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1. An application component distribution system comprising: a repository of semantic models for interdependent ones of application components; a mapping of individual listings in said semantic models to target platform specific installation instructions; and, a script generation engine configured to produce a target specific set of instructions for a specified application component based upon a mapping of at least one of said semantic models in said repository.

2. The application component distribution system of claim 1 , wherein each of said semantic models comprises a listing of component relationships, target platform requirements and platform neutral installation instructions.

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13. The information retrieving apparatus according to claim 1 , wherein, in addition to the produced additionally recognized vocabulary, the recognized vocabulary producing unit produces a new additionally recognized vocabulary by combining any one attribute of the name database and the additionally recognized vocabulary.

1. An information retrieving apparatus comprising: a name database that registers at least one record as a unit, each of the record contains at least one attribute to be retrieved and a value associated with the attribute, wherein the value is content about each of the attribute; an operation input unit that receives an operation input of a user; a voice input unit that receives a voice input of the user; a voice recognizing unit that recognizes voice obtained from the voice input unit as a character string; a sound model storing unit that stores sound data referred by the voice recognizing unit; a language model storing unit that stores, as a language model, a vocabulary recognized by the voice recognizing unit and a connection rule of the corresponding vocabulary; a retrieving unit that retrieves the value of the attribute included in the name database using an input character string input from the operation input unit or the voice recognizing unit, and creates, as a candidate, the record in which the input character string is included in the value; an output unit that outputs, as the search result, the candidate of the record created by the retrieving unit; a selecting unit that selects the output candidate of the record; and a recognized vocabulary producing unit that receives a selection result of the record by the selecting unit, and produces a new additionally recognized vocabulary that is a voice recognized vocabulary to be added to the language model, wherein the recognized vocabulary producing unit records, in the name database or the language model, a corresponding relationship between the additionally recognized vocabulary corresponding to the input character string and the selected record.

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1. A method comprising: storing reliability data that indicates, for each source of a plurality of sources, a reliability rating of said each source; wherein a first source of the plurality of sources has a first reliability rating that indicates a reliability of the first source, and a second source of the plurality of sources has a second reliability rating that indicates a reliability of the second source and that is different than the first reliability rating; wherein at least one of the first reliability rating or the second reliability rating is based on previous fact checking results; receiving information to be fact checked; selecting at least one of the first source or the second source from among the plurality of sources based on the first reliability rating or the second reliability rating, wherein a difference between the first reliability rating and the second reliability rating indicates that one source is more reliable than the other source; in response to receiving the information to be fact checked, performing a comparison of the information to be fact checked with source information from one or more sources to determine factual accuracy of the information and to generate a fact checking result representative of a factual accuracy of the information, the one or more sources comprising the at least one of the first source or the second source; causing an icon indicative of the fact checking result to be displayed; wherein the method is performed by one or more computing devices.

6. The method of claim 1 wherein hovering over the icon displays the fact checking result as text or audio.

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9. An encoding apparatus, comprising: a determining unit configured to determine a to-be-encoded first information group, wherein the first information group comprises m characters, m≧2, and m is an integer, wherein a character attribute of any character is a data character, a boundary character, or a third-type character, one character occupies one byte, and the third-type character is a character except the data character and the boundary character; a detecting unit configured to detect a character attribute of each character in the first information group; a generating unit configured to: if the first information group comprises n boundary characters, wherein n≧1, and n is an integer, delete the n boundary characters, and generate a second information group by using a character, except the n boundary characters, in the first information group, and type information and position information that are of the n boundary characters, wherein the second information group comprises m bytes; and an adding unit configured to add header information to the second information group according to a type of the first information group and a correspondence between a prestored type of a information group and a type of header information of the information group, wherein the type of the first information group is determined by the prestored type of the information group and character attributes of the characters in the first information group.

10. The encoding apparatus according to claim 9 , wherein the generating unit is configured to: interchange first n characters in the first information group and the n boundary characters, delete the n boundary characters, and record, in at least first n bytes of the first information group, the type information and the position information that are of the n boundary characters to obtain the second information group, wherein the second information group comprises the m bytes; or delete the n boundary characters to obtain n idle bytes; move backward a character preceding the n th idle byte in the n idle bytes, so that remaining m-n characters in the first information group are recorded in consecutive bytes; and record, in at least first n bytes of the first information group, the type information and the position information that are of the n boundary characters to obtain the second information group, wherein the second information group comprises the m bytes.

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14. The system of claim 8 , wherein at least one of the plurality of random document vectors include a plurality of floating point values.

8. A system for generating and using a semantic space in a computer system, comprising one or more computer processors configured to: receive a plurality of documents and a plurality of random document vectors, wherein each random document vector in the plurality of random document vectors is generated based on random indexing and is associated with a corresponding document in the plurality of documents; select a term for which to generate a term vector; for a first document in the plurality of documents, determine if the term appears in the document; and if the term appears in the document: determine a frequency of the term in the document; add an associated random document vector of the document to the term vector, wherein the associated random document vector is scaled by the term frequency; determine if the term appears in any remaining documents in the plurality of documents; if the term does not appear in any remaining documents in the plurality of documents, generate a normalized version of the term vector with the added associated random document vector; output the normalized term vector; receiving a query; and generating, based at least in part on the semantic space including the normalized version of the term vector, a user interface displaying similar and near-duplicate documents.

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1. An intra-sentence boundary extracting system for extracting a boundary in a structure of a sentence located either before or after a target word included in words forming inputted sentence data, said system comprising: inputted word classifying means for classifying a first number of words forming the inputted sentence data to produce an input pattern indicating a second number of classification results of the words; and boundary position data output means for receiving the classification results from said inputted word classifying means and for outputting at least one of clause and phrase boundary position data, said boundary position data output means including a neural network formed of an input layer having a third number of units, each unit coupled to said inputted word classifying means to receive each part of the input pattern for the first number of words including the target word, n preceding words before the target word and m succeeding words after the target word, where n and m are at least one, the third number corresponding to the first number times the second number of classification results of the words; more than one intermediate layer coupled to said input layer; and an output layer, coupled to at least one of said more than one intermediate layer, to output the boundary position data on the structure of the sentence, corresponding to a boundary of at least one of a clause, a noun phrase, a verb phrase, a preposition phrase and an infinitive phrase either before or after the target word.

2. An intra-sentence boundary extracting system according to claim 1, further comprising: boundary determining means for outputting a boundary determination result for the target word based on the boundary position data outputted by said boundary position data output means indicating whether at least one of a clause and a phrase boundary exists at least one of before and after the target word.

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1. A method for automatically presenting content relevant to a current message, said method comprising: obtaining a multi-tiered user model containing a multi-tiered representation of pair-wise interactions of a first user with each of one or more contacts, wherein the multi-tiered representation includes a plurality of topic models, wherein each of the topic models is generated from a pair-wise interaction between the first user and one of the contacts for at least one communication outside of a communication thread of said current message, wherein each of the topic models contains a set of topics, wherein each topic is associated with (i) a first probability of a word given the topic for substantially all words, wherein the first probability provides a list of topic keywords that describe the topic, and (ii) a second probability of the topic given a message for substantially all messages in the associated pair-wise interaction, wherein the second probability provides a list of messages associated with the topic; extracting context information of a current message based on a content of the current message, one or more of a sender and a recipient of the current message, and the multi-tiered user model; determining the topic of the current message by computing a topic distribution of the current message based on the second probabilities for each topic and selecting the topic with the highest probability; determining a retrieval strategy based on the extracted context information of the current message; selecting from a set of information repositories for contextual information retrieval based on the determined retrieval strategy, wherein the set of information repositories comprises one or more of people directories, a local memory, one or more online repositories, an email repository and a calendar entry repository, wherein at least one information repository in said set is outside of said communication thread of said current message; generating one or more contextual queries for document retrieval based on one or more words contained in the current message and one or more keywords associated with the determined topic of the current message to search the selected information repositories; and presenting the content relevant to the current message from the selected information repositories based on the one or more contextual queries.

2. The method of claim 1 , wherein the contacts comprise one or more of email contacts, calendar contacts, groups of email contacts and groups of calendar contacts.

