcode matches any of the plurality of reference song jumpcodes; and upon determining that the query song jumpcode matches at least one of the plurality of reference song jumpcodes, generates an indication that the reference song is a cover song of the query song.

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2. The method of claim 1 , wherein the prediction model is a neural network.

3. The method of claim 2 , wherein the neural network is a multilayer perceptron neural network and wherein the neural network is trained by applying a backpropagation algorithm.

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1. One or more computer-readable memories comprising executable instructions to cause a computer to perform a method, the method comprising: receiving, from a user of the computer, an explicit choice of language; providing, from an accounting application program that executes on said computer to a database that stores a first representation of a first data record, said choice of language, said first representation of said first data record being in a numeric form and not being written words of a spoken language; submitting, from said accounting application program, a query to said database; receiving, from said database, a request to provide information that describes how to convert from said first representation into said language; providing, to said database, a first file that defines a correspondence between first elements of said first representation and second elements of said language, wherein said first file is provided in response to said request, said first elements being numbers that represent concepts, said second elements being words in said language, said first file containing a table that indicates which of the numbers corresponds to a particular word in the language; receiving from said database, in response to said query, a second representation of said first data record, said second representation being in said language and comprising one of said second elements, said one of the second elements being one of the words in the language; and determining said user's choice of language based on a logon credential that is associated with said user, and that said database collects before allowing said user to access data in said database.

3. The one or more computer-readable storage memories of claim 1 , wherein the method further comprises: installing, on the computer, a language pack that comprises (a) a label that indicates said language, and (b) said first file.

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3. The method of claim 1 , wherein displaying the wizard control panel, comprises: displaying a Natural Language Understanding element of the wizard that is configured for: viewing an intent and changing the intent; displaying a slot and a value and changing the slot and the value; wherein the Natural Language Understanding element is populated using results determined by an input understanding component of the conversational system.

1. A method for using a wizard control panel in a conversational system, comprising: receiving a user interaction with the conversational system during a dialog flow; receiving information associated with graphical entities of a user's display; displaying the wizard control panel including a display of elements that are used for affecting an automatic operation of the conversational system during the dialog flow and a display of a representative state of the user's display for interacting with the user's display by a human wizard; processing the user interaction to display results for the user interaction within the wizard control panel; determining receipt of an update to the results in the wizard control panel; and in response to determining the results are updated in the wizard control panel, submitting updated results to the conversational system, wherein submission of the updated results modifies operation of the conversational system before the automatic operation is processed.

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8. The method of claim 1 , wherein the estimated relevance score is calculated based on a plurality of weighted score components.

1. A method for providing for display an estimated relevance indicator for a result set of documents, the method comprising: receiving, at a computer comprising a processor and a memory component, a search query, wherein the search query includes a plurality of query terms; searching a database using the search query to identify the result set of documents, wherein the result set of documents are identified based on the search query; calculating an estimated relevance score for the result set of documents, wherein the estimated relevance score is indicative of a degree to which the result set of documents are relevant to the search query; providing for display on a graphical user interface a results feedback element and an estimated relevance element comprising the estimated relevance indicator based on the estimated relevance score, wherein the estimated relevance indicator provides a visual indication of the degree to which the result set of documents are relevant to the search query; updating the results feedback element based on the result set of documents; and updating the estimated relevance element to display the estimated relevance indicator based on the estimated relevance score.

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11. A non-transitory computer-readable medium storing instructions, which when executed by a processing device, cause the processing device to perform method comprising: receiving, within a datacenter management user interface, an action request to perform an action; determining, in response to receiving the action request, a first suggested object compatible with the action request, wherein the first suggested object is a datacenter or a component within the datacenter, wherein the component may be physical or virtual, and wherein the first suggested object is not displayed as a directly selectable option within the datacenter management user interface when the action request is received; and providing, in response to determining the first suggested object compatible with the action request, a first command suggestion within the datacenter management user interface, wherein the first command suggestion comprises the first suggested object.

17. The medium of claim 11 , the method further comprising determining a second suggested object is compatible with the action request and ranking the first and second suggested objects based on one or more of: frequency of accesses to each respective object within the datacenter management user interface, and current user context within the datacenter management user interface.

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10. A system for determining a user attention to at least one multimedia data element (MMDE) displayed in a web-page over a user computing device, comprising: an interface to a network for receiving a request to determine the user attention, wherein the request includes at least the web-page and an identification of the at least one MMDE in the web-page for receiving at least one sensory signal captured by at least one sensor connected to the user computing device; a processor; and a memory connected to the processor, the memory contains instructions that when executed by the processor, the system is configured to: query a deep-content-classification (DCC) system to find a match between at least one concept structure and the received sensory signal, wherein the at least one concept structure includes a plurality of metadata associated with reduced clusters of the MMDEs, the clusters represented by a compressed number of signatures; receive a first set of metadata related to the at least one matched concept structure; analyze the returned set of metadata to determine the user attention with respect to the at least one MMDE; and associate the at least one MMDE with the determined user attention.

11. The system of claim 10 , further comprising a database configured to save associations of the at least one MMDE with the determined user attention.

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11. A system comprising: a processor of a machine; a template generation module configured to generate, using the processor of the machine, a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; a user interface module configured to receive a content item from a first user of a group of users designated as contributors to the publication the user interface module further configured to receive, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and a generation module configured to generate the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user.

16. The system of claim 11 , wherein the user interface module is further to transmit, in response to receiving the content item, a notification to at least one other user in the group of users, the notification including a display of the content item, the notification providing an ability to edit the content item in accordance with contribution privilege information associated with the template.

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3. The system of claim 1 , wherein the summary excerpt of the representation of the page further comprises a summary of the representation of the page.

1. A records management system, comprising: a memory that stores instructions; and a processor that executes the instructions to perform operations, the operations comprising: designating an electronic storage location for a representation of a page of a document of a plurality of documents; creating an electronic data file for the plurality of documents, wherein the electronic data file includes the electronic storage location for the representation of the page and relates the representation of the page to a corresponding document of the plurality of documents; receiving data for the electronic data file, the data including information that identifies the representation of the page; correlating the representation of the page with the electronic data file such that the representation of the page and the electronic data file are accessible from a single electronic project file; and creating a summary excerpt of the representation of the page.

