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6. A system according to claim 1 , wherein the processor of the system further comprises a database processing component configured to form the database of scenario data elements by: parsing a scenario sample into parsed portions, the scenario sample being associated with a cultural group of human subjects; associating each parsed portion of the scenario sample with a scenario resolution factor having a hierarchical structure, the hierarchical structure having a plurality of categories, each category being defined by at least one attribute, wherein each attribute includes at least one parameter, with each parameter having a parameter value, so as to form the scenario data element; associating a scenario data element identifier with each scenario data element; and compiling the scenario data elements into the database.

7. A system according to claim 6 , wherein the database processing component of the processor is further configured to parse a scenario sample including at least one of a linguistic element, a cultural element, a communication, an interaction, a condition, an environment, a purpose, and an effect.

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4. The computer program process code of claim 3 , each song node comprising metadata, the metadata comprising an artist associated with a song represented by the song node, and further comprising instructions for implementing an artist graph, the artist graph being generated by the crawler, the artist graph comprising a plurality of artist nodes each representing an artist, at least a subset of the artist nodes comprising metadata, the metadata comprising an artist name and song title, and at least a subset of the artist nodes further comprising at least one edge, each edge comprising a weight.

3. The computer program process code of claim 1 further comprising a stored set of listener preferences, the recommendation engine applying the listener preferences when providing a song recommendation.

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16. The system of claim 13 , wherein: the first resources are generic web pages and the second resources are video resources.

18. The system of claim 16 , wherein the operations further comprise: receiving a third search result from the second search engine; and inserting the third search result at a position between two otherwise adjacent first search results in the order, the position not being adjacent to the inserted one or more second search results.

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1. A method for compiling a unique sample code for specific web content, comprising: defining at least one sample code template comprising multiple sample code segments to be used for building a sample code for specific web content, said sample code segments at least comprising: a sample owner identifying code segment, and a sample identifying code segment; specifying the content of the sample code segments to be used for building said sample code, wherein the sample owner identifying code segment is specified by an Internet address of an owner of the specific web content; stringing the specified sample code segments to form the sample code; defining a digital path to a digital location via which access can be gained to the specific web content and which is mutually distinctive from the sample code; creating a cross-reference between the sample code generated during the stringing of the specified sample code segments and the digital path defined during the defining of the digital path; and providing the sample code with a time stamp indicating a time dependency of the specific web content.

12. The method according to claim 1 , further comprising providing the sample code with a segment defining a location to which the time stamp refers.

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25. The system of claim 19 , wherein the relevance measure is selected from the group consisting of: cover density rankings, vector space model measurements, okapi similarity measurements, three level relevance scores and hypertext induced topic selection algorithm scores, and wherein reinforcement learning determines which relevance measure is selected.

19. A system, comprising: a computing device and a storage device having computer-executable instructions stored therein which, if executed by the computing device, cause the computing device to perform operations comprising: obtaining a subject entity definition of a subject entity, a node depth criteria and an impact cutoff criteria; aggregating and preparing a plurality of data items that include data related to the subject entity for processing, wherein the data comprises at least one entity function, one or more entity function measures and a creation date for each of the plurality of data items; storing the aggregated plurality of data items in one or more context layers by a component of context; developing a subject entity situation summary by analyzing the subject entity related data, wherein the subject entity situation summary comprises a linear or nonlinear regression model of each of the one or more entity function measures, a relevance for each of the measures and one or more of the context layers; using the subject entity situation summary, the node depth criteria and the impact cutoff criteria to identify components of context to include in a composite index; creating a composite index for the data associated with the identified components of context, wherein the composite index comprises a column for the creation dates of the plurality of data items, a column for each of the identified components of context and a ranking for each of the plurality of data items of the composite index; receiving a search request from a mobile access device, and providing a plurality of search results in response to the search request, wherein the plurality of search results are prioritized using a weight comprised of a mathematical combination of an index position ranking and a ranking provided by a relevance measure, and wherein at least part of the data and the search request are obtained from a mobile device.

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9. A system according to claim 1 , wherein said attribute properties include content attribute properties comprising at least two of, (a) an allowable value set of an attribute, (b) a default value of an attribute, (c) a maximum number of values allowed for an attribute and (d) an indication free text entry is allowed for user entry of data representing an attribute.

1. An expected outcome data system storing data representing a plurality of different expected outcomes of patient care and treatment for use in providing healthcare to a patient, comprising: an acquisition processor for acquiring data representing an expected outcome of treatment associated with a medical problem, for storage in a repository; at least one repository, electrically coupled to said acquisition processor, including data representing a plurality of different expected outcomes of treatment and an individual expected outcome of treatment has an expected outcome name and is characterized by expected outcome attributes and an individual expected outcome attribute has a plurality of attribute properties determining how an expected outcome attribute is represented, said expected outcome attributes including, a focus term indicating a topic of an expected outcome, an expected outcome likelihood term indicating an assessment of likelihood of the associated corresponding expected outcome, and a client term indicating at least one target person for care; said attribute properties including, a format attribute property indicating a format constraint of said expected outcome attribute and determining formatting or presentation of said expected outcome attribute, and a content attribute property indicating a content constraint of said expected outcome attribute and determining modification of said expected outcome attribute; and a retrieval processor, electrically coupled to said repository, for retrieving data representing at least one expected outcome from said repository and communication of said expected outcome attributes to a destination system for processing data representing an expected outcome in response to said attribute properties.

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8. The computer-implemented method of claim 7 , wherein the sorting factor includes at least one of a matching degree of the candidate word and the geographic information, a utilization frequency of the candidate word, or a retrieval sorting policy.

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

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14. The non-transitory computer-readable storage medium of claim 9 wherein said operations further comprise: displaying said second data; and in response to selection of said second data via a graphical user interface, displaying information indicating said relationship between said second and third fields.

9. A non-transitory computer-readable storage medium having stored thereon, computer-executable instructions that, responsive to execution by a computing device, cause said computing device to perform operations comprising: accessing a first data from a first data source, wherein said first data is associated with a first field; accessing a second data from said first data source, wherein said second data is associated with a second field; accessing a third data from a second data source, wherein said third data is associated with a third field; determining whether said second data source comprises said first data and whether said third data comprises said first data; in response to determining that said second data source comprises said first data and said third data comprises said first data, determining a transitive relationship between said second field and said third field; and storing said relationship between said second field and said third field.

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9. The method of claim 6 , wherein the combined Gaussian Mixture Model is generated from Gaussian Mixture Models of the speech samples of that class.

6. The method of claim 5 , wherein the speaker clustering technique is based on a Gaussian Mixture Model and a Gaussian Mixture Model metric.

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12. The machine readable medium of claim 7 , wherein at least one column exists between the first column and the second column within a reading order of the document.

7. A machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying a first set of hierarchically-organized lists in a first column and a second set of hierarchically-organized lists in a second column subsequent to the first column in the document, each of the first and second sets of hierarchically-organized lists comprising one or more list items identified by a list label; determining that a first list in the first set of hierarchically-organized lists continues as a second list in the second set of hierarchically-organized lists based on an analysis of the list labels of a last list item in the first list and a first list item in the second list; and storing the first list and the second list as a single list structure associated with the document.

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11. A system comprising: a scanner configured to receive at least one tangible document; a processor configured to generate an image file corresponding to the at least one tangible document; the processor further configured to receive destination address data corresponding to a plurality of document destinations; the processor further configured to generate language selection data in accordance with received destination address data; a memory configured to store the destination address data corresponding to the plurality of document delivery destinations, store the language selection data for each of the plurality of document delivery destinations, and store web service address information corresponding to at least one cloud-based document processing service including a fee based machine document translation service; a processor configured to communicate document output data, corresponding to the electronic document and the language selection data to the at least one cloud-based document processing service via a network interface; and the processor further configured to send an instruction to the cloud-based server to distribute translated versions of character data in the image file to the plurality of document delivery destinations.

13. The system of claim 11 wherein the processor is further configured to communicate the document output data to the at least one cloud-based document processing service comprised of a file transfer protocol server.

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10. The method of claim 9, further comprising the step of (6d) immediately following step (6c), repeating steps (6a)-(6c) until (n-x) is equal to one.

11. The method of claim 10, further comprising the step of 1(b) following step (1a), determining said threshold values, and therefore a particular partition, based upon said amount of memory storage to be used.

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8. The method of claim 7 , wherein the partial list of people, animals, or creatures discussed in the story are organized by the relationships between them in the story.

7. The method of claim 1 , wherein the summary document includes a description of the partial list of people, animals, or creatures discussed in the story.

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12. A device, comprising: a transceiver; and a processor to implement a voice engine, wherein the processor is to receive an incoming call from a caller's device using the transceiver, determine a locale preference associated with the caller's device, dynamically configure the voice engine using locale settings associated with the determined locale preference, send a query message to the caller's device using the transceiver, parse a voice response from the caller to the query message using the voice engine, and process the incoming call in the called device based on the voice response.

14. The device of claim 12 , further comprising a display, wherein the processor is to process the incoming call by displaying a call back message on the display.

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5. The method of claim 1 further comprising: Blocking transmission of the document to destinations that are not associated with the recipients listed on the selected recipient list.

1. A method executed by a computer comprising a video display, of determining approval of an electronic document by one or more personnel comprising: Receiving data representing a first document type; Storing data representing a recipient list comprised of data representing members of the list; Storing a data structure representing an association between the received first document type and received the stored recipient list where said data structure is characterized by having a write access permission; Receiving a document data file, comprised of a document, from a remote computer operated by a user excluded from the write access permission; Extracting at least one data from the contents of the received document data file and using the extracted data to determine a second document type associated with the document comprising the received document data file by using text string matching; Selecting by use of the determined second document type the stored recipient list that corresponds to the first document type by determining using logic that the first document type is the same as the second document type; Retrieving the selected recipient list; Transmitting said received document data file to the members of the selected recipient list; Receiving at least one data message from at least one corresponding members of the selected recipient list, said received data message comprised of data representing the identity of the at least one of the recipients on the selected recipient list, an identity of the document comprising the received document data file and a data value representing an approval or a denial; Storing in a data record associated with the identity of the document comprising the document data file a data value representing the received data value.

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10. A non-transitory computer-readable medium including one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving an invocation of a map interface on a mobile device, the map interface having a default language; obtaining a current location of the mobile device; obtaining one or more local languages associated with the current location; determining if the one or more local languages associated with the current location correspond to the default language; and based on determining that at least one of the local languages does not correspond to the default language, displaying the map interface including a language control that indicates two or more languages for presenting information on the map interface and that can be manipulated to present information on the map interface concurrently in the two or more languages, wherein an amount of information presented in each of the two or more languages is adjusted based on the manipulation of the language control.