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6. The method of claim 5 further comprising notifying an administrator who is responsible for all knowledge management documents on the knowledge management system if the sensitive information for the first project appears on a knowledge management document on the knowledge management system and notifying the administrator if the sensitive information for the second project appears on a knowledge management document on the knowledge management system.

7. The method of claim 6 further comprising notifying an author of a knowledge management document if the sensitive information for the first project appears in content produced by the author.

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20. A system, comprising: one or more processors; and memory storing instructions that when executed by at least some of the processors effectuate operations comprising: obtaining a corpus of more than 500 documents, each document having unstructured natural language text; obtaining a set of topics and, for each topic in the set, a respective set of n-grams pertaining to the respective topic; receiving a selected topic among the set of topics, the selection indicating that relationships between the documents are to be enhanced or suppressed in virtue of the relationships arising from text relating to the selected topic; forming a relationship graph of the documents, the relationship graph having more than 500 nodes, each node corresponding to at least one document, the graph having edges between nodes indicating a relationship between documents corresponding to the respective nodes, wherein: forming the relationship graph comprises forming a feature vector for each document, each feature vector having plurality of scores, each score corresponding to a given n-gram and being based on: an amount of occurrences of the given n-gram in the respective document, a length of the respective document, an amount of occurrences of the given n-gram in a plurality of other documents different from the respective document, and whether the given n-gram is among the set of n-grams pertaining to the selected topic and, when the given n-gram pertains to the selected topic, a cardinal score indicating an amount that the given n-gram pertains to the selected topic, the relationships between pairs of the documents are determined based on co-occurrence of n-grams in the pairs of the documents, and wherein the relationships are enhanced or suppressed in response to co-occurring n-grams being in the respective set of n-grams of the selected topic; and storing the relationship graph in memory.

32. The system of claim 20 , wherein forming the relationship graph comprises performing steps for adjusting feature vectors of documents based on the set of n-grams pertaining to the selected topic.

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12. A computer program product comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer: to utilize two or more classifiers to calculate, for an input image, probability scores for a plurality of classes based on visual information extracted from the input image and semantic relationships in a classification hierarchy, wherein each of the two or more classifiers is associated with a given one of two or more levels in the classification hierarchy with each level in the classification hierarchy comprising a subset of the plurality of classes; to classify the input image based on the calculated probability scores; to train the two or more classifiers to calculate probability scores for respective subset of the plurality of classes; and to perform label inference to refine classification probabilities in the two or more classifiers based on semantic relationships in the classification hierarchy; wherein training the two or more classifiers and performing label inference comprises at least one of: taking as input a graph structure having initial values for nodes corresponding to classification probabilities in the two or more classifier and outputting the graph structure with modified values for the nodes; utilizing a multi-task learning based loss function that jointly optimizes classifiers associated with each of the two or more levels in the classification hierarchy; and utilizing a random walk process that smooths classification probabilities over two or more classes in a same semantic path in the classification hierarchy.

16. The computer program product of claim 12 , wherein the classification hierarchy comprises a tree structure and performing label inference to refine the classification probabilities in the two or more classifiers comprises, for two or more leaf nodes having classification probabilities within a designated threshold from one another, adjusting the classification probabilities for the two or more leaf nodes based on classification probabilities for parent nodes in a higher level of the classification hierarchy relative to the two or more leaf nodes.

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1. A method comprising: establishing a first entity and a second entity in an entity relationship graph, wherein the entity relationship graph comprises a set of entities interconnected through a plurality of edge relationships and wherein the first entity and the second entity are included in the set of entities; assigning an initial activation value to the first entity; creating an activation value distribution in the entity relationship graph by spreading the initial activation value assigned to the first entity to other entities in the entity relationship graph; determining an activation value at the second entity in the activation value distribution; determining a plurality of candidate path relationships between the first entity and the second entity, wherein each of the plurality of candidate path relationships terminates at both the first entity and the second entity and comprises one or more edge relationships in the plurality of edge relationships; for each candidate path relationship in the plurality of candidate path relationships: determining a path type that is associated with a candidate path relationship; and generating a score value for the candidate path relationship based in part on the path type that is associated with the candidate path relationship; wherein the score value represents a likelihood that the candidate path relationship is of interest to a user; and selecting, in the plurality of candidate path relationships, one candidate path relationship having a score value that satisfies one or more first criteria; wherein the plurality of candidate path relationships is identified as one or more path relationships whose contributions to the activation value at the second entity satisfy one or more second criteria; wherein the method is performed by one or more computing devices.

4. A method as recited in claim 1 , wherein an entity in the entity relationship graph is of one of a plurality of entity types.

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17. The system of claim 16 , wherein identifying one or more segments in the first sequence, comprises: evaluating the subsequences in the first sequence using a sliding window of length (L), wherein an internal entropy expert and a boundary entropy expert each vote a position in each sliding window subsequence at which to split the sliding window sequence; and inducing a segment boundary at each position in the first sequence that receives at least a number of votes satisfying a vote count threshold (V).

19. The system of claim 17 , further comprising, determining the sliding window length (L) as L = ⌈ argmax ⁡ ( H ^ I ) + argmax ⁡ ( H ^ B ) 2 ⌉ , wherein Ĥ I and Ĥ B , represent a standardized entropy value for the entropy measure determined for each node in the ngram trie and argmax( ) returns a level of the node in the trie with the greatest entropy values for Ĥ I and Ĥ B .

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9. A method comprising: maintaining, by one or more processors, a plurality of application state records on a storage, each application state record including i) a function identifier that indicates content corresponding to data provided by a software application when the software application is set in an application state indicated by the application state record; maintaining, by the one or more processors, a plurality of cluster records on a storage device, each cluster record indicating a respective cluster, each cluster including a respective clustered function identifier among a plurality of clustered function identifiers, each clustered function identifier indicating the state of the respective software application, the plurality of clusters of application state records being clustered according to one or more features; receiving, by the one or more processors, a search query containing one or more query terms from a remote device; identifying, by one or more processors, a consideration set of application state records from the plurality of application state records based on the search query, each application state record matching to at least one of the one or more query terms; and for each application state record in the consideration set: identifying, by the one or more processors, based on the search query, one or more cluster records from the plurality of cluster records using the function identifier of the application state record included in the consideration set of application state records; determining, by the one or more processors, a result score of the application state record included in the consideration set of application state records based on the contents of the application state record and one or more cluster records; generating, by the one or more processors, search results based on the application state records of the consideration set and result scores thereof; and transmitting, by the one or more processors, search results to the remote device.

10. The method of claim 9 , wherein the plurality of clusters of application state records are determined based on usage data collected from a plurality of user devices, the usage data indicating states of software applications accessed by users of the user devices.

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1. A user interface for providing dynamic search query resolution, the interface executed on a hardware processor comprising: a search input field to receive a search query from a user; and a resolved attribute portion to display a resolved-attribute of the search query for an entered attribute of the search query, wherein the resolved attribute is determined based on referencing an accuracy profile of the user, wherein the accuracy profile is a multivariate profile having one or more input-imprecision traits of the user, wherein the entered-attribute is an input of the user and the resolved attribute is a resolved-input for executing the search query, and wherein the search query with the resolved-attribute is provided as an option for executing the search query.

2. The user interface of claim 1 , wherein determining the resolved-attribute is based on altering the entered-attribute based on information generated by a search engine query processor, wherein the search engine query processor provides interface elements based at least in part on the accuracy profile of the user.

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15. The non-transitory machine-readable medium recited in claim 13 , wherein the text window comprises one or more words associated with the entity, and wherein the selected features are selected from the one or more words.

13. The non-transitory machine-readable medium recited in claim 12 , wherein the machine-readable instructions that train the classifier comprise machine-readable instructions that, when executed by the processor: select a text window comprising an entity of the microblogging data; select one or more features from the text window to train the classifier to determine a sentiment polarity for the entity.

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8. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text corresponding to a request of a user; processing the text in a first natural language understanding (“NLU”) module to generate a first interpretation of the transcription, and in a second NLU module to generate a second interpretation of the transcription, wherein first NLU module is associated with a first domain, and the second NLU module is associated with a second domain, wherein the first interpretation is associated with a first score indicative of whether the first interpretation corresponds to an action requested by the user, and wherein the second interpretation is associated with a second score indicative of whether the second interpretation corresponds to the action requested by the user; selecting the first interpretation based at least partly on the first score and the second score; and generating a response based at least partly on the first interpretation.