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9. The computer system of claim 8 , wherein: (A) creating the revised set of search terms further comprises comparing the one or more characteristics of the user and the entity data; (B) determining whether the one or more characteristics of the user match at least a portion of the entity data; and (C) if the one or more characteristics of the user match at least a portion of the entity data, creating the revised set of search terms at least partially based on the matched portion of the entity data.

8. The computer system of claim 5 , wherein creating the revised set of search terms further comprises creating the revised set of search based at least in part on the entity data.

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32. The method of claim 22 , wherein the interactive dialogue is saved in a voice xml format.

22. A digital conversation generation processor-implemented method, comprising: instantiating a processor-implemented dialogue agent application; populating the instantiated dialogue agent application on a dialogue platform; receiving a dialogue action from an individual target via the dialogue platform; generating a dialogue line in response to the received dialogue action via the dialogue agent; recording an interactive dialogue comprising the dialogue action and the generated dialogue line; determining a plurality of parameters associated with the interactive dialogue; allocating a value point to each dialogue element of the interactive dialogue; receiving pricing information from an ad exchange; adjusting the allocated value point of each dialogue element based on the received pricing information; creating a digital conversation asset comprising at least the retrieved interactive dialogue associated with the allocated value point to each dialogue element of the interactive dialogue; instantiating the created digital conversation asset; determining a key term of the digital conversation asset; determining a value for the digital conversation asset at least based on the determined key term of the digital conversation asset and the allocated value point to each dialogue element of the interactive dialogue; receiving information indicating a demand for the digital conversation asset; generating a subsequent exchangeable package for the ad exchange based on the instantiated digital conversation asset; determining a value for the subsequent exchangeable package; and facilitating a transaction of the subsequent exchangeable package between an owner of the digital asset and an ad participant.

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1. A computer based method of searching for documents, comprising the steps of: receiving a search query to search for documents, the search query including at least two terms; searching for related stored queries in a database of stored queries which were stored so to enable display of the related stored query as they were submitted and include at least two terms; wherein said searching is for related stored queries that include at least one term included in the received search query; displaying at least one of said related stored queries as submitted and that includes at least one term of said received query; and displaying at least one representation of a document that is related to one of said displayed related stored queries, the representation comprising at least one of a) a title, b) summary and c) a URL of said document.

21. The method of claim 1 , including storing said received search query as submitted by a user in said database as stored queries and storing said terms of the received search query in said database as related query terms of previously received query terms.

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10. The system that prioritizes comments of claim 1 , wherein the cloud manager application program further comprises a set of instructions for storing responses in the database that is communicably connected to the back-end server computing device and not stored in computer memory.

1. A system that prioritizes comments comprising: a client computing device comprising a processor, a memory, a display screen, and a non-transitory computer readable storage medium storing a client program which when executed by the processor prioritizes comments, said client program comprising sets of instructions for: selecting a set of comments from a plurality of pooled comments, wherein the set of comments and the plurality of pooled comments are related to a particular matter; displaying the set of comments related to the particular matter on the display screen; and providing a respondent-initiated response to a particular comment in the set of comments related to the particular matter; a web server computing device comprising a web server processor, a web server memory, and a non-transitory computer readable medium storing a comment prioritization web portal program which when executed by the web server processor facilitates comment prioritization by respondent clients, said comment prioritization web portal program comprising sets of instructions for: receiving a network connection request from the client computing device to access a cloud manager application service for prioritizing comments; and enabling the network connection from the client computing device, wherein the enabled network connection allows the client computing device to access the cloud manager application service for prioritizing comments and data transmission between the client computing device and the cloud manager application service is facilitated by the web server computing device; and a back-end server computing device comprising a back-end server processor, a back-end server memory, and a non-transitory computer readable medium storing a cloud manager application program which when executed by the back-end server processor provides a cloud manager application service for prioritizing comments, said cloud manager application program comprising sets of instructions for: retrieving the selected set of comments from a database that is communicably connected to the back-end server computing device; providing the retrieved set of comments to the web server for transmission to the client computing device for display on the display screen of the client computing device; and receiving the respondent-initiated response to the particular comment in the set of comments related to the particular matter.

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10. The self service system according to claim 1 , wherein: the computer system shows a two-dimensional plot including one data point representing each service enhanced resource delivery provided to the buyer over a time period plotted against the buyer's own satisfaction rating of said each service enhanced resource delivery; the computer system receives input from the buyer comparing previously purchased travel service bundles to select one of said previously purchased travel service bundles as a best bundle to use as a template for selection of future travel service bundles; and the computer system receives input from the buyer changing context attribute values, value resource parameters, and combined primary service and service enhancers criteria to obtain a desired travel service response set.

1. A self service system for composing and delivering a customized bundle of travel services, the system comprising: a computer system including one or more processing units to implement a travel service delivery program for buyers to select travel service choices, said computer system being configured for: using affective or emotive data to assist the buyers in said travel service choices, including receiving from each of the buyers input identifying a buyer context for said each buyer and selecting types of affective or emotive data about said each buyer, and actions authorized based on changes in the data; for each of the buyers, using said affective and emotive data in an adaptive algorithm to determine a plurality of travel service response sets for the buyer, each of the travel service response sets including a bundle of travel services for said each buyer; providing said each of the buyers with the plurality of the travel service response sets; and identifying a relevance of each of said travel service response sets in terms of the buyer context of said each buyer to facilitate said each buyer selecting one of the travel service response sets for purchase; for each of the buyers, once a buyer context is identified, showing to a travel service provider a service enhancer combination page for the selected buyer context, said page showing a plurality of service enhancers for a selected primary service; using said affective or emotive data to inform the identified buyer context of said each buyer to aid in said each buyer selecting and adjusting the travel service response sets; receiving from each of the buyers input for changing one or more of the travel service response sets; showing to said each of the buyers the effect on the plurality of the travel service response sets of said input for changing; and receiving input from the travel service provider to set one or more parameters for business effectiveness measurement, to select one or more of the buyer contexts to set values for detail attributes of services and service enhancers for the selected buyer context, and to select criteria for pricing and bundling guidelines.