11. The non-transitory computer-readable medium of claim 10 , wherein the language control is a graphical object, and wherein the instructions cause the one or more processors to perform operations comprising: receiving a user input selecting the language control; and based on receiving the user input, updating the map interface to present information in one of the local languages.

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18. The computing device of claim 17 , wherein the at least one internal text assistance service is configured to automatically operate as a background process when the one or more selected text assistance services are each located at one or more servers located remotely from the computing device.

17. The computing device of claim 11 , wherein at least one of the plurality of text assistance services is internal to the application and located at the computing device and wherein at least one of the plurality of text assistance services is located at a server located remotely from the computing device.

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5. An apparatus for valuing services for search engine optimization (SEO) of a campaign term for a site, the apparatus comprising: a data store configured to store search query volume information for the campaign term; and an analyzer comprising one or more computing devices, said analyzer configured to: determine a first probability that a search query for the campaign term will result in a referral from a search engine; determine a plurality of second probabilities, wherein the second probabilities are each associated with one or more particular positions in a search engine results page; generate an organic price for each of the one of more particular positions based on the search query volume information, the first probability, a second probability for a particular position, and a monetary value for the particular position; and generate a value of the SEO services for the campaign term based on the organic prices for the one or more particular positions.

8. The apparatus of claim 5 , wherein the first probability and each of the plurality of second probabilities correspond to computed fractions based on actual data.

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15. The computer program product of claim 12 wherein the instructions are executable such that only variances for scene traits associated with scene captures corresponding to digital representations from which features in the similarity feature sets were derived are analyzed.

12. The computer program product of claim 9 wherein the instructions are executable by the processor to identify similarity feature sets from a plurality of features derived from digital representations of a plurality of image captures, the plurality of features being represented in a feature space corresponding to a recognition algorithm, and the similarity feature sets being selected based on a similarity measure.

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12. The method of claim 7 , wherein the step of generating an XML document is carried out by applying an XSLT style sheet to select only the required XML elements within the retrieved target document and place them in new XML elements as required by a retrieving application.

7. The method of claim 6 , wherein in the step of retrieving and formatting, the formatting includes extracting XML elements specific to seed topics of the identified seed documents, and wherein the step of processing each target source for each seed topic comprises the steps of: constructing a special target document link search comprising a plurality of search terms, from the XML element for the seed topic; running the special target document link search in a target source specified in the list of target sources; returning target documents matching the special target document link search, from the specified target source; performing a target document link retrieval request for each target document returned by the returning step; in response to the target document link retrieval request, retrieving a requested target document; loading the retrieved target document into an XML parser; retrieving metadata for the retrieved target document based at least in part upon the target source; storing the metadata in a data set; generating core terms from the retrieved target document, based on the metadata; locating and marking each of the search terms found within the retrieved target document; comparing the found search terms within the retrieved target document with the core terms generated therefrom; determining a score equal to the number of unique search terms that are also core terms; generating an XML document containing all the data as defined within display of the target document link in response to the user request and the score; comparing the scores returned for each retrieved target document; retaining only those retrieved target documents meeting a pre-determined score threshold; collecting all the retrieved target documents retained by the retaining step; generating a new XML element containing the target document links; and adding the new XML element back into the original seed document.

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8. The method of claim 1 , wherein rules for manipulating the message vector are substantially in the form of a context-free grammar.

1. A method performed by a communications system including a communications server in communication with one or more communications devices for automatically optimizing a message text, the method comprising: receiving on the communications server a message text comprising a plurality of words or word phrases that combine together as non-overlapping parts of the message text; treating the non-overlapping words or word phrases of the message text as multiple independent variables that are reduced to a message vector having each of the multiple independent variables as components of the message vector; automatically creating on the communications server a plurality of lexical variants of the message text, wherein the lexical variants are created by replacing a word or word phrase for each of the multiple independent variables with one or more alternate words or word phrases based on one or more value-changing rules being applied to the received word or word phrase in the message text, the lexical variants for each of the multiple independent variables being reduced to a lexical vector such that the message vector is made up of variable-sized lexical vectors; sending each of the plurality of created lexical variants of the message text to the one or more communications devices; measuring a response rate for each sent lexical variant of the message text; identifying one or more lexical variants having the best performing measured response rates for each of the lexical vectors; automatically creating on the communications server syntactical variants of the identified best performing lexical variants by rearranging the lexical vectors within the message vector based on one or more position-changing rules; sending a plurality of the syntactical variants of the identified best performing lexical variants to the one or more communications devices, wherein only grammatically-correct syntactical variants are sent; measuring a response rate for each of the sent syntactical variants; and identifying a message text having the highest measured response rate for the sent syntactical variants.

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10. An apparatus, comprising: a processor configured to: access an ontology that defines a hierarchy of a plurality of concepts at different concept domain layers and that links natural language words to the plurality of concepts at different concept domain layers; classify each of a plurality of received queries with a particular intent category based on the ontology, wherein the intent category is pre-defined by a single natural language word or phrase that summarizes in a same natural language word formation a generalized information requested by the queries and wherein the queries use different natural language formations to request different types of information summarized by the natural language word or phrase of the particular intent category; associate an intent response formulated of natural language words or phrases with the particular intent category, wherein the intent response provides a single common applicable response for the queries; access an intent hierarchy of a plurality of intent categories including the particular intent category, wherein natural language phrases representing the hierarchy of intent categories at different domain layers of the intent hierarchy have different generalities of terms than natural language phrases representing the intent categories in other domain layers of the intent hierarchy, and wherein the intent hierarchy is independent and different from a hierarchy of the ontology; determine if the particular intent category has a parent hierarchical intent category located in a higher domain layer of the intent hierarchy; and determine whether to display an additional intent response based on the parent hierarchical intent category determination.

11. The apparatus of claim 10 , wherein the processor is configured to operate an Intelligent Matching Language (IML) engine and use the ontology to identify concepts and linguistic characteristics in the queries and compare the concepts and linguistic characteristics of the queries with concepts and linguistic formations of the natural language word formations or phrases representing different intent categories.

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21. The system of claim 12 wherein the machine-learned classification component includes one of a naïve Bayes classifier, a support vector machine, a maximum entropy classifier, a decision tree classifier, a neural network classifier and a Bayesian network classifier.

12. A computer-implemented system for assessing an editorial quality of a textual unit, the system comprising: a processor; and a feature extraction component, executed by the processor, configured to generate a plurality of training-time feature vectors by automatically extracting features, which include grammar and spelling features, word n-grams and linguistic analysis features based on automatic syntactic and semantic analysis, from first versions of training documents that represent a first class of text and last versions of training documents that represent a second class of text, and configured to combine the extracted grammar and spelling features, the extracted word n-grams and the extracted linguistic analysis features to form the plurality of training-time feature vectors, and further configured to generate a run-time feature vector for the textual unit to be assessed by automatically extracting features from the textual unit; and a machine-learned classifier, trained based on the plurality of training-time feature vectors with the help of the processor, configured to evaluate the run-time feature vector and to provide an assessment of the editorial quality of the textual unit based on a degree of similarity in quality of the textual unit to either the first versions of the training documents that represent the first class of text or the last versions of the training documents that represent the second class of text, wherein the first versions of the training documents are unedited documents and wherein the last versions of the training documents are edited documents, and wherein the linguistic analysis features include at least one logical form feature, and wherein each of the plurality of training-time feature vectors includes a designator of the editorial quality of a training document, of the training documents, to which it corresponds.

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33. The method of claim 19 , wherein (d) includes: sending by the search engine to the client application instructions for displaying a first plurality of buttons selectable by a user, each button in the first plurality of buttons corresponding to one of the first suggested search query refinements and including text representative of that suggested search query refinement; and sending by the search engine to the client application instructions for displaying in the search bar, upon receiving an indication that a pointer controlled by a user is located over a button from the first plurality of buttons, a tentative refined search query corresponding to the tentative selection, the tentative refined search query including the at least one first search term and at least one tentative additional search term.

19. A method of providing to a client application running on at least one digital electronic device in communication with a search engine a plurality of user-selectable refinements to a first search query including at least one first search term, the method comprising: (a) receiving by the search engine from the client application the first search query; (b) effecting by the search engine a first search in respect of the first search query yielding first search results; (c) determining first suggested search query refinements based at least in part on an analysis of groups of related search queries being related to the first search query, each of the first suggested search query refinements corresponding to a refined search query including the at least one first search term and at least one additional search term, the analysis of groups of related search queries including: filtering the related search queries to only those identified as having provided search results which provided a user with information sought by the user; grouping the filtered related search queries into the groups based on subsequent user behaviors of the users; and determining a suggested search query refinement for each of at least some of the groups, the suggested search query refinement corresponding to a refined search query including the at least one first search term and the at least one additional search term which has been derived from one of meaningful related search queries, the one of the meaningful related search queries having been determined as being the most popular in its respective group, the at least one additional search term having being determined as being the most unique as compared with previously identified suggested search query refinements; (d) sending by the search engine to the client application the first search results, the first suggested search query refinements, and instructions for displaying (1) at least one first search result and (2) apart from a search bar, the first suggested search query refinements, the first suggested search query refinements being selectable by a user via at least one first graphical object; (e) receiving by the search engine from the client application a request to obtain the first refined search results; (f) effecting by the search engine a first refined search in respect of a first refined search query including the at least one first search term and at least one first additional search term, the first refined search yielding first refined search results; and (g) sending by the search engine to the client application the first refined search results and instructions for displaying at least one first refined search result and a visual representation of a refinement relationship between the first search query and the first refined search query.

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1. A bundle database management system for generating, storing and searching bundle data defining an association structure between individual words having relation to each other, the system comprising: a search server having a processor connected to a memory, the search server comprising: a bundle definition unit configured to define a core word, a relevant word connected to the core word, and another relevant word derived from the relevant word regarded as another core word, generate bundle data defining an nth connection relationship between the core word and the relevant word as a graph hierarchy (topology) structure, and store the generated bundle data; a description definition unit configured to store description data corresponding to the core word and relevant word; a search request receiving unit configured to receive a search request including a specific search word input by a user; a search result page generating unit configured to generate a search result page including the bundle data having a search word in its core word and the description data relating to the core word; and a search result page transmitting unit configured to transmit the search result page to the user; and a user terminal connected to the search server, the user terminal being configured to transmit the search request and receive the search result page, wherein the search server connects a first bundle with a second bundle to generate a single nth bundle data, in case the search server connects the first bundle with the second bundle having, as a core word, a same word as an arbitrary word of the first bundle to generate a connected bundle, while the search server maintains word association structures of the first and second bundles in the connected bundle, the search server integrates each same word of the first bundle and the second bundle into one word relative to the first bundle, connects bundle data of the first and second bundles with each other in such a way to add words of the second bundle to the first bundle, and integrates each description data of the first and second bundles into a description data of the integrated word, wherein the search server represents the bundle data to the user with a graph hierarchy structure that horizontally connects at least one relevant word for each core word in odd bundles (n=1, 3, 5, . . . ), and vertically connects at least one relevant word for each core word in even bundles (n=2, 4, 6, . . . ).