9. The computer-implemented method of claim 8 , wherein processing the transcription in the first NLU module is performed in parallel with processing the transcription in the second NLU module.

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6. A computer program product embodied on a non-transitory computer readable medium and configured to execute by a microprocessor, the computer program product comprising a method for predicting a sequence of cyber events by computer instructions comprising: collecting baseline cyber event patterns and storing the baseline cyber event patterns in a cyber event repository; searching the baseline cyber event patterns for sequential patterns and storing the sequential patterns in a pattern repository; translating the sequential patterns into a probabilistic graphical model, wherein the probabilistic graphical model is a Dynamic Bayesian Network prediction model; and using a temporal reasoning engine to feed the probabilistic graphical model with current cyber events and predict future cyber events and the probability the future cyber events will happen in a next time window.

7. The computer program product of claim 6 , wherein the baseline cyber events are collected by executing sequential event mining algorithms.

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3. A computer implemented method for optimizing a query expression on a database engine of a database server, comprising: sending, by the computer, the query expression to the database engine, wherein the query expression contains a plurality of predicates; initiating, by the computer, query processing of the query expression; incrementing, by the computer, an evaluation counter, wherein the counter increments an evaluation counter value corresponding to a predicate when a predicate evaluation results in a Boolean result; setting, by the computer, a flag within the database engine when the evaluation counter value reaches a threshold value; incrementing, by the computer, a seen counter, wherein the seen counter increments a seen counter value corresponding to each of the plurality of predicates when a predicate is evaluated; assigning, by the computer, a cost value to each predicate of the plurality of predicates determined by a duration of time that a query processor uses to evaluate each predicate; and reordering, by the computer, predicates in the query expression in order of a most efficient predicate with a greatest probability of an early exit of the query expression evaluated first and a least efficient predicate with a lowest probability of an early exit of the query expression evaluated last in the query expression, wherein predicate efficiency is defined as the evaluation counter value divided by a product of the seen counter value and the cost value.

12. The method of claim 3 , further comprising continuing to run the query on a first query processor while evaluating the efficiency of an ordering of the predicates in the query expression on a second query processor.

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3. The method of claim 1 , wherein generating the set of the large event types is configured to determine a set of candidate event types, for which a total number of supporting customers is a preset minimum support or more, among one or more candidate event types to be the large event type set.

4. The method of claim 3 , wherein: the candidate event types are extracted by processing the event file in parallel using a Map function, and supports of the candidate event types are calculated in parallel using a Reduce function.

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14. A computer program product for annotating a video, the computer program product stored on a non-transitory computer-readable medium and including instructions configured to cause a processor to execute steps comprising: displaying by a computer on a device a video player graphical user interface, the user interface including a display area for presenting a video and associated control buttons, the video including a plurality of annotated intervals; displaying, by the computer, a timeline associated with the video; displaying, by the computer in the display area, a frame of the video ; receiving, by the computer, a user selection of a region of the displayed frame; responsive to receiving the selection of the region, displaying, by the computer in the displayed frame, an annotation definition image indicating the selected region; receiving, by the computer, a user selection of a control button to create an annotation; providing, by the computer, a display area for receiving user input of annotation content; receiving, by the computer in the display area, the user input of annotation content; associating the annotation content with the displayed frame of the video and the selected region to generate an annotated video frame; ranking the plurality of annotated intervals based on a number of annotations associated with each annotated interval; indicating on the timeline a marker associated with the annotated video frame; while displaying the timeline, displaying an annotated thumbnail associated with the annotated video frame in the user interface responsive to a user interaction with the marker; and displaying indications of ranked orders with markers associated with each of the annotated intervals on the timeline.

16. The computer program product of claim 14 , wherein displaying the frame of the video further comprises: playing the video in the user interface; receiving, during playback of the video, user selection of a control button; ceasing playback of the video; selecting a frame of the video responsive to a portion of the video being played back at the time of receiving the user selection; and displaying the selected frame in the user interface.

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1. A computer-implemented method for processing language input in a system that includes a mobile computer, the mobile computer including a microphone and a display and a text input device operable by a user, the method comprising operations of: (a) responsive to the mobile computing device receiving via the microphone voice input comprising multiple discrete utterances from a user, converting the voice input into a digital sequence of vectors; (b) the mobile computing device creating an initial N-best list of words corresponding to each of the utterances by conducting speech recognition operations including matching the vectors to potential phonemes and matching the phonemes against a lexicon model and a language model, the operation of creating each initial N-best list of words further considering context of the corresponding utterance with respect to words of N-best lists corresponding to others of the received utterances, said context including subject-verb agreement, proper case, proper gender, and numerical agreement; (c) for each of said utterances, the mobile computing device visually displaying a best word from the initial N-best list of words corresponding to said utterance; (d) responsive to implied or explicit user selection of one of the displayed best words, said selected word being from a given N-best list of words corresponding to a given utterance, the mobile computing device causing the display to present additional words from the given initial N-best list of words; (e) during said presentation of the additional words, the mobile computing device receiving via the text input device hand-entered input from a user, and responsive to said text input, constraining said presentation of the additional words to exclude words of the given initial N-best list that are inconsistent with the textual input; (f) responsive to said presentation of the additional words being constrained to a resultant word, displaying the resultant word instead of the selected word; (g) the mobile computing device updating the initial N-best lists of others of the utterances besides the given utterance to provide subject-verb agreement, employ proper case, use proper gender, and exhibit numerical agreement when considered in context of the resultant word; (h) for each of the utterances having an updated N-best list, the mobile computing device causing the display to present a best word of the updated N-best list of words for that utterance; and (i) for each of the utterances without an updated N-best list, the mobile computing device causing the display to present a best word of the initial N-best list of words for said utterance.

2. The method of claim 1 , where the operations further include, in parallel with the operation (e), the mobile computing device interpreting the text input as user entry of a new word for entry immediately after the selected word; and responsive to the user completing entry of the new word before the presentation of additional words is constrained to a resultant word, instead of operations (f), (g), (h), and (i), the mobile computing device causing the display to present the new word following the selected word.

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2. In a business activity monitoring system, a method for enabling a real time view of heterogeneous enterprise data of an operational system in a view engine, comprising: capturing a stream of operational events in real time; materializing a resulting views wherein said resulting view comprises a dynamically defined view of said stream of events, and wherein said resulting view provides visibility into a current state of said operational system from a plurality of views, wherein said materializing of said resulting view comprises: receiving a structured query language (SQL) string; parsing said SQL string into a parse tree; normalizing said parse tree to form a query graph; optimizing said query graph to obtain a query plan; compiling said query plan into an operator graph; and executing a query based upon said operator graph, wherein said query defines said view.

3. The method as recited in claim 2 wherein said operator graph comprises a query execution plan comprising an operator selected from a group consisting of: event scan, wherein said event scan operator subscribes to said stream of events and gets rows corresponding to said events; view exchange, wherein said view exchange operator maintains a snapshot of said view; remote scan, wherein said remote scan operator scans a context table; nested loop join, wherein said nested loop join operator performs a nested loop joining operation; group by, wherein said group by operator performs a group by and a set function evaluation operation; and projection, wherein said projection operator performs an operation wherein wanted columns are projected.

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11. The system of claim 7 , wherein said outputted modified set of records comprise a concise and complete temporal history of all data records such that a history of said entity is retrievable via a standard XML manipulation language.

7. A system for processing a set of data records having time conflicts, the data records representing respective versions of an entity for which there can be only one preferred value at any given point in time, wherein each of the data records has an n-dimensional time record, the system comprising: one or more processors; and a memory comprising instructions which, when executed by the one or more processors, cause the one or more processors to: define a policy from among a plurality of candidate policies, said defined policy designed to resolve time conflicts between those data records having time conflicts; compare all data records in a cumulative, pair-wise fashion; identify time-based conflicts between pairs of records and identify time-conflicted pairs; determine which record in every time-conflicted pair of records is to be adjusted in accordance with said defined policy; adjust the time interval of every said determined record to be adjusted in accordance with said defined policy; and output a modified set of data records having said adjusted time intervals, wherein (i) said modified set of data records contains no time conflicts and (ii) said adjusted time intervals in the modified set of data records do not depend on the order in which the data records are processed by said computer-implemented method.