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15. A method for processing electronically captured images formed by a plurality of spectral components comprising the steps of: electronically capturing image data with complex spectral content, the image data including a plurality of image data vectors defined with respect to a spatial image plane; establishing a plurality of candidate spectral components; actuating a discovery processor to execute a simultaneous sparse approximation process upon image data vectors of at least a portion of the captured image, actuating the discovery processor to adaptively discover for the image data vectors a set of core spectral signatures defined in terms of candidate spectral components automatically selected from a general dictionary; and, selectively matching at least one individual captured image data vector to at least a portion of said core spectral signature set to decompose said image data vector to a representation as a linear combination of the portion of said core spectral signature set; whereby constituent features of the captured image portion corresponding to said selectively matched core spectral signatures are discriminated according to said linear combination thereof.

17. The method as recited in claim 15 , wherein said simultaneous sparse approximation process is executed upon at least one selectively grouped set of image data vectors.

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4. The method of claim 3 , wherein only a selected limited number of lists are consulted to determine the subject matter of the question sentence.

3. The method of claim 2 , wherein the General Library Tables are subdivided into a number of lists.

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3. The method of claim 1 , wherein the number of IG-Trees is generated based on a number of features of the annotated data.

1. A method comprising: generating a number of Information-Gain (IG)-Trees based on a memory learning technique and training sets relating to a document, wherein the training sets are based on global context features, wherein a global context feature offers a broader view of a word or a word sequence with regard to an entirety of the document; extracting entity names and relations between entity names based on the IG-Trees; receiving annotated data; parsing, at least partially, the annotated data, wherein parsing includes identifying syntactic structure of sentences within the annotated data; and extracting the training sets from the parsed annotated data, wherein the training sets are further based on features including one or more of local context features, surface linguistic features, and deep linguistic features, wherein the global context feature, when included in an IG-Tree, further offers a set of first verbs in a same sentence that appear before or after the word or the word sequence for the entirety of the document or corpus.

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17. The computer-readable storage medium according to claim 16 , wherein the modifications include changes to attribute values associated with the selected user context object that describe behavioral, search and informational needs of the avatar.

16. A computer-readable storage medium storing computer instructions, which when executed, enables a computer system to facilitate use of a plurality of user context objects determined for an avatar that is online in a virtual universe, the computer instructions comprising: presenting the plurality of user context objects to the avatar, wherein the presenting of the plurality of user context objects to the avatar includes deriving the plurality of user context objects from all of the following: inventory items belonging to the avatar, teleportation history of the avatar, motion history of the avatar and social tagging behavior exhibited by a user of the avatar in the real world; receiving a user context object selection from the avatar, wherein the user context object selection contains one of the plurality of user context objects determined for the avatar and any desired modifications made to the selected user context object; and permitting the avatar to interact with the virtual universe in accordance with the user context object selection, wherein the permitting of the avatar to interact with the virtual universe includes instructions for applying the user context object selection to a robot avatar that is configured to allow the avatar to interact anonymously and semi-autonomously within the virtual universe.

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1. An event analysis system comprising: a network interface; an information database comprising articles received through the network interface from a first information source; a memory comprising: an event model comprising an event type and event attributes of the event type; an event detection engine; an event implication engine; an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; and a processor coupled to the memory and the network interface which is operable to: receive the articles; initiate execution of the event detection engine on the articles to detect an event involving the first model entity represented in the articles and apply the event model to generate an event object according to a common event structure which is independent of the first information source; initiate execution of the event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship; and generate a display of the event and the inferred event: where the event implication engine recognizes that the focus relationship exists between the focus entity and the first model entity and responsively generates the inferred event due to detection of the event involving the first model entity, and creates a new event object from the inferred event; where the event object comprises: an event type field: an event type probability field; an importance field; and a public interest field; where the network interface receives a public interest level value and importance level value of the event; and where the event detection engine is configured to: store an event type value in the event type field that indicates an event type; store an event type probability field value in the probability field that indicates the probably that the event type has occurred; store the importance level value in the importance field that indicates the importance level of the event; and store the public interest level value in the public interest field that indicates the level of interest of the public in the event.

2. The event analysis system of claim 1 , where the event detection engine is further configured to: determine whether any entities in the environment model are associated with the event; and discard the event when no entity in the environment model is associated with the event.

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15. A computer-readable, non-transitory storage medium having stored thereon a computer program which is executable by a computer, the computer program controlling the computer to execute functions of: displaying on a screen a handwritten document including a plurality of strokes described by handwriting; transmitting to a system a handwritten part designated by a select range on the screen; receiving from the system a reshaping result corresponding to the handwritten part; changing a line kind or a color of a plurality of strokes included in the handwritten part; and displaying the reshaping result in a manner to at least partially overlap with a display area of the handwritten part.

20. The storage medium of claim 15 , wherein the computer program further controls the computer to execute functions of: when the handwritten part includes one or more strokes corresponding to a handwritten character and one or more strokes other than a handwritten character, erasing a locus of the one or more strokes corresponding to the handwritten character from the screen; changing a line kind or a color of the one or more strokes other than the handwritten character; and displaying a display area of the reshaping result and a display area of the handwritten part in a partly overlapping manner.

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5. The method of claim 4 , wherein the machine learning uses known template documents as a ground truth to process the documents obtained from the clustered services.

4. The method of claim 1 , wherein the identifying of overlaps in the inferred dataset to cluster services together that have likely used corresponding templates is performed using machine learning.

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4. The method of claim 1 wherein the character pairs include the open and close bracket pairs { }; ( ); < >; and [ ].

1. A method for inputting characters in an electronic device having a user input device, a display for displaying characters input through the user input device, and a memory for storing characters input through the user input device, comprising: selecting a set of characters on the display; receiving an input character, the input character being an opening character of a predefined character pair through the user input device; and automatically adding to the memory and displaying on the display both the opening character and a corresponding closing character of the predefined character pair, the opening character being displayed before the selected set of characters, and the corresponding closing character being displayed after the selected set of characters.

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10. The computer-readable storage medium of claim 1 wherein at least one of the plurality of navigation providers is associated with navigation between two data units that share a dimension.