2. The bundle database management system of claim 1 , wherein the search server generates, stores and searches bundle data constituting n-dimensional (n>1) bundle, the n-dimensional bundle having a repetitive connection structure, comprising: a first (n=1) bundle in which at least one relevant word corresponding to a single core word is connected; a second (n=2) bundle in which an arbitrary relevant word constituting the first bundle becomes a single core word and at least one relevant word connected to the single core word is connected; and a third (n=3) bundle in which an arbitrary relevant word constituting the second bundle becomes a single core word and at least one relevant word connected to the single core word is connected.

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8. An apparatus comprising processing circuitry configured to: receive one or more initial search terms; define a concept for each initial search term by: determining if a concept associated with a respective search term has been previously defined; when a concept associated with a respective search term has been previously defined, at least initially utilizing the previously defined concept; when a concept associated with a respective search term has not been previously defined, constructing the concept based on terms related to the respective search term; and combine the concepts defined for the one or more initial search terms to generate the query; and conduct a search of one or more data sources in accordance with the query in order to identify one or more records that satisfy the query, wherein the processing circuitry is configured to construct the concept, prior to conducting the search of one or more data sources, by: identifying a plurality of terms related to the respective search term based upon string matching within sample data, wherein the string matching is performed in accordance with a predefined string matching algorithm that identifies a term to be related to the respective search term comprising a plurality of letters when the term includes a plurality of the same letters or letter sequences as the search term even though the term also exhibits one or more differences including transposed letters relative to the search term; and constructing the concept associated with the respective search term incorporating at least some of the terms related to the respective search term that were identified based upon string matching.

13. An apparatus according to claim 8 wherein in an instance in which a concept associated with a respective search term has not been previously defined, the processing circuitry is further configured to store the concept associated with the respective search term that has been constructed utilizing the string matching prior to conducting the search of the one or more data sources.

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7. The method of claim 1 , further comprising: comparing the normalized output sequence to a training sequence to determine a number of subjects, verbs, and objects overlapping between the training sequence and the normalized output sequence.

1. A method comprising: receiving at a computing node an input sequence comprising a plurality of tokens; applying by a processor of the computing node a plurality of domain-specific generators to the input sequence to generate a set of candidate replacements of the tokens of the input sequence; creating in a memory of the computing node a directed graph comprising a plurality of nodes and a plurality of edges, each node having an associated candidate replacement of the set of candidate replacements, and each edge connecting a first node to a second node, the second node being associated with a consistent follower of the candidate replacement associated with the first node, and creating the plurality of edges comprising determining syntactic consistency between each pair of the set of candidate replacements; determining by the processor a plurality of paths in the directed graph, each of the plurality of paths comprising at least one of the plurality of edges; determining by the processor a score for each of the paths; selecting by the processor a path of the plurality of paths having the highest score; applying by the processor each candidate replacement of the selected path to the input sequence to generate a normalized output sequence; and evaluating a correctness of the normalized output sequence by parsing the normalized output sequence to obtain a parse result and comparing the parse result with a gold standard that is obtained by parsing a manually normalized sequence.

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3. The method of claim 1 wherein configuring the browser application to perform a search using the detected search engine comprises: receiving user input at an input field of the browser application; generating a message to include the user input as one or more search parameters; sending the message to the detected search engine at the web site; and receiving the results of the search at the wireless communication device.

1. A method of selecting a search engine on a wireless communication device, the method comprising: establishing a communication link between a wireless communication device and a network server hosting a web site; automatically detecting, at the wireless communication device, whether the web site provides a search engine based on data received from the web site; configuring a browser application executing on the wireless communication device to perform a search using the detected search engine responsive to detecting that the web site provides the detected search engine; and displaying the results of the search at the wireless communication device; wherein automatically detecting whether the web site provides a search engine comprises determining whether the data received from the web site includes an embedded indicator, and wherein the embedded indicator comprises meta data received from the web site via the established communication link, and identifies a file that defines the search capabilities of the detected search engine.

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6. Method according to claim 5 , wherein an entry in the coding dictionary also comprises a coded value corresponding to literal coding of said value associated with this entry, and said coded value is deleted in said dictionary at the time of the coding, by means of the coded value, of the event value associated with said reference run through.

5. Method according to claim 4 , wherein the coding of the channels of values for generating at least one coded stream comprises: the running through of said channels of values so as, in said coding dictionary, to recover a coding index for each value to be coded, by means of said reference; replacement, in said coding dictionary, of at least one coding index associated with a reference run through, by a current index value, when this at least one coding index is equal to said first particular value.

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6. The method according to claim 1 , wherein said calculating the pair semantic similarity score value includes submitting a query to the at least one electronic information source and processing a query result from each electronic information source queried.

8. The method according to claim 6 , wherein query results obtained by submitting the query to the at least one electronic information source include sets of the named entities.

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6. The method of claim 1 , further comprising encrypting the embedded one-way hash, and wherein embedding a digital watermark representing the embedded one-way hash in an arbitrary digital representation comprises embedding a digital watermark representing the encrypted one-way hash.

7. The method of claim 6 , wherein encrypting the one-way hash comprises using a private key associated with the signing device.

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9. The method of claim 7 , wherein the usage cost and the preference are predetermined.

7. The method of claim 5 , wherein the prioritizing step further comprises: employing the usage cost in combination with a preference for the enforcement of the condition.

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6. The method of claim 1 , where the step of determining a score for each candidate recommendation rule comprises multiplying the margin value factor, the confidence value factor and the predetermined scoring criteria factor to form the score.

1. A computer-based method of generating recommendations for potential purchase by a customer, comprising: generating association rules from a transaction history data set; receiving a recommendation context from a customer; using the recommendation context at a computer system to identify a plurality of candidate recommendation rules from the association rules that match the recommendation context, where each candidate recommendation rule recommends at least one recommended item; determining a score for each candidate recommendation rule using a margin value factor for the recommended item, a confidence value factor for the candidate recommendation rule and a predetermined scoring criteria factor; ranking the plurality of candidate recommendation rules using the score for each candidate recommendation rule to identify at least a highest ranking candidate recommendation rule; and issuing at least the highest ranking candidate recommendation rule as a recommendation.

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11. A computer-implemented method comprising: training, using a processor, an encoder to receive an input data item and to compress the data item into an encoding comprising a plurality of numerical values, where the numerical values are grouped at least according to whether they relate to content of the input data item or style of the input data item; storing the encoding; and wherein the training comprises using: a plurality of groups of training data items grouped according to the content and where training data items within individual ones of the groups vary with respect to the style, and a training objective which takes into account the groups.

14. The method of claim 11 wherein the training comprises using the encoder to compute encodings of training data items of a group, and computing a grouping operation on the encodings.

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112. The system of claim 110 , wherein the storing of each said at least one resume is to a database.

110. A system for using a computer to identify a matching resume for a job description, comprising: means for receiving the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; means for storing the job description; means for receiving at least one resume; means for parsing each said at least one resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein said at least one skill or experience-related phrase includes the required skill or experience-related phrase for at least one of said at least one job requirement, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; means for storing each said at least one resume; means for computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and means for determining whether each said at least one resume is the matching resume that satisfies the job description.

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2. The method of claim 1 , wherein the machine readable form is a markup language.

1. A computer-implemented method, comprising: receiving user input specifying (i) search criteria for acquiring search results, (ii) a maximum payment amount for purchasing document content, and (iii) result parameters for indicating how to integrate document content embodying search results into a document; defining a machine readable form of the search criteria and the result parameters for insertion into the document; responsive to receipt of the search criteria inserted in the document in the machine readable form, using the search criteria to acquire search results; the acquired search results being associated with a purchase fee; providing, for integration into the document, document content embodying the acquired search results in accordance with the result parameters when the purchase fee of the acquired search results is less than or equal to the maximum payment amount for purchasing document content; wherein at least said receiving, defining, using, and providing are performed using one or more processors.

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15. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: receive a plurality of data items associated with imported into a social-networking system by a first user of the social-networking system, the plurality of data items being related to an entity; access one or more data stores storing a social graph of the social-networking system, the social graph comprising a plurality of nodes and a plurality of edges between nodes, the nodes comprising user nodes corresponding to users of the social-networking system and concept nodes corresponding to concepts; identify one or more nodes of the social graph that likely match the entity, each of the one or more nodes having at least one matching attribute that matches one of the plurality of data items; and update an unmatched attribute, different from the at least one matching attribute, of at least one of the identified nodes with at least one of the data items.

16. The system of claim 15 , wherein the data items comprise an email address, a name, a phone number, a user identifier of the social-networking system, a unique identifier of a communication channel or application, or a device identifier.

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16. The system of claim 1 , wherein the training history comprises at least one of a work history, a resume, and a report card.

1. An attribute building system for characters in a virtual environment comprising: a real-time monitoring component that receives a training request for a training session associated with at least one attribute and that determines whether a minimum real-time threshold value has elapsed since a previous training session in order to permit further processing of the training request, wherein the training request is submitted on behalf of a character and wherein the real-time monitoring component denies the training request when the minimum real-time threshold value has not elapsed since the previous training session and where the real-time monitoring component denies the training request by at least one of preventing participation in a competition that requires completion of said training request and not advancing to a subsequent level, wherein the real-time monitoring component determines upon receipt of the training request how many training sessions the user has participated in within a 24-hour period to determine whether the user has already participated in a permitted number of training sessions allowed within the 24-hour period, and wherein the training request is denied until the 24-hour period has elapsed by at least one of preventing participation in a competition that requires completion of said training request and not advancing to a subsequent level; a training selection component that determines a level of training for the character based at least in part on a training history of the character, and that selects the training session from among multiple different possible training sessions, based at least in part on the character's training history, and wherein said training selection component presents the training session on-screen; and a performance indicator display that presents at least one of a grade, score and final result indication of the training session on-screen, wherein successful completion of the training session facilitates advancement to more difficult levels of training sessions for the at least one attribute and wherein the at least one attribute increases social status and value of the character in the virtual environment.

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22. The bone screw of claim 20 further comprising a closure having a first guide and advancement structure for mating engagement with a second guide and advancement structure located on the receiver arms, the closure having a sloping lower surface and a partially spherical bottom surface located adjacent to the lower surface, the bottom surface being in engagement with the longitudinal connecting member during an interim adjustment stage of assembly allowing slidable movement of the insert with respect to the bone screw, at least one of the bottom surface and the lower surface being in fixed frictional engagement with the longitudinal connecting member when the closure is rotated downwardly in the receiver into a final assembled position wherein the longitudinal connecting member is in fixed frictional engagement with both the insert and the closure, the insert also being in fixed frictional engagement with the receiver.