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19. The computer-readable memory of claim 17 , wherein the edge detection algorithm is selected from the set of edge detection algorithms based on at least one of the visual content or the search word from the voice directed query.

17. A computer-readable memory including computer-executable instructions that, when executed by a processor, cause the processor to perform acts including: rendering visual content on a display, wherein the visual content is one of a frame from a video stream, a two-dimensional image, or a three-dimensional image; receiving a voice directed query related to the visual content rendered on the display, wherein the voice directed query comprises at least a search word; using the search word from the voice directed query as an input for a first search; detecting an object from the visual content as a function of a first result of the first search; selecting an edge detection algorithm from a set of edge detection algorithms; extracting an image of the object from the visual content using the edge detection algorithm selected from the set of edge detection algorithms, wherein the image of the object is a portion of the visual content and is extracted from a remainder of the visual content; using the image of the object extracted from the visual content as an input for a reverse visual search, wherein the reverse visual search is executed based upon the image of the object extracted from the visual content; and rendering a second result of the reverse visual search on the display.

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15. A computer-readable storage device having instructions stored which, when executed by a computing device, perform operations comprising: training a spoken dialog system using task-independent call-types of a previous application; recognizing a user utterance using the spoken dialog system, to yield a recognized user utterance; determining an acceptance threshold and a rejection threshold based on an entity referenced in the recognized user utterance; classifying the recognized user utterance, to yield a classification, where the classification meets one of: the rejection threshold, the acceptance threshold, and both the rejection threshold and the acceptance threshold; when the classification meets the acceptance threshold acting according to a call-type associated with the classification; and when the classification meets the rejection threshold, transcribing the recognized user utterance and using the recognized user utterance for further training of the spoken dialog system.

17. The computer-readable storage device of claim 15 , wherein the spoken dialog system performs call-type classification.

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1. A method for resolving a query, the method comprising: maintaining, in electronic storage, a query ontology that includes one or more query categories and one or more queries associated with each of the one or more categories; receiving a query from a user, the received query including a first portion and a second portion that is different than the first portion; in response to receiving the query, accessing, from the electronic storage, one or more queries included within the query ontology; comparing the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query; comparing the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a second group of multiple categories that are associated with a query that matches the second portion of the received query, the second group of multiple categories being different than the first group of multiple categories; comparing the second group of multiple categories with the first group of multiple categories; based on the comparison of the second group of multiple categories with the first group of multiple categories, identifying a category that is included in the second group of multiple categories identified for the second portion of the received query and the first group of multiple categories identified for the first portion of the received query; performing a search process that uses the identified category in identifying search results responsive to the received query, the search process comprising: accessing, from the electronic storage, a subset of one or more query terms included within the query ontology and associated with the identified category; configuring the received query to include the accessed subset of one or more query terms associated with the identified category, the configured query being different than the received query; submitting the configured query to a search engine; receiving, from the search engine, search results corresponding to the configured query; and storing, using a processor in electronic storage, the received search results corresponding to the configured query.

2. The method of claim 1 wherein submitting the configured query to the search engine comprises: identifying a search engine to handle the configured query based on the identified category; and submitting the configured query to the identified search engine.

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28. The computer-readable medium of claim 23 , wherein the method further comprises: creating a second digital signature of the first electronic document using a certificate of an authorized person or an authorized legal entity, creating a second electronic document having the second digital signature; and presenting the second electronic document to the sender of the first electronic document.

23. A computer-readable medium containing instructions for performing a method for automatically processing a first electronic document sent from a sender to a designated receiver, the first electronic document having a digital signature, the method comprising: receiving the first electronic document from the sender; validating the digital signature by using a public key of the sender; checking whether the digital signature is from a person or a legal entity authorized to send the first electronic document; determining, if the person or the legal entity is authorized to send the first electronic document, whether the person or the legal entity that signed the first electronic document is authorized by an issuer named in the first electronic document to sign the first electronic document; creating an electronic protocol of the results of validating, checking, and determining; signing the protocol; archiving at least one of data selected from the group consisting of the protocol and the first electronic document; and presenting the first electronic document to the designated receiver.

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7. The method of claim 6 , where the specification of the constituent methods includes a specification of an attribute and a value of the attribute, and the attribute is represented by a property of the meta-method class.

6. The method of claim 1 , where the class is defined by a class definition that includes a specification of constituent methods, and each specified constituent method, of the constituent methods, corresponds to an instance of a meta-method class.

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16. The system of claim 13 , wherein the score stored in the beauty score datastore is a score selected from the group consisting of a score of another user, a score of a public figure, and a score of an ideal person.

13. A beauty quantification system comprising: a beauty quantification processor; a beauty measure datastore, wherein the beauty measure datastore comprises quantifiable measures of beauty of a plurality of body regions; a beauty score datastore; a user computing device; a network; and a beauty enhancement processor, wherein the beauty quantification processor comprises instructions for: receiving user data indicative of physical attributes of the plurality of body regions of the user; obtaining measures of beauty from the beauty measures datastore associated with each of the plurality of body regions; evaluating the user data against the beauty measures of each of the plurality of body regions; determining a composite user score indicative of the beauty of the user; storing the user score in the beauty score datastore; and comparing the user score to a score stored in the beauty score datastore; and, wherein the beauty enhancement processor comprises instructions for: receiving from the user a selection for an enhancement of a body region selected from the plurality of body regions; applying the selected enhancement to the selected body region; and determining an enhanced composite user score indicative of the beauty of the user after application of the selected enhancement.

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15. The computer-readable medium of claim 14 , further comprising: determining whether the document content comprises audio; if the document content comprises audio, further comprising embedding a visual representation of the audio at a specified position in the content region of the element; determining whether the document content comprises video; and if the document content comprises video, further comprising embedding the video at a specified position in the content region of the element.

14. The computer-readable medium of claim 13 , wherein selecting the appropriate set of templates further comprises accepting a plurality of templates with successfully evaluated content preconditions and value preconditions.

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7. The method of claim 1 , wherein, in order to offer wares for sale in certain categories, the one or more ontologies are used to annotate the wares with ontology terms.

1. A method of scoring items resulting from a query containing specified terms, wherein the items being scored are annotated to a set of terms in one or more ontologies comprising the steps of: determining whether the set of terms in the one or more ontologies to which the items being scored are annotated are semantically related to the terms in the specified query, assigning an observed semantic similarity score to each of the items being scored; for each item being scored, determining the probability of obtaining the observed semantic similarity score in the event a random set of query terms is used instead of the specified query terms, assigning an individual P-value to the item being scored based on the determined probability, and scoring each of the items, using a computer, according to the assigned P-values.

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1. A computer-implemented method performed by a data processing apparatus, the method comprising: receiving a first query provided to a first search service having a first recall and a first precision and a response from the first search service to the query, wherein the first query references a first entity of a first entity type; determining a first value specified in the response from the first search service; generating a query for a particular attribute value of the first entity, wherein the query is generated using the first value specified in the response from the first search service and using the first entity referenced in the first query; querying a second search service using the query for the particular attribute value of the first entity to identify the particular attribute value of the first entity that matches the first value in the response from the first search service, wherein the particular attribute value is for one of a plurality of attributes that is descriptive of the first entity and that corresponds to an attribute of the first entity, the second search service is distinct from the first search service and has a second recall less than the first recall and a second precision greater than the first precision; receiving a response from the second search service, and that specifies the particular attribute value that corresponds to the attribute of the first entity; determining, based on the particular attribute value specified in the response from the second search service that matches the first value, an attribute type of the first value, the attribute type corresponding to the attribute value of the first entity; and generating, based on the determined attribute type and at least the first query, a parsing rule that parses one or more queries, the parsing rule being associated with an action to provide the particular attribute value of the attribute for an entity referenced in at least the first query.