1. A computer-readable storage medium having computer-readable program instructions embedded therein for directing operation of a computer system, wherein the computer-readable program instructions, when executed by a processor on the computer system, enable the computing system implement a data processing system, that comprises: a model service system receiving, as an input, an object model description, indicative of a first object model that represents business data, and generating a dimensional model based on the input; an entity generator generating a second object model based on the dimensional model, the second object model representing business data represented by the dimensional model; a navigation service identifying a data navigation path from relationships between individual sets of data that comprise the business data, and outputting the data navigation path for navigation by a user from a first data set to a related second data set wherein the navigation service comprises: a plurality of navigation providers each associated with a specific type of navigation; a navigation service layer transmitting a navigation service request to one or more of the navigation providers that are registered with the navigation service layer; and a metadata service providing the plurality of navigation providers with access to a metadata store, each navigation provider responding to a received data navigation request by interacting with the metadata service to identify at least one data navigation path and returning the at least one identified data navigation path to the navigation service layer for output to the user; and a computer processor being a functional component of the data processing system and activated by the model service system, the entity generator and the navigation service to facilitate receiving the object model, generating the second object model and identifying the navigation path.

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28. A computer-readable memory device that includes programming instructions to control at least one processor, the computer-readable memory device comprising: instructions for calculating a first value representing a coherence of terms in a sequence of terms; instructions for calculating a second value representing variation of context in which the sequence occurs, where the variation of context in which the sequence occurs is calculated as a measure of entropy of the context of the sequence; instructions for identifying that the sequence is a semantic unit based on the first and second values; and instructions for outputting an indication that the sequence is a semantic unit.

40. The computer-readable memory device of claim 28 , where the sequence includes three or more words.

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9. A method as claimed in claim 8 wherein said UML is extended to provide for a single graphical element to represent a virtual transition between two or more states.

8. A method as claimed in claim 1 wherein said state/event model is provided using Unified Modeling Language (UML).

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18. The system of claim 13 , wherein the further processing includes using a language model to determine the refined score; and wherein the system further includes a storage device configured to store the language model.

13. A system configured to process text input, comprising: an input device configured to receive a sequence of user inputs; and a processor coupled to the input device and configured to: assign to each of a plurality of candidate sequences of one or more characters, each associated with a candidate key which has been identified as a candidate with which a received user input is associated, an initial score based at least in part on a keyboard geometry-based value associated with the received user input with respect to the candidate key; perform further processing with respect to a subset of the candidate sequences having the highest initial score(s), without at least initially performing the same further processing with respect to one or more other candidate sequences not in the subset, to determine for each candidate sequence in the subset a refined score; and select a candidate sequence for inclusion in a result set based at least in part on a determination that a refined score of the selected candidate is higher than an initial score of one or more candidate sequences that are not included in the subset and with respect to which the further processing has not been performed.

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32. A portable device according to claim 30, wherein said areas are equivalent to or larger than a predetermined minimum size.

30. A portable device according to claim 29, wherein the areas on the writing surface corresponding to each correlation vector are of a predetermined size and shape.

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1. A computer-implemented method for identifying phrasal terms, the method comprising: receiving a text having a plurality of words using a processor; determining a plurality of contexts using the processor, wherein a context comprises one or more words proximate to another word in the text, the plurality of contexts including contexts with differing lengths, wherein some of the contexts have a length of a number of words and some other contexts have a different length of a different number of words; for each context, determining a first frequency using the processor based on a number of occurrences of the context within the text; assigning a first rank to at least one context using the processor based on the first frequency for the at least one context; determining multiple word-context pairs using the processor and, for each word-context pair, determining a second frequency using the processor based on a number of occurrences of the word associated with the word-context pair being used in the context; assigning a second rank to at least one word-context pair using the processor based on the second frequency for the at least one word-context pair; determining a rank ratio for each word-context pair equal to the first rank divided by the second rank using the processor; determining a mutual rank ratio using the processor based on multiple rank ratios, the multiple rank ratios including rank ratios associated with contexts of differing lengths; normalizing the mutual rank ratio to account for the contexts of differing lengths using the processor; and identifying a phrasal term using the mutual rank ratio using the processor, the phrasal term being a multiword unit of a vocabulary.

2. The method of claim 1 wherein determining a mutual rank ratio comprises: selecting a first rank ratio for a first word-context pair, wherein the word in the first word-context pair comprises a first word, wherein the context in the first word-context pair comprises a second word following the word in the first word-context pair; selecting a second rank ratio for a second word-context pair, wherein the word in the second word-context pair comprises the second word, wherein the context in the second word-context pair comprises the first word preceding the word in the second word-context pair; and multiplying the first rank ratio by the second rank ratio to determine the mutual rank ratio.

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2. The system as claimed in claim 1 , further comprising a model annotator module for reflecting modularity defects on graphs via colored nodes and edges.

8. The system as claimed in claim 2 , wherein the nodes and edges are colored with different strengths depending upon the number and severity of modularity defects.

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17. The computer-implemented method of claim 15 , wherein the at least one subsequent confidence threshold comprises a first subsequent confidence threshold and a second subsequent confidence threshold that is lower than the first subsequent confidence threshold; and the method further comprises: determining that none of the text data is associated with a confidence level that exceeds the first subsequent confidence threshold; determining that at least one text data is associated with a confidence level that exceeds the second subsequent confidence threshold; and indicating additional processing on the at least one text data is required to translate the raw audio data.

15. The computer-implemented method of claim 10 , wherein the confidence threshold comprises a set of confidence thresholds, the set of confidence thresholds including a first confidence threshold and at least one subsequent confidence threshold that is lower than the first confidence threshold; and the method further comprises: determining that none of the text data is associated with the respective confidence level that exceeds the first confidence threshold; and determining whether any text data is associated with the respective confidence level that exceeds the at least one subsequent confidence threshold.

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13. The handheld electronic apparatus as claimed in claim 11 , wherein the parsing procedure further comprises: removing the full parsed result when the touch coordinates does not match the corresponding position of the specific text group.

11. A handheld electronic apparatus, comprising: a touch display; a storage unit, configured to store a plurality of program instructions; a parsing unit, configured to parse a content of a document; and a processing unit, coupled to the touch display, the storage unit and the parsing unit, and configured to execute the program instructions to execute a parsing procedure, comprising: activating a browser to download the document from a webpage for displaying the content of the document, wherein the browser supports a text parsing function; disabling the text parsing function and parsing the content of the document according to a markup language rule to generate an object parsed result; enabling the text parsing function and removing the object parsed result when a touch event is detected; parsing the content to find out text groups according to a preset pattern database and re-parsing the content of the document according to the markup language rule to generate a full parsed result when the touch event is detected and after removing the object parsed result, wherein the preset pattern database comprises a plurality of specific patterns, and a format of each of the text groups conform to one of the specific patterns; determining whether a touch coordinates matches a corresponding position of a specific text group of the text groups; and performing a corresponding action related to the specific text group when the touch coordinates matches the corresponding position of the specific text group.