20. A spinal bone screw pivotable with respect to a longitudinal connecting member in a single plane, the bone screw comprising: a) a shank having a thread; b) a receiver having a pair of spaced upstanding arms forming a channel for receiving the longitudinal connecting member, the receiver being integral with the shank, the receiver forming a cavity communicating with the channel, the receiver arms having opposed inner surfaces with opposed arcuate grooves, the grooves each defined in part by a radius originating at a pivot axis disposed perpendicular to and intersecting with a central axis of rotation of the shank; and c) a discrete insert located within the receiver cavity, the insert having a pair of opposed outwardly extending projections, each projection located within one of the arcuate grooves, the insert projections being slidable in the arcuate grooves, the insert having a seating surface in fixed, frictional engagement with the longitudinal connecting member.

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12. A morpheme analyzer, comprising: an information acquirement unit configured to acquire a morpheme analysis target and additional information associated with the morpheme analysis target, from search index data; a key creator configured to create a key based on the additional information in response to the information acquirement unit acquiring the additional information; and a morpheme analyzing unit configured to analyze a morpheme of the morpheme analysis target by using the key, wherein the key creator comprises: a plural key creator configured to create a plurality of keys by performing a morpheme analysis for each information included in the additional information; and a combined key creator configured to create a combined key by combining the plurality of keys, and wherein the morpheme analyzing unit comprises: a determination unit configured to determine whether the morpheme analysis target includes a partial character string corresponding to the key; and a partial character string adder configured to temporarily add the partial character string in a morpheme dictionary in response to determining that the morpheme analysis target includes the partial character string corresponding to the key.

19. The morpheme analyzer of claim 12 , wherein the morpheme analysis target comprises the key.

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9. The system of claim 1 , wherein the score associated with each term in the dictionary is derived from a frequency with which the term is used in a corpus of documents.

1. A system comprising: one or more processors; and a computer-readable storage device storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting one or more of the one or more splits according to the overall score for each split; and augmenting the query with the subterms of each selected split.

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1. A computer implemented method, performed by a computer having a processor, of disambiguating references to named entities, comprising: identifying a surface form of a named entity in a text, the surface form being an ambiguous orthographic representation of a common name for the named entity, the surface form having a corresponding surface form reference in a surface form reference database; enumerating, from the surface form reference, a plurality of different reference named entities based on the identified surface form of the named entity, wherein the surface form is associated in the surface form reference with the plurality of different reference named entities each being formed of a different set of words, and each of the different reference named entities is associated with a named entity reference, the named entity references being stored in a named entity reference database that is separate from the surface form reference database, each of the named entity references associating one of the different reference named entities to multiple entity indicators, the entity indicators including both labels applied to a respective named entity in an information resource, and context indicators applied to the respective named entity in the information resource, in which the labels comprise classifying identifiers applied to the respective named entities in the information resource; evaluating, with the processor, one or more measures of correlation between one or more of the entity indicators in the information resource for each of the identified reference named entities, and the text, the evaluation including comparisons of the text to both the labels and the context indicators; identifying, with the processor, one of the reference named entities for which the associated entity indicators have a relatively high correlation to the text; and providing a disambiguation output that indicates the identified reference named entity to be associated with the surface form of the named entity in the text.

2. The method of claim 1 , wherein the labels comprise at least one element selected from among: a tag; a category; a heading; a title; a section name; and a list name.

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11. Computer apparatus locating expertise, comprising: a user interface executable by a computer and enabling users to associate experts with respective certain objects, each object inheriting from classes in a mutable ontology-based hierarchy, the user interface resulting in respective correspondences between experts and the certain objects, wherein the mutable ontology-based hierarchy is extendable on demand such that said associating includes adding objects or classes, on demand, to the ontology-based hierarchy; a processor executable ontology-based location tool coupled to utilize the correspondences and to, based on ontology, find a candidate expert about a particular subject area, the candidate expert being in one of the correspondences associating the candidate expert with one of the certain objects as user defined through the user interface, the tool allowing the certain object associated with the candidate expert to be found from the particular subject area whether the particular subject area is a relatively specific topic or a more general area of expertise than the certain object; and an output member displaying an indication of the candidate expert.

16. Computer apparatus as claimed in claim 11 wherein the output further indicates relevancy of the candidate expert.

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14. The system of claim 13 , wherein the mapping is stored in a table.

13. The system of claim 8 , further operable to perform operations comprising: storing the mapping between entities and language scores.

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15. The non-transitory computer readable storage medium of claim 14 , wherein the processor is further configured to perform: the at least one first set of substitutions by expanding the input text string to create at least one additional input text string that includes at least one portion of the input text string and at least one additional portion not previously part of the input text string.

16. The non-transitory computer readable storage medium of claim 15 , wherein each of the at least one additional input text string contains words that are the same as the input text string except at least one word has been removed from the input text string and has been replaced by a different word in the at least one additional input text string.

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23. The system of claim 18 , the instructions further comprising instructions to cause the processor to perform operations comprising: transmitting to the electronic device for selection by the user a list of one or more character strings that are determined to be present in the third set of character string candidates.

18. A system comprising: one or more computers; one or more data storage devices coupled to the one or more computers and storing instructions, which, when executed by the processor cause the one or more computers to perform operations comprising: receiving, at a first time, a first spoken input from a user of an electronic device, the first spoken input comprising an original utterance by the user; based on the original utterance, determining a first set of character string candidates wherein each character string candidate represents the first spoken input converted to textual characters, and wherein determining the first set of character string candidates comprises using a speech recognizer to determine a first word lattice that represents the first set of character string candidates and a first set of probabilities, each probability corresponding to a character string candidate; providing for display to the user a selection of one or more of the character string candidates in response to receiving the first spoken input; receiving, at a second time, a second spoken input from the user; determining that the second spoken input is a repeat utterance of the original utterance; based on determining that the second spoken input is a repeat utterance of the original utterance, and using the original utterance and the repeat utterance, determining a second set of character string candidates, wherein determining the second set of character string candidates using the original utterance and the repeat utterance comprises: using the speech recognizer and the first word lattice as a language model to determine a second word lattice that represents the second set of character string candidates and a second set of probabilities, each probability corresponding to a character string candidate of the second set of character string candidates; determining an intersection or union of the first word lattice and the second word lattice and, for each character string candidate included in the intersection or union, determining a combined probability based on the probabilities from the first set of probabilities and the second set of probabilities that correspond to the character string candidate; and determining a third set of character string candidates based on the intersection or union and the determined combined probabilities.

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4. The method of claim 3 , wherein operably coupling the identified entity with the selected contextually relevant action comprises replacing the entity within the visual communication with the selected contextually relevant action.

3. The method of claim 2 , further comprising operably coupling the identified entity with the selected contextually relevant action.

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3. The system of claim 1 , wherein the math engine analyzes the input in the document and generates a list of possible math operations that can be performed on the input.

1. A computer-implemented word processing system, comprising: a computer; a word processing application of the computer for receiving and rendering math-based input in a word processing document; and a math component that interfaces to the word processing application and includes a math engine, the math component converts the math-based input into a math markup language for processing by the math engine, the math engine analyzes the math-based input and returns a list of operations from which an operation is selected, the math engine performs the selected operation on the math-based input and inserts a result to the word processing document.

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10. The method of controlling a control device described in claim 7 , wherein: the universal character codes and font data stored in the font groups can be edited.

7. A method of controlling a control device that controls a recording device that records on a recording medium and stores a plurality of font groups storing font data for a plurality of characters, the control method comprising steps of: creating or updating a character code conversion table that correlates each of a plurality of universal character codes that are rendered in a single font group and are specified from the control device side to information identifying a font group on the recording device side containing font data corresponding to the universal character code and information denoting the storage address of the font data in the font group; and when a recording job instructing to record a character is asserted, converting the universal character code contained in the recording job to a font data address including information identifying a font group containing font data corresponding to the universal character code, and information denoting the address of the font data in the font group based on the character code conversion table.

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21. The system of claim 19 , where the one or more computer devices further comprise: means for adjusting quality scores associated with the product reviews, or the commercial documents or sites, that are related to the one of the advertisements when the received search query is identified as commercial in nature.

19. The system of claim 15 , where one or more advertisements are associated with the selected search result document, and where the one or more computer devices further comprise: means for receiving a request to save one of the advertisements; means for saving the one of the advertisements in response to the request to save the one of the advertisements; and means for identifying the received search query as commercial in nature based on saving the one of the advertisements.

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13. A system comprising: a display; a user interface, including a control device and a microphone; and processor electronics configured to perform operations comprising: displaying a text script on a display; receiving input from the control device positioning a plurality of visual images associated with a plurality of media events adjacent to the text script in a scrollable portion of the display to establish a spatial relationship between the plurality of visual images and the text script, such that the position of each visual image corresponds to one or more words in the text script with which the associated media event is to begin during a presentation; scrolling the text script on the display while maintaining the spatial relationship between the text script and the visual images; causing the media events associated with the visual images to begin approximately upon the corresponding one or more words of the text script scrolling through a predetermined region of the display during the presentation; and generating the presentation, including audio information corresponding to the user speaking at least a portion of the text script.

19. The system of claim 13 , further comprising: a computer-readable medium configured to store a content folder including one or more of the plurality of media events.

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13. The testing harness of claim 10 , wherein the translator comprises an abstract syntax tree translator, mapping an abstract syntax tree of the TTCN-3 files into an abstract syntax tree of SystemVerilog files.

10. A testing harness comprising: a translator stored in a memory to map Testing and Test Control Notation, Version 3 (TTCN-3) language to a SystemVerilog test bench; a SystemVerilog syntax compiler and a simulator database, including the mapped TTCN-3 language; and a run time system using the SystemVerilog test bench with the simulator database including the mapped TTCN-3 language.

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2. The method of claim 1 , wherein the translation memory source text providing the exact match includes at least two assigned context hash codes.

1. A method for determining an in context exact (ICE) match from context matching levels of a plurality of translation memory source texts stored in a translation memory to a lookup segment to be translated, the method comprising: assigning a usage context hash code to the lookup segment and an asset hash code to the lookup segment; determining any exact matches for the lookup segment and the plurality of translation memory source texts; calculating for each exact match a context matching level based on: a match between the usage context hash code for the lookup segment and a usage context hash code assigned to a segment of a translation memory source text, and a match between the asset hash code for the lookup segment and an asset context hash assigned to the segment of the translation memory source text; and determining, for each exact match if the segment of the translation memory source text providing the exact match is an ICE match for the lookup segment based on the calculated context matching level.