2. The computer-implemented method of claim 1 , further comprising: selecting a group of queries and corresponding responses, each query in the group of queries determined to meet a similarity threshold to the first query and referencing an entity of a first entity type, and each corresponding response for a query in the group being value of a same value type and having been served by the first search service; querying the second search service for the first entities referenced in the group of queries for attribute values matching the values of the corresponding responses; and determining, from the response of the second search service, an attribute type of the first values.

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1. A method comprising operating a computer system to perform steps of: receiving a document having: markup language constructs comprising a plurality of tags in a first section of the document comprising a first plurality of lines of code; and a plurality of function declarations in a second section of the document separate from the first section of the document and comprising a second plurality of lines of code, the plurality of function declarations comprising the second plurality of lines of code, which define a plurality of corresponding functions, wherein one or more of the function declarations correspond to tags in the first section and have function names the same as tag names of the corresponding tags; and performing a step of tag processing on a first tag among the plurality of tags in the markup language constructs, including: executing a body of the first tag and producing tag output; and subsequent to executing the body of the first tag, invoking a first function, declared among the plurality of function declarations, having a function name that is the same as a tag name of the first tag, and during invocation of the first function accessing the tag output produced as a result of executing the body of the first tag.

6. The method of claim 1 wherein the programming language is a procedural language or an object oriented language.

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10. The apparatus according to claim 9 , further comprising a shortening unit that shortens a reproduction time of the translated speech and the source speech by a length of a second difference computed by subtracting the first threshold time from the first difference, when the first difference is more than the first threshold time.

9. The apparatus according to claim 1 , further comprising a delay unit that computes a first difference by subtracting a second time point at which the source speech is received from a first time point at which the translated speech is determined to have been generated in all of the target languages, and delays output of the translated speech and the source speech until the first threshold time has passed since the second time point, when the computed first difference is less than a first threshold time determined in advance, wherein the output unit outputs the translated speech and the source speech after the delay unit delays the reproduction.

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1. An automated method for generating an image quality guide document comprising: for at least one image in a set of images undergoing image enhancement: identifying image quality-related features for the image based on enhancements being automatically applied to the image, identifying image content-related features based on content of the image, determining a content-based degradation of the image based on the identified image quality-related features and image content-related features, and retrieving a photograph shooting tip for correcting the degradation in the image, based on the determined content-based degradation; generating a thumbnail of each of the images; and generating an image quality guide document including the thumbnails for the images in the set of images in which at least one of the thumbnails is associated with a respective text description that is based on the determined content-based degradation, the text description including the shooting tip associated with the thumbnail of the image.

3. The method of claim 1 , wherein the identifying of image quality-related features for the image includes identifying image quality-related features related to a set of predefined quality-related categories.

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14. The system of claim 12 wherein the one or more definitions for the particular analysis results comprise an association with an associated user.

15. The system of claim 14 wherein the analytic engine further retrieves an analysis digest specification associated with the associated user, parses the multidimensional data set according to the analysis digest specification associated with the associated user to generate a second parsed multidimensional data set, and generates a second plurality of analysis digests in response to the second parsed multidimensional data set and the analysis digest specification associated with the associated user.

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13. A method according to claim 7, comprising the step of: recognizing potential 0-cell matches with non-monotone indices.

7. A method according to claim 1 wherein said matching step b comprises the step of: building an isomorphism between two subsets of 0-cells by several successive runs of different filtering procedures which reject certain potential matches if they are recognized as invalid.

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1. A method for recommending search phrases, comprising: obtaining one or more subject terms and one or more descriptive terms relating to the one or more subject terms from title information of information published by publishers; combining at least some of the one or more subject terms with at least some of the one or more descriptive terms to form a set of one or more search phrases; calculating a first appraisal value for a search phrase among the set of one or more search phrases, the calculating of the first appraisal value comprising multiplying term frequency of the search phrase with an inverse document frequency of the search phrase; determining a second appraisal value of the search phrase, the determining of the second appraisal value comprising: calculating an inverse class frequency of the search phrase within a designated category, wherein the inverse class frequency is regarded as the second appraisal value; calculating a third appraisal value of the search phrase, comprising: calculating a first probability that a first term appears in a search phrase associated with the published information; calculating a second probability that the first term appears jointly with a second term in the search phrase associated with the published information; and combining the first probability and the second probability to obtain the third appraisal value; combining at least the first appraisal value, the second appraisal value, and the third appraisal value of the search phrase to obtain a publisher recommendation appraisal value for the search phrase; and selecting a recommended phrase among the set of one or more search phrases based at least in part on a set of one or more corresponding publisher recommendation appraisal values for the set of one or more search phrases.

7. The method as described in claim 1 , wherein the combining of the at least the first appraisal value and the second appraisal value of the search phrase includes weighting and summing at least the first appraisal value and the second appraisal value of the search phrase.

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2. The method of claim 1 , wherein manipulating the destination table comprises: determining whether the destination table has a structure and a set of destination column names; and in response to determining the destination table does not have a structure and the set of destination column names, copying a structure of the source table and the set of source column names into the destination table.

3. The method of claim 2 , further comprising: in response to determining the destination table has a structure and the set of destination column names, modifying the structure of the destination table and the destination column names, wherein modifying the structure of the destination table further comprises at least one of: adding at least one column to the destination table; and removing at least one column from the destination table.

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2. The computer-implemented method of claim 1 , wherein the content descriptors comprise at least: a large scale subset of the content descriptors characterizing larger scale features of the content piece; and a small scale subset of the content descriptors characterizing smaller scale features of the content piece.

4. The computer-implemented method of claim 2 , wherein the content descriptors at each respective scale are contained in the large scale subset of the content descriptors.

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2. The method of claim 1 , wherein said translating comprises translating the first word at each leaf into a second word in the second language in response to a probability of a correct translation.

1. A method for translating natural languages using a statistical translation system, the method comprising: parsing a first string in a first language into a parse tree using a statistical parser included in the statistical machine translation system, the parse tree including a plurality of nodes, one or more of said nodes including one or more leafs, each leaf including a first word in the first language, the nodes including child nodes having labels; determining a plurality of possible reorderings of one or more of said child nodes including one or more of the leafs using the statistical translation system, the reordering performed in response to a probability corresponding to a sequence of the child node labels; determining a probability between 0.0000% and 100.0000%, non-inclusive, of the possible reorderings by the statistical translation system; determining a plurality of possible insertions of one or more words at one or more of said nodes using the statistical translation system; determining a probability between 0.0000% and 100.0000%, non-inclusive, of the possible insertions of one or more words at one or more of said nodes by the statistical translation system; translating the first word at each leaf into a second word corresponding to a possible translation in a second language using the statistical translation system; and determining a total probability between 0.0000% and 100.0000%, non-inclusive, based on the reordering, the inserting, and the translating by the statistical translation system.

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5. A computer implemented method as recited in claim 1 , wherein analyzing phonetic pronunciations of the words within the potential confusion zone includes, performing a phoneme-level alignment across phonemes of the words of the plurality of statements within the potential confusion zone, and computing a phonetic accuracy value for the potential confusion zone based on the phoneme-level alignment, wherein the phonetic accuracy value corresponds to the measure of confusion probability between the words of the plurality of statements within the potential confusion zone when audibly processed by the speech recognition system during the computing event.

1. A computer implemented method for evaluating potential confusion within a grammar structure for a set of statements to be used in speech recognition during a computing event, comprising: receiving a plurality of statements from within a grammar structure, each of the plurality of statements formed by a number of word sets; identifying a number of alignment regions across the plurality of statements by aligning the plurality of statements on a word set basis, wherein each aligned word set represents an alignment region; identifying a number of potential confusion zones across the plurality of statements, wherein each potential confusion zone is defined by words from two or more of the plurality of statements at corresponding positions outside the number of alignment regions; for each of the identified potential confusion zones, analyzing using a computer phonetic pronunciations of the words within the potential confusion zone to determine a measure of confusion probability between the words when audibly processed by a speech recognition system during the computing event; and generating, using the computer, a report to convey an identity of the potential confusion zones across the plurality of statements and their corresponding measure of confusion probability.

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3. The device of claim 1 , wherein the transformation process compares the data from the process sensor to a threshold parameter for mapping the data from the process sensor to a process parameter.