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17. The apparatus of claim 16 , wherein said apparatus is implemented within an intrusion detection system and intrusion prevention system (IDS/IPS) operative to analyze packets transiting between an unsecured network and a secured network.

16. An apparatus, comprising: a memory for storing program logic; and a processor operably coupled to the memory and configured by the program logic stored thereon to estimate a worst-case time complexity of a regular expression comprising one or more back-references (backref-regex), the regular expression defining a pattern adapted for identifying malicious packets, the program logic comprising: logic for constructing a non-deterministic finite automaton (NFA) corresponding to the backref-regex (backref-NFA), wherein the backref-NFA comprises a plurality of NFA-states and a respectively labeled edge for each of the one or more back-references of the backref-regex; logic for performing liveness analysis on the backref-NFA to determine for each NFA-state of the backref-NFA a set of back-references alive at the NFA-state; logic for determining a maximum number of alive back-references over the plurality of NFA-states, wherein the determined maximum number is indicative of the worst-case time complexity of the backref-regex; and if the indicated worst-case time complexity is below a pre-defined threshold, logic for selecting the pattern for use in identifying malicious packets.

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16. A printing system for detecting motion quality error of printed documents comprising: a print engine configured to print a document having text lines comprising a plurality of characters; a scanning device configured to scan the printed document and to generate a scanned image having the text lines and the characters; and a processor configured to: determine the orientation of the text lines in the scanned image with respect to a process direction of the printing system; detect positions in the process direction of the printing system of one of the text lines and the characters in the scanned image; determine position errors in the process direction in the printed document based on the detected process direction positions of one of the text lines and the characters in the scanned image and the determined orientation of the text lines; determine at least one motion quality error of the printing system in the process direction based on the determined process direction position errors; and initiate an activity associated with the printing system in response to a motion quality error having been determined.

19. The system according to claim 16 , wherein the processor is configured to segment the scanned image into individual text columns, if there are multiple text columns in the printed document.

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15. The tangible computer readable storage medium as defined in claim 10 , wherein the messages are stored in a data structure, further comprising storing, for each one of the messages, an indication of the number of messages that preceded the one of the messages in the data structure.

10. A tangible computer readable storage medium comprising instructions that, when executed, cause a machine to at least: sort a set of messages based on a set of probabilities, the set of probabilities indicating a likelihood that the set of messages belong to a first classification; assign a first subset of first consecutive ones of the sorted set of messages to a first bucket; assign a second subset of second consecutive ones of the sorted set of messages to a second bucket, wherein a first message of the second bucket is consecutive to a last message of the first bucket with reference to the set of probabilities; determine a mean of probabilities of the first subset of messages assigned to the first bucket; store the mean in a tangible memory; store, for respective ones of the messages assigned to the first bucket, an indication that the respective message is assigned to the first bucket in the tangible memory, repeatedly (1) move a boundary between the first bucket and the second bucket and (2) recalculate the mean of probabilities of messages assigned to the first bucket in response to moving the boundary until deviations of the probabilities within the first bucket with respect to the mean are equal to or less than a threshold; and store a last recalculated mean as representative of the first bucket.

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4. A method of claim 1 further comprising: maintaining a database of authorized users; and providing the ability to deny access to unauthorized users.

1. A method for providing on-line testing comprising: maintaining a database of test questions comprising at least one text item or at least one item comprising text and images; providing on-line access to at least one of the test questions; presenting to a user the at least one of the test questions describing a task to be performed using a computer application; receiving from the user an answer to the at least one of the test questions comprising a captured image representing a computer screen prepared by the user based on the presented at least one of the test questions, representing the status of the computer screen after the user has performed the task using the computer application; and automatically associating the answer with the respective test question, for each of the test questions, to create an answer set.

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13. The method of claim 12 , further comprising attaching a confidence factor to the subsequent ad request based on the geographical information associated with the first IP address.

12. The method of claim 1 , further comprising: receiving a subsequent ad request for document, wherein the subsequent ad request includes the first IP address; determining if the subsequent ad request includes a set of geographic coordinates that meet a second set of predefined criteria; in response to the set of geographic coordinates in the subsequent ad request not meeting the second set of predefined criteria, searching for the first IP address in the IP region database; in response to finding the first IP address in the IP region database, deriving a set of coordinates for the subsequent ad request from the geographical location information associated with the first IP address in the IP region database; and annotating the subsequent ad request with the derived set of coordinates.

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11. The method of claim 7 , wherein the conditions of the at least one assertion comprise expectations pertaining to the quantity of data in a business intelligence output generated by execution of the business intelligence artifact.

7. In a general purpose computer, a method for automatically testing a business intelligence artifact in a business intelligence system, comprising: providing a business intelligence artifact in the business intelligence system, wherein the business intelligence artifact is a user-authored object that produces output when the business intelligence artifact is executed in the business intelligence system, and wherein the business intelligence artifact is selected from the group consisting of: a report specification and an analysis cube; creating at least one pre-execution or post-execution assertion with conditions to verify the desired function of the business intelligence artifact; testing, with an automated agent interfaced with the business intelligence system, the business intelligence artifact for problems by determining whether the business intelligence artifact satisfies the conditions of the at least one assertion before execution of the business intelligence artifact or by determining whether execution of the current version of the business intelligence artifact in the business intelligence system satisfies the conditions of the at least one assertion; and reporting errors in the business intelligence artifact if problems are detected during testing.

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8. The method of claim 1 , wherein the particular audio communication comprises a network-based audio communication session.

1. A method comprising: receiving, by a first computing device, one or more speech inputs during a conversation associated with a particular audio communication between the first computing device and a second device, wherein the first computing device stores identifying information associated with a contact associated with the second device, the identifying information comprising a name of the contact and an image associated with the contact; performing, by the first computing device, speech-to-text processing on the one or more speech inputs to generate text based on the one or more speech inputs; performing, by the first computing device and based on one or more keyword extraction criteria, keyword extraction processing on the text to generate one or more keywords that are relevant indicators of the conversation associated with the particular audio communication, wherein the one or more keyword extraction criteria comprise at least one criterion related to whether a word is used by at least two participants in the conversation; storing, by the first computing device, the one or more keywords; and outputting, by the first computing device and for display, a graphical representation of the one or more keywords in association with the identifying information comprising the name of the contact and the image associated with the contact.