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5. The system of claim 2 , wherein determining an insertion score comprises: determining central tendency score from relevance scores of images that are to be displayed in the image display environment, each relevance score being a measure of relevance of a corresponding image to the search query.

2. The system of claim 1 , wherein the data processing apparatus instructions cause the data processing apparatus to perform operations comprising: determining an image intent score for the search query; and generating an image insertion request only when the image intent score exceeds an intent threshold.

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23. The computer program product of claim 19 , wherein the physical markup representation is a paginated representation including pages each having a respective physical width and a respective physical height.

24. The computer program product of claim 23 , wherein the target size includes a target height.

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12. The method of claim 1 , wherein said identifying includes using face recognition to identify said face-specific set of video frames for said at least one detected human face.

1. A method for processing video data, comprising: detecting human faces in a plurality of video frames in said video data using a processor; for at least one detected human face, identifying a face-specific set of video frames using said processor, irrespective of whether said detected human face is present in said face-specific set of video frames in a substantially temporally continuous manner; grouping video frames in said face-specific set of video frames into a plurality of face tracks using said processor, wherein each face track contains corresponding one or more video frames having at least a substantial temporal continuity therebetween; using said processor, merging two or more of said plurality of face tracks that are disjoint in time using a face recognition method based on a Bayesian Network based classifier, wherein the Bayesian Network based classifier is constructed based on a ratio of a plurality of Bayesian networks and each of said Bayesian networks is a probability distribution representation derived from dependencies among video input variables that statistically depend upon each other; and enabling a user to view on an electronic display face-specific video segments of said at least one detected human face in said video data based on said merging of temporally disjoint face tracks.

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26. The system of claim 25 , wherein receiving the third input for manually editing the avatar element comprises: receiving a touch selection of the zoomed avatar element; and after receiving the touch selection, receiving a gesture selection of the zoomed avatar element.

27. The system of claim 26 , the operations further comprising resizing the zoomed avatar element in response to the touch selection and the gesture selection.

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1. A method of presenting documents to a user, comprising: a. assigning relevance scores to a plurality of the documents, by a computer programmed to compute relevance scores based on a relevance model using one or more user input events, wherein at least one of the one or more user input events is an active selection of a user input feature about at least one document and is received outside a context of a presentation of search results of a search, the one or more user input events comprising input about the at least one document from at least one user; and b. presenting the documents to the user according to the relevance scores.

4. The method of claim 1 , further comprising, after presenting the documents to the user, receiving user input about at least one of the documents presented to the user, the user input comprising a user input event.

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11. The method of claim 1 , wherein the voice command is verified by characteristics of the user's voice.

1. A method of interacting with a mobile communication facility comprising: generating a plurality of clipped versions of a voice command, wherein the plurality of the clipped versions of the voice command is simulated from a complete voice command; receiving a switch activation from a user to initiate a speech recognition recording session, wherein the speech recognition recording session comprises the voice command from the user followed by speech to be recognized from the user; recording the speech recognition recording session using a mobile communication facility resident capture facility; detecting a first portion of the voice command as clipped and a second portion of the voice command as a portion of the command that was not clipped off during the speech recognition recording session, wherein the first portion is determined as being clipped as a result of the user providing the command before the mobile communication facility resident capture facility was ready to receive is based in part on the plurality of clipped versions of the voice command; recognizing the first portion of the voice command as an indication that user speech for recognition will begin following the end of the first portion of the voice command; recognizing the recorded speech in the second portion of the voice command using a speech recognition facility to produce an external output; and using the selected output to perform a function on the mobile communication facility.

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17. A computer readable storage device storing a software program to cause a computing device to: determine a user context based on a tunable parameter; determine a first aspect of the user context and a second aspect of the user context, wherein the first aspect of the user context includes data indicative of text being accessed by a user and the second aspect of the user context includes data indicative of at least one user task from a plurality of user tasks, wherein the at least one user task is determined based upon the user context of the user's interaction with one or more software applications; formulate a first query and a second query based on the first aspect of the user context, the first query and the second query being different than the user context; submit the first query to a first search engine; receive a first plurality of search results from the first search engine, the first plurality of search results being based on the first query; submit the second query to a second different search engine; receive a second plurality of search results from the second different search engine, the second plurality of search results being based on the second query; determine a first plurality of scores associated with the first plurality of search results at least in part by comparing data indicative of the first plurality of search results to data indicative of the first aspect of the user context; determine a second plurality of scores associated with the second plurality of search results at least in part by comparing data indicative of the second plurality of search results to the data indicative of the first aspect of the user context; and display a subset of the plurality of search results on a client device, wherein at least one of the first plurality of search results is filtered from being displayed to the user based on at least a portion of the first plurality of scores, and wherein at least one of the second plurality of search results is filtered from being displayed to the user based on at least a portion of the second plurality of scores.

22. The computer readable storage device of claim 17 , wherein the user context is based on (a) a style of the at least one predetermined word in the text being accessed by the user and (b) a type associated with a computer application.

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8. The method of claim 7 , transitioning the query comprising: identifying at least one phoneme in the query according to an acoustic model; identifying at least one query term corresponding to the at least one phoneme according to a pronunciation model; and generating a recognition result from the at least one query term according to a vocabulary of an n-gram language model.

7. The method of claim 2 : at least one input component of the device comprising an audio input component; the query comprising an audio query received through an audio input component; at least one search engine comprising a textual search engine configured to handle textual queries; and the instructions configured to, after receiving the query through the audio input component and before executing the query on the textual search engine, transitioning the audio query to a textual query.

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4. The method of claim 1 , wherein the number and arrangement of links corresponding to popular web pages and other content items included in the subset of the search result listing are selected through ranking.

1. A method for enhancing search results, comprising: receiving a search query from a user; identifying web pages relevant to the search query; identifying a subset of the relevant web pages as popular web pages; generating a first search result page that simultaneously displays: A) a search result listing that displays a respective link to each of the relevant web pages, wherein the respective links to the relevant web pages include respective links to the subset of the relevant web pages identified as popular web pages, and B) a subset of the search result listing separate from the search result listing, wherein the subset of the search result listing includes a respective link to each of the popular web pages in the subset of the relevant web pages, including a displayed first link to a first of the popular web pages and a displayed second link to a second of the popular web pages; and upon receiving a request from the user to select the first link to the first popular web page in the subset of the search result listing and navigate to the first popular web page, generating a second search result page having both content of the first popular web page and the subset of the search result listing of the first search result page, wherein the subset of the search result listing continues to display the subset of the search result listing from the original search query received from the user, including the first link to the first popular web page and the second link to the second popular web page, wherein the first link to the first popular web page and the second link to the second popular web page persist from the first search result page to the second search result page.

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43. A method of processing documents associated with a deposit transaction of a customer, the method comprising: receiving in a document processing system a data file associated with the deposit transaction from a network, the data file including a plurality of records, each record including image data that is reproducible as a visually readable image of at least a portion of a respective document associated with the deposit transaction, a respective value, and respective identifying information; determining if one or more of the plurality of records is a suspect record based on a comparison of the respective identifying information with suspect information stored in the document processing system; determining that one of the records included in the data file associated with the deposit transaction is a suspect record; and in response to the determination of the suspect record, automatically making a suspect notice electronically available, the suspect notice including information indicative of the determination of the suspect record associated with the deposit transaction.

44. The method of claim 43 , wherein the act of automatically making the suspect notice electronically available comprises posting the suspect notice to a website accessible by the customer.

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37. The improvement of claim 23 , wherein the closure further comprises an inner threaded bore and a set screw having an outer thread for mating with the closure at the inner threaded bore.

39. The improvement of claim 37 , wherein the closure has a first top surface with a first drive feature and the set screw has a second central portion with a second drive feature.

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2. The method according to claim 1 , wherein said printing comprises printing, in said one or more non-grayscale colors, a page which includes said figure, wherein the page which includes said figure is part of the digital document.

1. A method comprising using at least one hardware processor for: analyzing text in a digital document, to identify a text segment referring to a figure of the digital document; mapping said text segment to said figure; identifying, in said text segment, reference to one or more non-grayscale colors of said figure, to determine a level of importance of said one or more non-grayscale colors to legibility of said figure; and printing said digital document in accordance with the level of importance.

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1. A method for executing a first serial language code in a processor, comprising: parsing a first serial language code having an embedded second serial language code until a segment of the second serial language code is encountered, the second serial language code being executable to generate additional first serial language code; storing parsing state information associated with the parsing of the first serial language code upon encountering the segment of the second serial language code in a memory of a computing device; continuing to parse the first serial language code; executing the encountered segment of the second serial language code to generate the additional first serial language code, wherein the encountered segment of the second serial language code is executed concurrent with the continued parsing of the first serial language code; inserting the additional first serial language code at a point in the first serial language code identified by the stored parsing state information; determining whether the additional first serial language code generated from the execution of the encountered segment of the second serial language code is well formed; and re-initiating parsing of the first serial language code and the additional first serial language code from the point in the first serial language code identified by the stored parsing state information in response to determining that the additional first serial language code is not well formed.

2. The method of claim 1 , further comprising: packaging the second serial language code and the parsing state information in an execution state package upon encountering the segment of second serial language code; and storing the execution state package in a memory of a computing device.

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14. An electronic device configured to perform a gesture recognition function, the electronic device comprising: a plurality of gesture recognition systems comprising: an image-based gesture recognition system configured to receive first gesturing input using an imager to perform the gesture recognition function; and a non-image-based gesture recognition system configured to receive second gesturing input without using an imager to perform the gesture recognition function; a processing element configured to select an active gesture recognition system from the plurality of gesture recognition systems, wherein the selecting is based on a context of operation for the electronic device that affects the gesture recognition function performed by at least one of the gesture recognition systems; and a photosensor configured to determine an ambient light level as the context of operation, wherein the processing element is configured to select the active gesture recognition system from the plurality of gesture recognition systems based on the ambient light level.

17. The electronic device of claim 14 further comprising at least one of an accelerometer or a vibration transducer configured to determine a level of vibration as the context of operation, wherein the processing element is configured to select: the non-image-based gesture recognition system as the active gesture recognition system when the level of vibration is above a first threshold level of vibration; or the image-based gesture recognition system as the active gesture recognition system when the level of vibration is below a second threshold level of vibration.

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20. A computer program product, encoded on a computer-readable medium, operable to cause data processing apparatus to perform operations comprising: searching for one or more parameter values associated with an n-gram, including: receiving the n-gram; identifying a fingerprint corresponding to the received n-gram; performing a composite hash on the n-gram; identifying array locations corresponding to the composite hash values; and combining the values of the array locations with the fingerprint value to identify one or more n-gram parameter values.