1. A device comprising: a processing module configured to: receive data from a process sensor, the data including data associated with a system monitored or controlled by the process sensor, a description of the data and a description of a quality of the data, and execute a transformation process for mapping the data from the process sensor to a process parameter associated with the system monitored or controlled by the process sensor, wherein the process parameter is capable of being processed by a process controller that is incapable of processing the data from the process sensor; and an output module configured to: receive the process parameter, generate an output signal representing the process parameter, and output the process parameter to the process controller capable of processing the process parameter and incapable of processing the data from the process sensor.

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17. The non-transitory computer readable medium of claim 14 , the conceptual model comprises resource description framework (RDF) as a data model and the executable code, when executed by the processor, further causes the processor to: summarize RDF data in a resource description framework schema (RDFS) or an ontology web language (OWL) type class to obtain summarized RDF data; and generate, a summarized RDF type graph; and interconnect the summarized RDF type graph with the concept model.

14. A non-transitory computer readable medium having stored thereon instructions for translating user keywords into semantic queries the instructions comprising executable code which, when executed by at least one processor, causes the processor to: receive keywords; search the conceptual model to identify one or more concepts relevant to the keywords; transform at least a portion of the conceptual model into a connected graph; generate at least one path through the connected graph, the at least one path connecting the one or more concepts; identify and rank facets that support incremental user navigation from nodes of convergence in the at least one path, wherein the facets are generated at least in part by indexing a number of distinct values for attributes of the one or more concepts; generate at least one structured semantic query from the at least one path with the identified and ranked facets; and execute the at least one structure semantic query on a semantic repository.

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23. A computer program product according to claim 21 , further comprising program code instructions configured to: determine a temporal relationship between the time period and the descriptor, wherein the phrase specification is further based on the temporal relationship between the time period and the descriptor.

24. A computer program product according to claim 23 , further comprising program code instructions configured to: verify the phrase specification using one or more constraints.

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7. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, maintaining communication data associated with a contact type based at least in part upon past communications between a user and one or more contacts associated with the contact type, the communication data including: a type of communication sent to the one or more contacts of the contact type by the user in a context, the context being associated with at least one behavioral pattern of the user; and a dialog pattern associated with the type of communication in the context, the dialog pattern including at least one of words or phrases from one or more past communications between the user and the one or more contacts associated with the contact type; generating a dialog profile for the contact type based at least in part upon the dialog patterns; identifying a current context as being related to the context; adjusting the dialog profile associated with the one or more contacts to include dialog patterns associated with the context; and generating a communication for the current context based at least in part upon the dialog patterns associated with the dialog profile and the context.

10. The computer-implemented method of claim 7 , wherein the contact type is at least a business contact group, a friend group, or a family group.

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10. A system for determining a rule applicable to uniform resource locators (URLs) corresponding to a plurality of web resources, comprising: a web crawler to receive the web resources from at least one web site on a web server; and a processor to receive the content of the web resources, grouping web resources by content so that each group comprises all of the web resources from the at least one web site that have substantially identical content, wherein each group of substantially identical web resources is referred to as an equivalence class, analyzing URLs corresponding to all substantially identical web resources in an equivalence class to determine a per equivalence class URL rewrite rule applicable to the URLs; analyzing the per equivalence class URL rewrite rule compared to at least one other per equivalence class URL rewrite rule for at least one different equivalence class to determine a trans-equivalence class URL rewrite rule; and applying the trans-equivalence class URL rewrite rule to additional web resources from the at least one website to predict that different URLs reference substantially identical web resources, thereby avoiding receipt by the web crawler of substantially identical web resources.

12. The system of claim 10 , wherein analyzing URLs corresponding to an equivalence class to determine a per equivalence class rule comprises determining what portions of the URLs corresponding to the substantially identical web resources in the equivalence class are relevant to select the substantially identical content and what portions are not.

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11. A computer program product for retrieving task information using task-based indexes, the computer program product comprising computer-readable instruction means encoded on a non-transitory Computer-readable medium for causing a computer to: acquire a plurality of mutually exclusive task-based categories, where L is the number of task based categories; receive a plurality of text documents, where D is the number of text based documents; partition the text documents into a plurality of document sets, where N is the number of document sets, such that each task-based category is associated with a document set, where each document set is comprised of at least one document having subparts and having task information described in the document; associate at least one task-descriptive symbol with each task-based category, index the documents in each document set to create an index having index words and pointers, where the index words reflect the task information in the documents or subparts of documents; correlate the task-descriptive symbols with the index words to create an alignment of words having similar meaning such that index words are matched with similar task-descriptive symbols; and form a plurality of task-based indexes by grouping the alignment of words with the respective task-based category, where M is the number of task-based indexes, and where L is equal to N, which is equal to M, which is less than or equal to D, such that retrieval of a document having task based information pertaining to the task descriptive symbols is a function of the task based index.

19. A computer program product for retrieving task information as set forth in claim 11 , wherein the computer program product is further configured to associate, index, correlate, and form over a computer network.

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9. The method of claim 1 , wherein monitoring includes monitoring an anger level of the contact over a predetermined time period.

1. A method for dialog management within a call handling system, comprising: initiating, by a computer executing machine readable instructions stored on a non-transitory computer readable medium, a dialog between a contact and an operator; monitoring, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, dialog attributes including generating a dialog attribute score for each dialog attribute; presenting, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, an instantaneous value of at least one of the dialog attributes on an operator display; and effecting, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, a dialog rule in response to the dialog attribute scores; wherein the monitoring includes, identifying computational resources required to calculate each of the dialog attribute scores; generating dialog attribute scores hierarchically beginning with the dialog attribute score requiring a least amount of computational resources; and stopping generation of the dialog attribute scores once the combined dialog attribute score exceeds a predetermined threshold.

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24. The system of claim 19 , wherein the web application context includes at least one of a session identifier (ID), a user identity.

19. An application level security system for real-time correlating between requests to a web server and requests to a database server, the security system comprises: a first sensor adapted to capture the requests to the web server; a second sensor adapted to capture the requests to the database server; and a secure server adapted to correlate the requests based on inputs from the first sensor and the second sensor, wherein the security system is being further capable of binding a web application context to each request to a database; wherein requests to web servers are hypertext transfer protocol (HTTP) requests and wherein requests to database server are structured query language (SQL) queries; wherein correlating the request comprises identifying correlated pairs of SQL templates and uniform resource locators (URLs); wherein binding the web application to the SQL query, further comprises; receiving a SQL query from the first sensor; converting the SQL query to a SQL template; searching in the SQL NBP for URLs that correlate to the SQL template; for each HTTP request with a correlated URL: matching between parameters of the HTTP request and literals of the SQL query; computing a matching score for each HTTP request; selecting the HTTP request with the highest correlate score; and binding the web application context of the selected HTTP request to the incoming SQL query.

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66. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a search query; generating first search results that identify resources that a search engine has identified as being responsive to the search query; identifying one or more search modes based on the search query, the resources, or both the search query and the resources; providing a first user interface that presents for display at least a portion of the first search results and a respective search mode selector for each of one or more of the identified one or more search modes; receiving user input selecting a first search mode by selecting one of the search mode selectors, wherein: the first search mode is associated with a first collection of records, all records in the first collection have a common attribute structure of data elements, the first search results identify resources that the search engine has identified from a corpus of resources as being responsive to the search query, and all records in the corpus do not have the common attribute structure of data elements; generating second search results that satisfy the search query and that refer to mode-specific records from the first collection of records that are associated with the first search mode, each of the one or more search modes being associated with a particular collection of records from among multiple collections of records; formatting a plurality of the second search results using a mode-specific presentation template that is associated with the first search mode to generate formatted search results; and providing a second user interface that presents for display the formatted search results.

68. The system of claim 66 , wherein: the first search mode is associated with the first collection of records that share the common attribute structure; a second of the search modes is associated with a second collection of records that share a second common attribute structure; and the common attribute structure is different from the second common attribute structure.