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14. A system that facilitates predicting an epitope, the system stored on computer-readable storage media, the system comprising: a prediction component configured to predict epitope information by employing information from a plurality of sources including human leukocyte antigen (HLA) alleles and HLA supertypes to be processed by a classification model; a classification model engine executing a selected trained classification model employing information using standard and special features of the epitope, wherein the trained classification model is trained to include one or more hidden binary variables that represent a presence or an absence of the HLA supertypes, wherein the trained classification model is trained to include one or more shift variables to generate the epitope prediction, wherein the trained classification model is trained within the HLA alleles and within the HLA supertypes to generate the epitope prediction, and the classification model engine further executing the selected trained classification model to perform an optimization by determining a global maximum; and the classification model engine further executing the selected trained classification model to perform a multi-factor cross validation to confirm the epitope prediction.

19. The system as recited in claim 14 , wherein the classification model employs an expectation-maximization (EM) algorithm and a standard inference in determining a probability of whether a given peptide-MHC pair is an epitope.

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6. The system of claim 3 , wherein said keyword record generating module receives said plurality of aftermarket sales information each day at a prescheduled time.

3. The system of claim 1 , further comprising a keyword record generating module running on said one or more server computers and configured to: i) receive, for each of one or more sold domain names in a domain name aftermarket, a plurality of aftermarket sales information comprising: a) a sold domain name sold in said domain name aftermarket; b) a sale date on which said sold domain name was sold in said domain name aftermarket; and c) a sale price for which said sold domain name sold in said domain name aftermarket; ii) identify, in said sold domain name: a top level domain, one or more keywords, a quantity of said one or more keywords and an ordinal position of each of said one or more keywords; iii) generate, for each of said one or more keywords, said monetary value comprising a quotient calculated by dividing said sale price by said quantity of said one or more keywords; and iv) write to said database, for each of said one or more keywords: a) said sale date; b) said text string comprising one of said one or more keywords; c) said monetary value; d) said ordinal position, in said sold domain name, of said one of said one or more keywords; and e) said top level domain.

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6. The method of claim 1 , wherein processing one or more of the gap length or the corresponding video description content comprises inserting at least a portion of the video description content in one or more nearby gaps.

1. A method, comprising: receiving time-aligned script data comprising dialogue words of a script and timecodes corresponding to the dialogue words; comparing pauses between timecodes of adjacent dialogue words to a gap threshold that corresponds to a pre-specified period of time; ignoring pauses that do not meet or exceed the gap threshold; identifying pauses that meet or exceed the gap threshold as gaps between dialogue words for the insertion of video description content; aligning segments of video description content with corresponding gaps in dialogue, wherein the video description content for the segments is derived from corresponding script elements of the script; comparing a duration of a gap to a length of corresponding video description content to determine if the gap is of sufficient length for the insertion of the corresponding video description content; in an event that the gap is not of sufficient length, processing, responsive to determining that the gap is not of sufficient length and independent of user input, one or more of the gap length or the corresponding video description content such that the corresponding video description content is insertable into the gap; and generating a script document comprising the aligned segments of video description content.

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15. A computer program product for reviewing software source code, the computer program product comprising: one or more non-transitory computer-readable tangible storage medium and program instructions stored on at least one of the one or more non-transitory tangible storage medium, the program instructions executable by a processor, the program instructions comprising: program instructions to receive, by a computer, a changeset object containing information that identifies text changes made to source code statements in a source code module; program instructions to create, by the computer, a workflow of the source code module after the text changes identified in the changeset, wherein the workflow identifies execution paths among logical groupings of source code statements in the source code module; program instructions to identify, by the computer, logical groupings of source code statements in the workflow that contain text changes identified in the changeset; program instructions to generate, by the computer, an integrated graphical user interface (GUI) that will: display source code statements in the source code module with a visual indication of the identified text changes; display the workflow with a visual indication of the logical groupings of source code statements in the source code module that contain the text changes identified in the changeset; visually indicate logical groupings in the workflow that contain text changes that are selected by a user in the displayed source code statements; visually indicate source code statements in the displayed source code statements that are contained in a selected logical grouping in the workflow; link comments, entered by the user, that are associated with a source code statement in the displayed source code statements to the logical groupings in the workflow that contain the associated source code statements; link comments, entered by the user, that are associated with a logical grouping in the workflow to the source code statements in the displayed source code statements that contain the associated logical grouping; visually indicate the linked logical groupings when a source code statement in the displayed source code statements is selected; and visually indicate the linked source code statements when a logical grouping in the workflow is selected.

18. The computer program product of claim 15 , wherein the visual indication of the logical groupings that contain text changes is located adjacent to each logical grouping that contains a text change.

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14. The method of claim 13 , further comprising utilizing the genetic markers of the at least one target member of the family to support inferring the one or more genetic findings for the person.

13. The method of claim 1 , further comprising inquiring whether the at least one targeted member of the family of the person has genetic markers associated with the subject gene.

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11. The method of claim 10 , further comprising: determining whether the modified displayed object is already stored in the database; and responsive to determining that the modified displayed object is not already stored in the database, adding the modified displayed object to the database with a sticky flag.

10. The method of claim 1 , further comprising: responsive to exiting the edit mode, determining whether the modified displayed object conflicts with a conflicting word in a database; responsive to determining that the modified displayed object conflicts with a conflicting word, determining whether the conflicting word lacks a sticky flag; and responsive to determining that the conflicting word lacks a sticky flag, deleting the conflicting word from the database.

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8. A system comprising: one or more processors; and one or more computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause performance of operations comprising: providing a database of images and a textual description of the contents of a given image; receiving a search query from a user for retrieving an image associated with a subject matter of interest to the user from the database; evaluating the database including comparing the search query the textual description of the contents of a given image including automatically providing a plurality of images from the database to the user based on the query; receiving a selection of one of the plurality of images from the user; creating an association between the selected image and a concept including storing the association, wherein the concept is related to the subject matter of interest; after creating the association, receiving a request from another user for creating an image advertisement; determining that the request is related to the concept; suggesting the selected image for the image advertisement using the stored association and based at least in part on determining that the request is related to the concept; creating the image advertisement using the selected image; and storing the created image advertisement including storing the created image advertisement in association with the concept.