23. The computer program product of claim 20 , further operable to perform operations comprising: reducing an error rate including: performing a search for an n−1-gram as a lesser included n-gram of the received n-gram; and when one or more parameter values for the n−1-gram is not identified, truncating the search for the received n-gram to a lesser included n-gram.

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26. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a pair of words; generating a word-form score for the pair of words based on a consistency of the pair of words with word-form rules, wherein a word-form rule indicates how words with a common portion can vary; and determining that the pair of words is a synonym pair based at least on the generated word-form score; and generating an alternative search query for a search query that includes one of the words of the pair of words using another word of the pair of words.

27. The computer program product of claim 26 , wherein the operations further comprise: receiving one or more synonyms; and generating one or more word-form rules from the synonyms.

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13. The system of claim 1 , wherein said media products are personalized email greeting cards.

1. A Web-based system for accessing development components, which include an online video clip library and an online music clip library, and enabling online production of custom-integrated media products, said system comprising at least one computer server connected to a computer network, said server including: an upload engine capable of receiving over the computer network a plurality of video and music clips from a plurality of content provider users; a storage engine capable of storing the uploaded plurality of video and music clips provided by said plurality of content provider users in a database and media content storage devices as libraries; a search engine capable of indexing the database and media content storage devices that store the libraries of uploaded video and music clips; a user interface engine capable of providing over the computer network to a plurality of producer users interactive Web formatting screens allowing said producer users to select from said libraries a plurality of video and music clips from among any of the video and music clips uploaded by said plurality of content provider users; and a mixer module capable of allowing said producer users to edit and play said selected video and music clips, wherein said mixer module supports mixing together a plurality of said uploaded video and music clips, such that producer users are able to self-produce video advertisement templates each comprising static content and at least one placeholder, said mixer module further capable of allowing advertiser users to customize said video advertisement templates by uploading a list, such that advertiser users are able to automatically self-produce a set of different customized video advertisements based on an advertisement template, in which the at least one placeholder for each customized video advertisement contains a different item from the list, wherein said mixer module is capable of arranging said video advertisement templates and customized video advertisements as respective XML files on a server, said XML files being accessible by a plurality of users using respective browser applications, such that upon updating an XML file representing a video advertisement template or a customized video advertisement, the updated video advertisement template or customized video advertisement is made accessible to users accessing the updated XML file; said system further comprising a Web application for encoding and formatting video advertisements in particular formats.

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8. The structured document processing device according to claim 2 , further comprising: difference amount calculating means configured to increase a difference amount between a content of the new structured document and a content of the source structured document by one unit, each time it is decided that a result of performing the matching check is NO; and replacing means configured to replace a pre-replaced source structured document with a post- replaced source structured document and continuing the same process, which has been performed on the new structured document and the pre-replaced source structured document, on the new structured document and the post-replaced source structured document from its beginning after the difference exceeds a threshold.

2. A structured-document processing device implemented on a computer, wherein the computer is configured as the structured-document processing device, comprising: storage means configured to store contents of both (i) a source structured document which has been parsed and (ii) a result of parsing structured partitions of the source structured document; matching check means configured to perform a matching check on whether or not source contents of the source structured document and contents of a new structured document match each other by comparing one of the structured partitions of the source structured document and a corresponding structured partition of the new structured document one by one in order starting from a head of both the source and new structured documents; classification means configured to classify each of the structured partitions of the new structured document into two categories, that is a first-class structured partition and a second- class structured partition, based on a result of performing the matching check concerning each of the structured partitions; parsing means configured to parse a structured partition which the classification means has classified as a second-class structured partition and generating a new parsed partition as a result of parsing the structured partition; and posting means configured to post to an application program (i) an event concerning each of the structured partitions in order from a structured partition in the head of the new structured document to a structured partition in a tail of the new structured document, (ii) an event concerning a source parsed partition of the source structured document corresponding to each of the structured partitions of the new structured document as a result of parsing the structured partition if the structured partition is a first-class structured partition, and (iii) an event concerning a new parsed partition concerning a structured partition as a result of parsing the structured partition if the structured partition is a second-class structured partition.

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15. The article of manufacture of claim 14 wherein the first document comprises a plurality of elements.

14. An article of manufacture comprising: (A) a content management system comprising: a review activity mechanism that monitors review activity of at least one user in reviewing a first document that is a first instance of a schema that defines elements and attributes for documents that are instances of the schema, annotates the schema to reflect the review activity of the at least one user in reviewing the first document, and provides in a display of a second document that is a second instance of the schema at least one indication of the review activity of the at least one user in reviewing the first document according to the annotated schema; and (B) recordable media bearing the content management system.

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15. A system for automatically generating systematic reviews of received documents in a field of literature, comprising a processor programmed to perform the following steps: constructing associative networks of documents within the received documents; decomposing the associative networks into clusters of topics or fields; performing information extraction within the received documents to provide tagged text; constructing semantic structures of concepts and/or assertions extracted from the tagged text; generating citation-based and content-based summaries of the clusters of topics or fields and the semantic and ontological structures; and generating structured narratives of the clusters of topics or fields and the summaries of the generated semantic structures wherein the programmed processor constructs associative networks of documents within the received documents by selecting node types and link types for each time slice of the received documents, computing similarity or proximity scores for the nodes, constructing matrices of the node information, and merging respective matrices from different time slices.

22. The system of claim 15 , wherein the programmed processor generates structured narratives of the clusters of fields or topics and the summaries of the generated semantic structures by selecting a narrative template from a set of predefined templates.

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15. An apparatus for concept identification in software, comprising: a processing device; a graphical user interface and user input device operatively connected to the processing device; and a storage component, operatively connected to the processing device, having stored thereon executable instructions that, when executed by the processing device, cause the processing device to: display, via the graphical user interface, concept specification prompts; receive, via the at least one user input device based on the concept specification prompts, concept specification information corresponding to a concept, the concept comprising at least one of code abstraction, design abstraction, and architectural abstraction, the concept specification information comprising a code pattern illustrating the concept, and the code pattern including a predetermined length of source code or object code that defines the concept; parse the code pattern to identify at least one token; generate at least one rule based on the at least one token and according to a mapping; identify occurrence of the concept in a code listing based on the at least one rule; and display, via the graphical user interface, information regarding the occurrence of the concept in the code listing as an indication of quality of the code listing, the displayed information comprising at least one of information concerning presence of the concept in the code listing and information concerning absence of the concept in the code listing.

16. The apparatus of claim 15 , wherein those instructions that cause the processing device to receive the concept specification information are further operative to receive an indication of an abstraction level applicable to the concept.

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1. A computer system for diagramming comprising: a computer generated diagram graphically representing a subject model, the subject model having model elements and the diagram being formed of notational elements corresponding to the model elements of the subject model; and a view generator responsive to primary edits to the subject model, the view generator generating a non-persistent view representative of the primary edit for secondary edits to the diagram, the non-persistent view being contained in a non-persistent container element, that is associated with but detached from a persistent container element of the diagram, and the view generator generating the non-persistent view in a manner such that the diagram and the non-persistent view are displayed to a user as if the non-persistent view were a persistent part of the diagram by displaying both attributes of the persistent and non-persistent container elements of the diagram; wherein a notation meta-model persists the notational elements with references to the corresponding model elements, the notation meta-model allowing notational elements to be recreated and changed dynamically in a manner free of replacing original notational elements in the diagram by mapping from which persistent and non-persistent container elements to retrieve said attributes, and wherein mapping the attributes of the non-persistent container element to the persistent container element transforms the non-persistent view into a persistent view persisting with the diagram.

9. A computer system as claimed in claim 1 wherein the diagram is a state diagram of a state machine with the subject model and the primary edit is addition of a new state; and the view generator generates the non-persistent view instead of automatically adding a state view corresponding to the new state.

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1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to create a service instance based on a provider function for calculating a service order, the creating comprising: defining a structured set of metadata for the provider function, the structured set of metadata defining one or more variants that select a fulfillment pattern, the fulfillment pattern comprising a process flow declaration that includes one or more fulfillment functions of the fulfillment pattern and sets dependencies between pairs of fulfillment functions that impose an ordered priority of execution of the one or more fulfillment functions, and including metadata retrieved from a technical catalog; defining a transformation sequence, based on the metadata for the provider function, comprising customizable process logic for the provider function, wherein the customizable process logic is structured within one or more stages configured to generate the service order; dynamically generating a runtime process flow for the provider function based on the metadata and the transformation sequence, the dynamically generating including selecting at least one fulfillment pattern from the one or more fulfillment patterns based on at least one entity from one or more entities comprised in the metadata and at least one discriminator from one or more discriminators comprised in the metadata; and generating a fulfillment flow based on the at least one selected fulfillment pattern; calculating the service order with customer-facing service order line objects and referring to an entity as its subject based on the fulfillment flow, wherein the metadata comprises the entity that defines a capability that is provided, and wherein the entity comprises one or more child entities; designing a configuration for the entity, wherein the configuration comprises the entity, the one or more child entities, and one or more relationships between the entity and the one or more child entities; creating, for each child entity, a design context comprising a reference to both a parent entity and one or more sub-components, wherein each child entity is a subject for the design context and wherein each subject comprises either a customer order, service order or a technical order; and designing, for each child entity, an instance of the child entity using a corresponding design context.

9. The non-transitory computer-readable medium of claim 1 , wherein at least one child entity of the one or more child entities is a parent of another child entity of the one or more child entities.

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1. A method comprising: via computer processor hardware, performing operations of: parsing an utterance to identify syntactic relationships amongst words in the utterance; creating sets of words from the utterance based on the syntactic relationships; mapping each set of the sets of words to a respective candidate intent value to produce a list of candidate intent values for the utterance; ranking the candidate intent values in the list based on usage of the sets of words in previously received utterances; selecting, from the list, a candidate intent value as being representative of an intent of the utterance; detecting that the selected candidate intent value maps to multiple possible labels in a label listing, an entry in the label listing indicating that the selected candidate intent value maps to the multiple possible labels, the multiple possible labels including a majority label representing a first classification and a minority label representing a second classification; selecting the majority label; assigning the selected majority label to the utterance to indicate that the utterance falls into the first classification, the selected majority label representative of a dominant subject matter likely intended by the utterance.

3. The method as in claim 1 , wherein creating the sets of words in the utterance includes: producing a first set of words to include a first word and a second word in the utterance, the first word being syntactically related to the second word as indicated by the identified syntactic relationships; and producing a second set of words to include a third word and a fourth word in the utterance, the third word being syntactically related to the fourth word as indicated by the identified syntactic relationships.

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2. The apparatus of claim 1 , wherein the processor further issues instructions to filter the received user media program selection message when the received user media program selection message is determined not to indicate a user watching event.