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40. The method of claim 39 , further comprising: numerically expressing, as an associated score, the association between the associated keyword or the extended keyword and the other keywords based on the association indicator; and calculating a ranking score for each purpose of usage based on the associated score and the independent indicator, wherein providing the associated keyword or the extended keyword with respect to the keyword comprises providing the associated keyword or the extended keyword with respect to the search word, based on the ranking score, the association indicator comprises at least one of a purchase association indicator, an advertising association indicator, a service data association indicator, an exposure association indicator, a subject context association indicator, a knowledge shopping association indicator, and a duplication indicator of each association indicator, and the independent indicator comprises a plurality of indicators including at least one of a common indicator, a cost per click (CPC) indicator, and a cost per mille (CPM) indicator.

39. The method of claim 33 , wherein generating the indicator comprises: generating an independent indicator by indicating characteristics of the associated keyword or the extended keyword; and generating an association indicator by indicating an association between the associated keyword or the extended keyword and other keywords.

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16. A system comprising: a processor device to: acquire an electronic image of a document with a fixed structure, wherein the fixed structure comprises field names and field values corresponding to the field names, and wherein the field names and the field values are located at set locations in the document; recognize key words in the electronic image of the document, wherein the key words comprise the field names and the field values; match one or more templates from a plurality of templates with the document, wherein the one or more templates comprise reference objects that specify areas in the electronic image of the document where permitted field values corresponding to field names are to be extracted, and wherein, to match the one or more templates, the processor device is further to match the field names and the permitted field values from the one or more templates with the identified field names and the field values from the recognized key words; select a template from the one or more templates based on a quality of a match between the field names and the permitted field values from the template with the identified field names and the field values from the recognized key words; and extract the field values from the electronic image of the document using the selected template.

28. The system of claim 16 , wherein the plurality of templates comprises at least one preexisting template.

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1. A method comprising: receiving, by a server computer over a network from a computing device, a first request for search suggestions related to a first search query that has been input into a search term entry area displayed by a web browser executing on the computing device; transmitting in response to the first request, by the server computer over the network to the computing device, instructions for the computing device to display a plurality of search suggestions related to the first search query, each of plurality of the search suggestions representing content from a respective search results web page; setting, by the server computer, a cookie with a time stamp for the displaying of the plurality of the search suggestions related to the first search query; transmitting, by the server computer over the network, instructions to the computing device to receive an identified web page component that is part of at least one respective search results web page prior to an initial display of the respective search results web page by the computing device; transmitting, by the server computer over the network to the computing device, during the transmission of instructions to initially display the plurality of search suggestions related to the first search query, storage instructions that further cause the computing device to store in a memory of the computing device the web page component that is part of the at least one respective search results web page prior to initially displaying the respective search results web page; transmitting, by the server computer over the network instructions to the computing device, to visibly display the plurality of search suggestions related to the first search query transmitted by the server computer without visibly displaying the stored web page component during display of the plurality of search suggestions related to the first search query; receiving, by the server computer over the network, a second request for a second search suggestion related to a second search query; determining, by the server computer, that the time period associated with the timestamp of the cookie related to the first search query has not elapsed; and transmitting, by the server computer over the network, upon determination that the time period related to the first search query has not elapsed, instructions to the computing device to display a search suggestion related to the second search query prior to initially displaying the respective search results web page and further causing the computing device to store a web page component associated with a search results web page corresponding to the search suggestion related to the second search query.

8. The method of claim 1 , the instructions to receive the identified web page component are transmitted, by the server computer over the network, in response to the request for search suggestions.

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3. The system of claim 1 wherein the data modeling component models web query log data by weighting the edges using a mutual information probability calculation and discarding edges below a threshold probability.

1. A computer system for iterative set expansion using samples, the system comprising: a processor and memory configured to execute software instructions embodied within the following components; an input component that receives a set of seed terms and a set of terms and associated contexts with which to expand the set of seed terms; a data modeling component that models the received terms and seeds as a bipartite graph with candidate terms being nodes on one side and identified context nodes on the other side, and models web query log data by dividing each query into a context of a fixed number of tokens of prefix or suffix and a remaining term; a similarity determining component that determines a similarity metric between two candidate nodes in the graph based on the candidate nodes' relationship to the context nodes in the graph; a relevance determining component that determines a relevance metric that indicates how similar a node in the graph is to the received seed terms and corresponding nodes; a coherence determining component that determines a coherence metric that indicates how consistent a concept set is that includes the seed terms and one or more candidate nodes; a quality measurement component that combines the determined relevance metric and coherence metric to determine a quality metric that indicates relevance and coherence among a set of nodes in the graph; an iterative expansion component that identifies an expanded seed set having a high quality metric; and a set reporting component that reports the identified expanded seed set as output.

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1. A system comprising: an analytics server associated with a customer contact center, the analytics server being configured to: identify an interaction between a customer and an agent; parse a text of the interaction; determine an intent and a topic of the interaction based on the parsed text; compare the intent and the topic of the interaction with an intent and a topic of a second interaction, wherein the intent and the topic of the second interaction are stored in a data storage device in correlation with an explicit survey score; determine an implicit survey score for the interaction based on the comparing and the explicit survey score; and generate an output based on the determined implicit survey score.

2. The system of claim 1 , where the analytics server further determines the implicit survey score based on attributes about an identity of the customer.

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2. A mobile computing device having telephone functionality for providing one or more alternate symbols associated with a base symbol, the mobile computing device comprising: a display; a memory; a processor coupled to the display and the memory; a user input mechanism; and a computer program stored in the memory, the computer program including instructions that, when executed by the processor, cause the mobile computing device to: receive, through the user input mechanism, a request to display the base symbol for insertion at a cursor location; receive, through the user input mechanism, a request to display the one or more alternate symbols associated with the base symbol, wherein the one or more alternate symbols are accented versions of the base symbol; display the one or more alternate symbols and the base symbol at the same time on the display; and responsive to a user selection of one of the displayed alternate symbols, replace the base symbol with the selected alternate symbol.

13. The mobile computing device of claim 2 , wherein execution of the instructions to display the one or more alternate symbols causes the computing device to: receive, from the user input button, a selection identifying a selected base symbol; determine a plurality of alternate symbols associated with the selected base symbol; and display the plurality of alternate symbols associated with the selected base symbol.

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13. The system of claim 11 , wherein said citation information is resolved from a database containing publication information.

14. The system of claim 13 , wherein said database is an XML-based database.

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3. A method for communicating between a mobile platform and a control device, comprising: generating a first packet of mobile platform specific information at said mobile platform; sending said first packet of mobile platform specific information from said mobile platform to a translating subsystem; using said translating subsystem to convert said first packet of mobile platform specific information to a second packet of common language information understandable by said control device, said common language information including a common language command and common language data; using a publication manager of the translating subsystem to publish the second packet of common language information to said control device via a Global Information Grid (GIG); sending said second packet of common language information from said GIG to said control device; using the control device to receive a new command from a user; using the control device to generate a third packet of common language information relating to the new command; using the GIG to send said third packet of common language information to a subscription manager of said translating subsystem; using said translating subsystem to translate said third packet of common language information to a fourth packet of mobile platform specific information; and using said publication manager of said translating subsystem to transmit said fourth packet of mobile platform specific information to said mobile platform.

9. The method of claim 3 , further comprising using said control device to generate an initial packet of mobile platform specific information that instructs said mobile platform to initiate an electromagnetic jamming signal from said mobile platform.

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1. A game delivery system for delivering a plurality of games in a training program configured to systematically drive neurological changes to overcome cognitive deficits associated with a neurological disorder, the game delivery system comprising: a computerized game manager configured to assess a game participant and, in response to the assessment, calibrate a training program comprising games for the game participant; the computerized game manager also being configured to administer the games, manipulate a plurality of game stimuli, and receive input from a game piece; and a participant portal that provides remote access to and delivers the games to game participants; wherein the game manager is configured to administer games of the training program to the game participant by: presenting a plurality of target and/or distractor stimuli; prompting the game participant to respond to the target and/or distractor stimuli; receiving the game participant's input through the game piece; and repeating the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range; wherein the game manager is further configured to administer an assessment, using at least one of the plurality of games, by administering a brief version of the game using mid-level game difficulty parameters.