12. The system of claim 8 , wherein a first image among the plurality of images comprises an animated image.

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1. A method in a computer system with a processor and storage device for using a hierarchy showing a web page and child web pages in a web site for generating a feature of the web page, the method comprising: providing the hierarchy of the web pages of the web site, wherein a parent web page of the web site and a child web page of the web site have a parent and child relationship when the parent web page is identified by a parent uniform resource locator of a parent depth and the child web page is identified by a child uniform resource locator of a child depth such that the parent uniform resource locator is a prefix of the child uniform resource location and the child depth is one more than the parent depth irrespective of whether the parent web page has a link to a child web page or whether the child web page has a link to the parent web page; for each of a plurality of topics, calculating relevance of the web page to the topic by: when the web page has no child web page as indicated by the hierarchy, setting the relevance using the web page; and when the web page has a child web page as indicated by the hierarchy, setting the relevance using the web page and the child web page; and for each of a plurality of features, when the web page has no child web pages as indicated by the hierarchy, setting the feature of the web page using the web page; when the web page has a child web page as indicated by the hierarchy, setting the feature of the web page using the web page and using the child web pages.

2. The method of claim 1 wherein the feature further comprises a length; wherein the length is represented by the following: L ′ ⁡ ( p ) = { L ⁡ ( p ) Child ⁡ ( p ) = Φ ( 1 + α ) * L ⁡ ( p ) Child ⁡ ( p ) ≠ Φ where L′(p) represents an adjusted length of web page p, L (p) represents a length of web page p, Child (p) represents the child web pages of p, Φ represents the empty set, and α represents a factor for increasing the length of web page p.

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1. A computer implemented method of interpreting written text, said method comprising the steps of: providing an alphabet, at least one symbol for constructing lexical elements, and at least one syntactic element built on said alphabet, said lexical elements, and said at least one symbol on at least one computer; determining, by said at least one computer, a sort of value, an arity, a notation, and a type for each said syntactic element, to provide well-formed syntactic elements and meaningless syntactic elements; building, by said at least one computer, formal definitions from said well-formed syntactic elements, and determining a type for each said formal definition to provide a list of terminologies, assertions, theorems, questions and answers; building, by said at least one computer, at least one formal glossary as ordered sets of said formal definitions; providing, on said at least one computer, to an output of at least one said formal glossary, and a related minimal lexicon; parsing, verifying and normalizing each said formal definition, by said at least one computer, from said formal glossary, to provide a list of defined lexical elements and undefined lexical elements; accepting at least one input, wherein said at least one input includes at least one question containing at least one well formed syntactic element; retrieving for each said defined lexical element, at least one formal definition from said at least one formal glossary; applying said at least one formal definition to said defined lexical elements according to at least one interpretation process to provide at least one meaningful value; coding each said at least one input and said at least one meaningful value as a new questions and answers definition; and saving said new questions and answers definitions in said formal glossary in said computer, to provide an intelligent glossary.

21. A computer implemented method as in claim 1 , further comprised of the step of: providing an answer, by said at least one computer, to said actor as the meaningful value of a syntactic element, if said syntactic element is not meaningless; coding said meaningful value of a well formed syntactic element as a question and answer type definition; and saving in said at least one computer said formal glossary of said result definition, in accordance with said types of definition.

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21. A computer readable storage medium with executable instructions for identifying electronic documents stored on a computer readable media, and providing a search result in response to a search query, comprising: instructions for receiving a search query; instructions for identifying a predetermined number of documents that satisfy the search query, the predetermined number of documents including reference documents which are a subset of the identified documents that are deemed to be the most relevant to the search query and secondary documents; instructions for parsing text excerpts of the identified documents and applying text function tags to the text excerpts, wherein the text function tags identify semantic roles of the text excerpts; instructions for identifying the secondary documents that have text function tags that match the text function tags of a reference document; and instructions for generating a search engine results page in response to the search query, the search engine results page including a listing of the identified reference documents, each with a hyperlink to at least one secondary document, the at least one secondary document being a secondary document that has a text function tag that matches a text function tag of the reference document.

25. The computer readable storage medium of claim 21 , wherein the text excerpts parsed include sentences and snippets.

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9. One or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the computing system to personalize a language model for a particular target user, the computer-executable instructions causing the computing system to: identify a first set of data from usage history associated with the target user, the first set of data comprising at least one entity or user action; analyzing the usage history information for statistical data; map the first set of data to a personalized knowledge source for the target user, wherein the mapping comprises assigning probabilities to entities and relationships in the personalized knowledge source based on the statistical data, thereby providing a probabilistic personalized knowledge source; determine a set of users similar to the target user; map a second set of data to the personalized knowledge source for the target user, the second set of data comprising at least one entity or user action corresponding to the set of users similar to the target user, thereby creating an extended personalized knowledge source, the extended personalized knowledge source comprising a second entity and a triple indicating a relationship between the at least one entity or user action and the second entity, the mapping comprising at least one of incrementing a count of the one or more of the entity or calculating a weight of the one or more of the entity; and utilize the extended personalized knowledge source to build a personal language model for the target user for speech recognition.

12. The one or more computer storage media of claim 9 , wherein determining the set of users similar to the target user includes performing a clustering algorithm.

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12. A system for detecting and replacing global variables in code, comprising: one or more non-transitory computer-readable storage media, and program instructions stored on at least one of the one or more storage media; and a hardware processor for executing the program instructions, the program instructions comprising: code instructions for receiving a JAVASCRIPT code having at least one of a plurality of globally defined functions, said JAVASCRIPT code is received according to a user input received via an interface and generating at least one code segment for each globally defined function in said JAVASCRIPT code; code instructions for generating at least one call flow graph for each one of said at least one of globally defined functions; code instructions for generating an inter-procedural control flow graph for each one of said call flow graph; code instructions for generating an inter-procedural dominator graph for each one of said inter-procedural control flow graph; code instructions for identifying each of referenced global variables within each of said inter-procedural dominator graph and determining a JAVASCRIPT scope of each of said referenced global variables; code instructions for identifying at least one of: one or more confined global variables which receive a value within a first JAVASCRIPT scope of each of said referenced global variables wherein said value is not referenced outside of said first JAVASCRIPT scope, and one or more repeating global variables accessed repeatedly within a second JAVASCRIPT scope of each of said referenced global variables; and code instructions for automatically adding local variables in place of said repeating global variables or said confined global variables.