1. A media content based exposure measuring apparatus, comprising: a memory; a processor disposed in communication with said memory, and configured to issue a plurality of processing instructions stored in the memory, wherein the processor issues instructions to: obtain program listing data including a plurality of marked tags representing a plurality of marked media segments; provide the obtained program listing data including the plurality of marked media tags representing the plurality of marked media segments to a user mobile device communicatively coupled to a wireless communication component; receive a user media program selection message from the user mobile device, wherein the user mobile device transmits a media play selection indication to a media player component, wherein the user media program selection message and the media play selection indication comprise the same user selected media; receive an atmospherics data package from the user mobile device; obtain an atmospherics data artifact from the atmospherics data package; extract user instant activities information based on analysis of the atmospherics data artifact; determine whether the received user media program selection message indicates a user media participation event; generate a user viewing status indication based on the user instant activities information; incorporate the user viewing status indication into viewer measurement data of the user selected channel; and retrieve a media tag associated with the user selected media program from the program listing data, the media tag indicating a timestamp when a media play segment embedded in a user selected media program is to be experienced by the user via the media player component and a media referenced item featured in the media segment; determine the timestamp of the media tag with the user selected media when the received user media program selection message is determined to indicate the user media participation event; generate a deliverable mobile media segment featuring the media referenced item featured in the media play segment; and provide the generated deliverable mobile media segment to the user mobile device in synchronization with the timestamp when the media play segment featuring the media referenced item is experienced on the media play component.

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5. The computer-implemented method of claim 1 , wherein the remediation strategy for inducing the user to speak the particular term using an age-appropriate pronunciation involves prompting the user to speak the particular term again.

1. A computer-implemented method comprising: receiving audio data corresponding to a user speaking a particular term; generating, by an automated speech recognizer, a phonetic representation of the particular term based on the audio data; accessing a database of canonical pronunciations of terms that are used by the automated speech recognizer in transcribing utterances, wherein one or more of the canonical pronunciations are associated with an indication of age-appropriateness; determining that, in the database of canonical pronunciations of terms that are used by the automated speech recognizer in transcribing utterances, the phonetic representation matches a particular canonical pronunciation of a particular term, wherein the particular canonical pronunciation is associated with the indication of age-appropriateness; obtaining data that indicates an age of the user; determining, based on a comparison of (i) the data that indicates the age of the user and (ii) indication of age-appropriateness that is associated with the particular canonical pronunciation of the particular term, that the pronunciation of the particular term by the user is not age-appropriate; based on determining that the pronunciation of the particular term by the user is not age appropriate, selecting a remediation strategy for inducing the user to speak the particular term using an age-appropriate pronunciation, and providing, for output, a transcription of the audio data, or of subsequently received audio data, that is generated by the automated speech recognizer.

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31. The system of claim 23 , wherein the snippets comprise a set of terms on either side of an occurrence of a word of interest within the content.

23. A system, comprising: a processor; a memory comprising computer code executed using the processor, in which a computer code implements: generating a dashboard user interface that displays analysis results identified from within one or more social media sources, the dashboard user interface comprising one or more selectable user interface components corresponding to different subsets of sentiment analysis results, the one or more selectable user interface components being selected from the dashboard user interface to perform analysis on a subset of the sentiment analysis results, results from performing the analysis on the subset of the sentiment analysis results being displayed within a results user interface, generating the results user interface that displays the analysis results performed on one or more social media data sources pertaining to a selected subset of sentiment analysis results from the dashboard user interface, the results user interface comprising: (a) a first interface portion comprising a list of one or more analysis results derived from a selection of the selected subset of the sentiment analysis results from among the different subsets of sentiment analysis results in the dashboard user interface, an individual analysis result from among the one or more analysis results being selectable to display a set of terms associated with a selected individual analysis result in a second interface portion, (b) the second interface portion comprising the set of terms, the set of terms associated with the selected individual analysis result from the first interface portion, and (c) a third interface portion comprising snippets corresponding to the social media data sources associated with the selected individual analysis result from the first interface portion; receiving the selection of the one or more selectable user interface components in the first user interface to perform the analysis on the subset of the sentiment analysis results; performing a search of content from the social media sources pertaining to the selected subset of the sentiment analysis results corresponding to a selected selectable user interface component to generate the list of the one or more analysis results; and performing the analysis to identify two or more themes from the sentiment analysis results of the search of the content from the social media sources by: receiving a random sample of messages from the content; generating snippets obtained from the search by analyzing the random sample of messages to identify the two or more themes, wherein an individual theme comprises a set of the snippets having vector values that are clustered together, vectorizing the snippets by applying a singular value decomposition (SVD) to represent the snippets as vectors, clustering the snippets by performing vector comparisons between the snippets, and generating the two or more themes based at least in part on clustered snippets; and displaying the results of the analysis in a first interface portion of the results user interface, a selection of the individual analysis result from among the results of the analysis in the first interface portion of the results user interface generating: (a) the set of terms associated with the selected individual analysis for display in the second interface portion of the results user interface, and (b) the snippets corresponding to the social media data sources associated with the selected individual analysis result for display in the first interface portion of the results user interface.

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7. A system, as in claim 6, where the query is a natural language query.

6. A system, as in claim 5, where the presentation is a schema display on a graphical user interface.

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14. The method of claim 1 wherein the automatic notification includes a first component comprising a graphical thermometer and a second component comprising a priority list, wherein the graphical thermometer provides a visual indication with a plurality of colors of how qualified the job seeker is for the selected job opening based on the one or more electronic questionnaires completed on the application on the target network device by the job seeker and wherein the priority lists a list of all job seeking candidates in a priority order for the selected job opening.

1. A method for career matching assessment, comprising: accessing on an application on a target network device with one or more processors from a server network device with one or more processors via a communications network, one or more electronic questionnaires created for a selected job opening for a first job seeker, the one or more electronic questionnaires including: (1) a plurality of non-self assessment questions for the first job seeker that are answered by the seekers as if the first job seeker were actually an employer offering the selected job opening instead of the job seeker seeking the selected job opening and (2) a plurality of general questions that focus on different aspects of a working environment and working relationships and do not access any underlying personality traits of the first job seekers; sending the one or more electronic questionnaires completed on the application on the target network device for the first job seeker to the server network device via the communications network for the selected job opening; processing the completed one or more electronic questionnaires from first job seeker on the server network device to create a first electronic profile for the first job seeker, wherein the created first electronic profile measures attributes of models of working environments, problem solving, communication and inter-personal skills related to job performance and job satisfaction for the first job seeker for the selected job opening; invoking a matching process to assess an amount of overlap between the created first electronic profile for the first job seeker and a plurality of other electronic profiles of created by a plurality of other job seekers and the employer profile created by an employer for the selected job opening; creating an electronic priority list from the assessed amount of overlap to list job seeker candidates in rank order for the selected job opening most desirable to the employer, wherein the priority list includes a prediction of job performance, job satisfaction and long term job retention for the job seeker candidates for the selected job opening for the employer; sending an automatic notification from the server network device to the application on the target network device via the communications network to indicate a priority ranking for the selected job opening for the job seeker; and displaying with the application on the target network device the automatic notification to indicate a priority ranking for the selected job opening for the job seeker.

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6. The method of claim 1 , further comprising storing the current context state in a prediction database.

7. The method of claim 6 , wherein the prediction database comprises an aggregation of a plurality of context states, wherein each of the plurality of context states is associated with a user.

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31. A non-volatile computer readable storage medium for associating words and word strings in a language comprising: providing a collection of documents, wherein said collection includes at least one document; receiving from a user a word or word string query to be analyzed; searching said collection of documents or the query to be analyzed and returning documents containing the query to be analyzed; determining a user-defined number of words or word strings or both to the left and right of the query in said returned documents containing the query to be analyzed; returning a list with an entry or plurality of entries, wherein said entry or said plurality of entries contain said determined words or word strings to the left and right of the query in said returned documents; searching said collection of documents for said entry or plurality of entries in said returned list and returning second documents containing said entry or one of said plurality of entries in said returned list; and determining a user defined number of words or word strings that appear between words or word strings to the left and right of said query in said second returned documents; returning a list of words and word strings or both that occur between said determined words and word strings to the left and right of said query in said second returned documents; and ranking said returned list of words or word strings based on the number of different words or word strings to the left and right of said query that each returned word or word string appears between in said second returned documents.

32. The non-volatile computer storage medium of claim 31 , wherein the results are used to aid a machine translation application.

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1. A method of building an index of web pages, the method comprising: accessing a set of URLs collected by crawling the Internet; accessing a list of URLs collected from one or more sources that collect clicks of URLs by users; for each URL in the set of URLs, for a given URL: computing a measure of likelihood that the given URL will be searched by a user in the future based on whether the URL has been clicked by a user, storing the given URL and its measure, selecting a subset of the URLs based on their respective stored measures, where some of the URLs in the set of URLs are omitted from the subset based on the measures of the omitted URLs; generating a first index of the web pages pointed to by the URLs in the subset of URLs, the first index not including the omitted URLs, the first index comprising a mapping between contents of the web pages and the URLs of the web pages, and generating a second index of the web pages pointed to by the URLs omitted from the subset, the second index not including the URLs in the first index; and using the index by a search engine to search for search results for arbitrary search queries submitted by users, wherein when the first index does not satisfy a given query, using the second index to attempt to satisfy the given query.

6. A method according to claim 1 , further comprising accessing information comprising measures of popularity of respective domains or web sites, wherein the computing the measure of the given URL is further based on a measure of popularity of a domain or web site containing a web paged identified by the given URL.

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3. The method recited in claim 1 , further comprising associating metadata with the one or more objects.

1. A method for providing data based on object relevance, comprising: executing instructions stored in memory via a processor of a computing system for: receiving one or more query terms from a user; determining a preliminary relevance of one or more objects associated with an enterprise system based on the query terms; assigning at least one rating to the one or more objects based on the preliminary relevance; establishing an overall relevance of the one or more objects based on the at least one rating; ranking the one or more objects according to the overall relevance; providing data as search results comprising the one or more objects according to the ranking to the user; filtering the search results based on at least one selected, dynamically generated filter associated with the one or more objects; and modifying the search results, based on one or more query terms from the user and the overall relevance, by re-ranking the one or more objects.

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3. The method of claim 1 , further comprising after the splitting of the digital audio file into a plurality of frames: calculating an overall energy speech probability for each frame; calculating a band energy speech probability for each frame; calculating a spectral peakiness speech probability for each frame; calculating a residual energy speech probability for each frame; computing an activity probability for each frame from the overall energy speech probability, band energy speech probability, spectral peakiness speech probability, and residual energy speech probability; comparing a moving average of activity probabilities to at least one threshold; and identifying speech and non-speech segments in the digital audio file based upon the comparison.