14. The system of claim 12 , further comprising code instructions for identifying at least one or more of said confined global variables, along paths of said inter-procedural dominator path.

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7. A system comprising: a processor, and memory storing computer readable instructions that, when executed by the processor, configure the system to provide: an input user interface that receives a speech input from a user, wherein the speech input is associated with a destination field in an application; a field recognition system that categorizes the speech input as either a dictation or a command, based on a flag associated with the destination field; dictation logic that, if the speech input is categorized as a dictation, converts the speech to text, and inserts the text into the destination field; a command interpreter that, if the speech input is categorized as a command, interprets the command; a query logic that, if the speech input is categorized as a command, translates the interpreted command into a format native to the application and sends the translated command to the application; communication logic that receives data from the application in response to the translated command; and an output user interface to provide a response to the user through multimodal output.

8. The system of claim 7 , wherein the output user interface further provides a visual indicator of the categorization to the user.

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22. A controller according to claim 12, wherein said graphical user interface includes means to vary text-to-speech conversion parameters.

12. A text-to-speech controller, comprising: a text buffer for storing a text file comprised by text characters organized into words; a controller for controllably feeding text characters in the text file from said text buffer to a text-to-speech converter; and command means including a graphical user interface for accepting input commands to alter how said controller feeds text characters from said text buffer to the text-to-speech converter; wherein said controller sequentially feeds text characters from said text buffer to said text-to-speech converter in the absence of commands from said command means, and wherein said controller alters how text characters are fed from said text buffer to the text-to-speech converter in response to commands from said command means which are effectuated at interword text boundaries.

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15. The method of claim 14 , wherein the developing an extraction pattern includes using an extraction command to segment the web page output of the respective web site into a plurality of units, and using a test condition that comprises a logical test and at least one argument, and wherein for each of the plurality of units, the logical test is computed with the at least one argument, and the unit is removed from the plurality of units if the logical test is not satisfied with the at least one argument.

14. The method of claim 7 , wherein the predetermined list of extraction commands includes an extraction command for segmenting the output of the respective web site into a plurality of units, each of the plurality of units matching the extraction pattern.

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16. A method of providing language interpretation service, comprising: providing a language access telephone number wherein that a caller speaking a first language and having a business need dials to place a telephone call to a language interpretation service to obtain language interpretation assistance; receiving a language access telephone call at the language interpretation service provider from the caller; identifying, after the telephone call is initiated, the first language from a plurality of languages with a voice recognition system so as to provide the caller with an interpreter that can translate between the first language and the second language, wherein the interpreter is associated with the language interpretation service provider; permitting the interpreter to telephonically engage a first agent representing a first business distinct from the language interpretation service provider that can serve a business need of the caller, wherein the first agent speaks the second language and the interpreter translates a conversation between the caller and the first agent; and determining whether the caller elects to be connected to a second business, wherein if the caller elects to be connected to a second business the interpreter telephonically engages a second agent representing the second business, wherein the second agent speaks the second language and the interpreter translates a second conversation between the caller and the second agent.

22. The method of claim 16 , further comprising establishing a first billing that accounts a time count that accrues from a time at which the language access telephone call starts until a time at which the first agent is engaged.

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10. The computer-implemented method of claim 1 , wherein the particular second service is a note service, further comprising: receiving a user input to store the message in a note application.

1. A computer-implemented method comprising: receiving, through a first service, a query, wherein the query comprises a reserved term associated with a particular second service; in response to receiving the query, interpreting the query as being directed to an action for the particular second service; identifying the particular second service; and providing a portion of the query to the particular second service to obtain a message for an application associated with the particular second service, the message comprising the portion of the query.

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11. The computer-readable storage medium of claim 10 , wherein the location identifiers comprise website links.

10. The computer-readable storage medium of claim 9 , wherein said content nodes store content to be accessed by the queries, and wherein indexing the links to said content nodes comprises indexing location identifiers to content in said content nodes.

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17. The computer-readable device of claim 14 , the actions implemented at least in part in an operating logic of a computing device.

14. A computer-readable device comprising processor-executable instructions configured to perform actions comprising: providing a mixed prototype database trained at least in part with one or more print and cursive samples; providing a cursive prototype database trained at least in part with one or more cursive samples; and using at least some of the mixed and cursive prototype databases for a cursive handwriting recognition operation.

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18. The eBook reader device of claim 17 , wherein the progress bar is presented along with another progress bar indicating progress of one or more other users in an electronic book.

17. An electronic book (eBook) reader device comprising: a display; one or more processors; and memory storing instructions which, when executed by the one or more processors, cause the one or more processors to perform acts including: identifying a progress of a user through a collection of electronic books that are associated with the eBook reader device or the user, the progress of the user being based at least in part on a number pages that have been consumed in the collection of electronic books, the collection of electronic books digital works comprising a plurality of electronic books; identifying an estimated amount of time to complete an electronic book of the collection of electronic books; identifying a number of session of consumption of the electronic book; presenting, on the display, a progress bar indicating the progress of the user through the collection of electronic books; presenting, on the display, the estimated amount of time to complete the electronic book of the collection of electronic books; and presenting, on the display, an indication of the number of sessions of consumption of the electronic book.

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10. A computer-implemented method as described in claim 7 , wherein the usage or reference of the user includes an immediately prior viewing of the page.

7. A computer-implemented method as described in claim 1 , wherein the history includes usage or reference of a user of an e-book-reading device on which the method is performed or that is associated with the electronic book.

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9. The phrase pair collecting apparatus according to claim 2 , wherein the processor is further configured to: filter new generated hypotheses such that only those relevant as phrase pairs representing causality are left.

2. The phrase pair collecting apparatus according to claim 1 , wherein: the storage medium is further configured to store predicate templates expressing mutually contradictory meanings; and for each of the first and second phrases for each of said one or more seed pairs, the processor is further configured to generate a new hypothesis by replacing the predicate template with another predicate template contradictory to the predicate template, wherein the another predicate template is read from said storage medium.