1. A method of producing a diarized transcript from a digital audio file, the method comprising: obtaining a digital audio file; splitting the digital audio file into a plurality of frames; segmenting the digital audio file into entropy segments based upon an entropy of each frame; performing a blind diarization to identify a first speaker audio file and a second speaker audio file by clustering the entropy segments into the first speaker audio file and the second speaker audio file, wherein the first speaker audio file only contains audio attributed to the first speaker and the second speaker audio file only contains audio attributed to the second speaker; and identifying one of the first speaker audio file and second speaker audio file as an agent audio file and another of the first speaker audio file and the second speaker audio file as a customer audio file; and transcribing the agent audio file and the customer audio file to produce a diarized transcript.

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17. The method of claim 15 , further comprising adding an attribute to the dictionary related to a different application to the dictionary for use of the dictionary by the different application.

15. A computer-implemented dictionary method, comprising: formatting a dictionary in a universal format consumable by disparate client applications; drawing content for the formatted dictionary from other available dictionary sources on networks including: lexicons related to Asian languages, automobiles, printing, financials, construction, abbreviations, Japanese English, translation, old words, sources related to Chinese traditional (CHT) and Chinese simplified (CHS), and compound words, old poems, legal, economy, and medical; compiling the drawn formatted dictionary specific for use in each of the disparate applications in response to a request for the dictionary; conducting checks related to at least one from a set of: geopolitics, accuracy, and performance to ensure the dictionary meets predefined criterion; downloading the compiled dictionary for use by the application; sharing the compiled formatted dictionary with at least one compatible application among the disparate client applications supporting a format of the compiled formatted dictionary; and synchronizing the compiled formatted dictionary with at least one other compiled formatted dictionary used by at least one other application among the disparate client applications, wherein the disparate applications comprise speech dictation, spell checking, linguistic analysis, and input method applications.

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21. The non-transitory computer-readable storage medium of claim 20 wherein the definable ratio bound is:  C ′   C *  > 1 - 1 e where I C* I is a number of points covered by an optimum solution C* and I C′ I is a number of points covered by the near optimal solution produced by the approximation algorithm.

20. The non-transitory computer-readable storage medium of claim 19 wherein the approximation algorithm provides a near optimal solution to an NP-hard n-gram selection problem, the non-transitory computer-readable storage medium further comprising: providing the approximation algorithm with a definable ratio bound of the optimal solution.

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4. The interlayer video decoding method of claim 1 , wherein the candidate is based on motion information of a right lower block of a corresponding block indicated by a disparity vector of the second layer current block from a location of the second layer current block.

1. An interlayer video decoding method comprising: obtaining brightness compensation information indicating whether a second layer current block performs brightness compensation; determining whether a candidate of the second layer current block is usable as a merge candidate based on whether the brightness compensation information indicates that the brightness compensation is performed and whether the candidate of the second layer current block performs time direction inter prediction; generating a merge candidate list including at least one merge candidate based on a result of the determining; and determining motion information of the second layer current block by using motion information of one of the at least one merge candidate.

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30. The computer-based system of claim 29 , wherein the IPC-overlap of a given patent document is an average overlap score between the IPC codes of that patent document and all the IPC codes of the initial high-ranking set of patent documents.

29. The computer-based system of claim 25 , wherein the set of patent features includes IPC-overlap, representing the number of the overlapping IPC codes between the IPC codes of a patent in the first set of candidate patent documents and the IPC codes of an initial high-ranking set of patent documents the first set of candidate patent documents, the re-ranking module further adapted to compute IPC-overlap including code adapted to define the overlap score between two IPC codes, divide each IPC code to a plurality of levels based on IPC code structure, and wherein a first level overlap between two IPC codes results in a first score and a second level overlap between two IPC codes results in a second score.

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12. The system of claim 1, wherein the driver and the API allow an application program to discover the number of rows of the table by visiting each object, if any, which is an instance of the effective class, until a "no more date" indication is returned because each object, if any, has been accessed.

1. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database result, wherein the directory services repository component includes an effective class and an object having a context the relational database language statement identifies a table and a subset restriction, and the driver and the API together map the effective class to the table and also map the context to the subset restriction.

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1. A recommendations system for selecting items to recommend to a target user, the system comprising: a computer system comprising computer hardware, the computer system programmed to implement: a user interface that provides functionality for users of an electronic catalog of items to create and assign arbitrary textual tags to individual items represented in the electronic catalog after selecting said items, such that the textual tags categorize the items represented in the electronic catalog, the user interface comprising a tag entry field on item detail pages of the electronic catalog, the tag entry field enabling the users to create the tags via entry of text strings into the tag entry field; a recommendation engine comprising a tag-based recommender configured to: programmatically identify, from item preference data stored in computer storage, an electronic catalog item previously selected by a target user, without receiving a designation from the target user of the previously selected item, subsequent to identification of the electronic catalog item, programmatically identify one or more tags of the textual tags associated with the previously selected catalog item in a data repository by at least identifying a threshold number of most popular tags assigned to the selected item, without any input from the target user, the one or more identified tags having been assigned to the electronic catalog item via the user interface, and subsequent to said identification of the one or more tags, automatically search the electronic catalog using the one or more identified tags as one or more keywords to identify a corresponding set of related items; and a candidate selector component configured to: select at least a portion of the set of related items to provide as recommendations to the target user, and output the recommendations with associated textual reasons for recommending the items.

25. The system of claim 1 , wherein the items of the electronic catalog are products that are available for purchase.

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17. The method of claim 14 , wherein the providing for user-annotation of the submitted print jobs with a constraint category comprises providing for the user to propose a new constraint category for adding to the plurality of constraint categories.

18. The method of claim 17 , wherein the proposed new constraint category is submitted to a coordinator for review before adding the proposed new constraint category to the plurality of constraint categories.

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6. The method of claim 1 wherein providing a personal search term list further comprises receiving from the user and adding to the personal search term list a keyword selected by the user from within a document.

1. A method of personalized searching for information in a distributed data processing system, the method comprising: providing in a server-side search portal a personal search term list, wherein the personal search term list includes a user identifier that is associated with a search keyword; receiving from a user a navigation identification message comprising a user identification for the server-side search portal, a search keyword, a user identification, a password, and a navigation location; inserting an index record in a personalized search index in dependence upon the user identification, the navigation location, and the personal search term list, wherein the index record associates the user identification with the navigation location and with the one or more search keywords from the personal search term list; and assigning priority to index entries in the personalized search index including counting the number of times each navigation location is received in navigation identification messages.

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10. The method of claim 1 , wherein determining at least one person of importance to each user and one term of importance to each user includes calculating an importance score for a collection of electronic documents belonging to that user based on at least one of a frequency of access by that user to the collection, a frequency of change by that user of electronic documents in the collection, and an importance of documents in the collection.

1. A method for tracking interests of users based on personal information, the method comprising: monitoring a stream of documents from more than one user to obtain therefrom a plurality of electronic documents each belonging to one of the users; generating, for each obtained electronic document, a dynamic interest profile (DIP) document based on information obtained from that electronic document; associating each generated DIP document with one of the plurality of users; uniquely assigning a document queue to each of the users; selecting, for each DIP document, one of the document queues into which to place that DIP document based on the user with which that DIP document is associated; polling each document queue to detect changes to that document queue; determining, in response to detecting a change to the document queue of each user, at least one person of importance to that user and one term of importance to that user based on the DIP documents in the document queue uniquely assigned to that user; generating an interest profile of each user that includes each person and each term of importance of that user; and storing the interest profiles of the users in a DIP database.

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2. A method for verification of image linear structure in medical imaging applications, comprising: selecting, from a plurality of different parameter generating sources, parameters for a linear structure verifier in a medical imaging system; configuring the linear structure verifier according to the parameters; and verifying, using the linear structure verifier, linear structure associated with a microcalcification candidate cluster in a medical image, wherein the linear structure verifier utilizes cascade rules to verify the linear structure associated with the microcalcification candidate cluster.

4. The method as in claim 2 , wherein the linear structure verifier can be used before classifying the microcalcification candidate cluster.

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11. A method according to claim 2 , wherein the grid includes rows and columns.

2. A method according to claim 1 , wherein the taxonomy is displayed in the form of a grid with the listing of the documents relevant to the deal on one axis, and the listing of the parties of the deal on another axis.

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13. The method of claim 1 , further comprising: detecting whether two or more abstract syntax trees are equivalent; and merging the two or more abstract syntax trees into a single abstract syntax tree based upon whether the two or more abstract syntax trees are equivalent.

1. A method for pre-parsing headers comprising: scanning one or more header files on a computing device into a tokenized form and scanning the tokenized form for one or more symbols and creating one or more preprocessor symbol tables based upon the one or more symbols; parsing the tokenized form on the computing device into one or more abstract syntax trees; creating one or more pre-parsed headers for the one or more header files, by: serializing in a modular form the one or more abstract syntax trees to a storage device; serializing in a modular form the tokenized form to the storage device; and serializing in a modular form the one or more preprocessor symbol tables to the storage device; locating the one or more pre-parsed headers from the storage device based upon directives in one or more source files; deserializing the one or more abstract syntax trees from the pre-parsed headers on the computing device; and compiling the one or more source files using the one or more abstract syntax trees on the computing device.

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18. A non-transitory computer-readable medium containing instructions for controlling a computer system to manage video contents, the computer-readable medium comprising: code for generating a customized taxonomy of topics personalized for a user, based on a viewing history of the user, the customized taxonomy of topics including at least one hierarchical level of sub-topics from dynamic data sources, wherein the code for generating the customized taxonomy of topics comprises: code for collecting a plurality of keywords related to a video topic, wherein the keywords are collected from a plurality of dynamic data sources; and code for utilizing a taxonomy builder for: identifying one or more video sub-topics of the video topic based on a ranking of the keywords collected for the video topic; and building a topic node in the custom taxonomy of topics, wherein the topic node includes a set comprising: a topic identifier for the video topic; a child topic identifier comprising a list of the video sub-topics identified; and a keyword section comprising the keywords collected for the video topic; and code for categorizing and ranking a plurality of videos by identifying keywords in video metadata associated with the plurality of videos, and using the hierarchical relationship in the customized taxonomy of topics to determine how closely the plurality of videos are related to the first video topic and the video sub-topics by comparing the keywords identified in the video metadata associated with the plurality of videos to the keyword section.

24. The computer-readable medium of claim 18 , further comprising: code for assigning a rank to each of the keyword collected based on the keyword's relevancy to the first topic, wherein the sub-topics are identified from the keywords by using the ranks assigned to the keywords; wherein the set comprises a tuple that includes the topic identifier for the topic node, the child topic identifier for the topic node, and the keyword section for the topic node.