22. The game delivery system of claim 1 , wherein the game piece is at least one of a keyboard, computer mouse, track pad, touch screen, camera, microphone, sensor, and switch.

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9. A method for updating language understanding classifier models, the method comprising: receiving via one or more microphones of a computing device, a digital voice input from a user of the computing device; performing natural language processing using the digital voice input to determine a user voice request; upon determining the user voice request does not match at least one of a plurality of pre-defined tasks in an agent definition of a digital personal assistant running on the computing device: receiving using a graphical user interface of an end-user labeling tool (EULT) of the computing device, a user selection of at least one of the following: an intent of a plurality of available intents and at least one slot for the intent, wherein: the intent is associated with at least one action used to perform at least one function of a category of functions for a domain; and the at least one slot indicating a value used for performing the at least one action; generating a labeled data set by pairing the user voice request and the user selection; selecting a language understanding classifier from a plurality of available language understanding classifiers associated with the agent definition, the selecting based at least on the intent selected by the user; and updating the selected language understanding classifier based on the generated labeled data set.

14. The method according to claim 9 , wherein the user selection comprises the intent, and the method further comprises: selecting the at least one slot automatically, based on the intent and the user voice request.

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1. A sign language action generating device which creates a sign language action for each word string by connecting sign language actions for each word used in a sign language performed by a robot, the robot including, as parts thereof, a body, a head, two arms, two legs, and a controller, each of the latter four parts being connected to the body, the sign language action generating device comprising: a storage unit that stores therein a sign language word database in which a sign language action data which is previously created such that, in units of words, no interference is generated between the parts of the robot used for performing a sign language, the sign language action data being stored in association with a word having the same meaning as a sign language action corresponding thereto; a word string input unit into which a word string is inputted; a trace creation unit that extracts, from the sign language word database, a data on a sign language action for each pair of words which is constituted by two successive words in the word string inputted into the word string input unit, and creates, for the each pair of words, a trace which connects between an end point position of a sign language action having the same meaning as a prior word of the pair of words and a start point position of a sign language action having the same meaning as a posterior word thereof, based on the extracted sign language action data; an interference determination unit that determines that interference is generated between the parts of the robot used when the robot performs a sign language, if a distance between the parts on each of the created traces is not within a prescribed allowable range; an action connection unit that connects sign language actions for words via the traces created in accordance with the inputted word strings such that no interference is generated between the parts of the robot; and an action adjustment unit that, if the interference is determined to be generated between any of the parts of the robot on the trace created for a pair of words, adjusts a position coordinate or a velocity as a sign language action for the pair of words so as to keep the position coordinate or the velocity within an allowable range as well as within a prescribed threshold range which is previously set such that meanings of both the prior word and the posterior word of the pair of words as the sign language action can be maintained.

2. The sign language action generating device according to claim 1 , wherein the action adjustment unit adjusts a position coordinate or a velocity using, as the prescribed threshold range, a threshold range of a shift amount of a prescribed position coordinate or a prescribed velocity, or a threshold range of an evaluation function calculated based on the shift amount.

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20. The method of claim 17 , further comprising performing an ongoing HRBAC model service to the client by receiving updates to permissions granted to users of the client organizational environment and generating revised HRBAC models in response.

17. A method for providing a hierarchical role based access control (HRBAC) model service to a client, the method comprising: receiving an indication of existing permissions granted to users of an organizational environment of the client; analyzing the permissions to create permission characteristics; performing cladistics analysis on the permission characteristics and generating an HRBAC model specifying role perspective relationships between individual users of the client organizational environment; and providing the generated HRBAC model to the client.

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15. A system comprising: a processor to: identify a mapping of a first object to a second object, the first object including code that contains a first code portion and a second code portion, the second object including a graphical model containing a first graphical element and a second graphical element that corresponds to the first graphical element, and the mapping including the first code portion being mapped to the first graphical element, and the second code portion being mapped to the second graphical element; regenerate the first graphical element, the second graphical element, and the second code portion based on the mapping and an edit to the first code portion; and cause a display to present a representation of the regenerated first graphical element and the regenerated second graphical element.

18. The system of claim 15 , where the processor, when regenerating the first graphical element, is further to: receive, from at least one user, information related to modifying the mapping, and regenerate the first graphical element further based the information.

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1. A voice controlled automatic dialer comprising: sound input means; a speech analyzer connected to said sound input means for generating a signal representative of characteristic patterns of an input utterance entered through said sound input means; a first memory for storing a plurality of reference signals representative of predetermined characteristic patterns of utterances of dialing numbers and command words, said predetermined characteristic patterns being representative of utterances common to any users; a second memory for storing a plurality of reference signals representative of specific characteristic patterns of utterances of dialing names defined by authorized users and entered through said sound input means to said speech analyzer after a training process; decision means for comparing the output signal of said speech analyzer with the reference signals stored in said first and second memories and generating a decision output representative of least distances between the characteristic patterns of the input utterance and the characteristic patterns represented by said reference signals; manually operated switch means for coupling the output of said speech analyzer to said second memory when the reference signal representing said dialing names is stored thereinto and coupling the output of said speech analyzer to said decision means during a full-digit dialing mode or abbreviated dialing mode; and means responsive to said decision output for generating a dialing signal for transmission to a switched network.

2. A voice controlled automatic dialer claimed in claim 1, further comprising sound output means and sound generating means repsonsive to said decision output for supplying an audio frequency signal to said sound output means.

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1. A system for dynamically generating a page displaying items of content extracted from sources of content available on a network, the system comprising: a processor; and a memory configured to store processor-executable instructions which when executed by the processor enable a user interface module for allowing a user to (a) navigate to sources of content available on the network, (b) select particular items of content as elements, and (c) build a page composed of the particular items, wherein a plurality of parameters are tracked during step (a), the selected items of content are recorded during step (b), and an indication of how the selected items of content are to be organized is included during step (c); a feature extraction module for automatically creating one or more objects representing the particular items of content on the page built by the user and generating one or more feature extraction tags for each of the one or more objects, wherein the one or more objects are associated with a container tag, and wherein the feature extraction tags comprise at least one container tag and element tags; a content collection module for dynamically generating the page by: extracting the particular items of content from the sources of content via the network using the objects and aggregating the particular items for display on the page by receiving a universal resource locator (URL) and one of the feature extraction tags as a target tag, determining whether the target tag matches the container tag and further determining whether the target tag matches a given one of the objects, and when the target tag matches the container tag and the target tag matches a given one of the one or more objects, information from a web page pointed to by the URL and identified by target tag is passed for display on the page; and a syndication module for sending the page built by the user to a given device, so as to enable the page to be dynamically generated on the given device.

9. The system of claim 1 , wherein the user interface module allows a user to preview the selected items of content.

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31. A method for interactive voice response mapping used in a transaction between a waiting party and a queuing party, the queuing party having a queuing calling system (QCS), the method comprising communicating with the QCS and extracting navigational information from the QCS and at least partially generating an IVR map of the QCS, and further designating at least one queuing party as frequently changing, and performing frequent IVR map validation for the at least one queuing party.

36. The method of claim 31 , further allowing an editor to perform at least one of correcting mistakes in an automated speech-to-text conversion process, removing text that is not relevant for visual navigation, correcting the structure of an IVR map via adding, and removing or changing commands.

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32. The computer program product of claim 31 , the computer-readable storage medium further comprising: program code for determining whether the obtained date value is consistent with rules related to the attribute.

31. A computer program product comprising a computer-readable storage medium, for resolving ambiguities in date values associated with an attribute of an entity, the computer-readable storage medium comprising: program code for obtaining a first text string associated with an attribute of an entity, wherein the first text string is extracted from a first web document; program code for determining that the first text string conforms to one or more date formats; program code for assigning a first confidence value for each of the date formats for the first text string based on a first number of unknown variables that remain when interpreting the first text string using each of the date formats; program code for obtaining a second text string associated with the attribute of the entity, wherein the second text string is extracted from a second web document; program code for determining if that the second text string conforms to one or more of the date formats; program code for assigning a second confidence value for each of the date formats for the second text string based on a second number of unknown variables that remain when interpreting the second text string using each of the date formats; program code determining a first date string expressed in a date format with a highest first confidence value for the first text string; program code determining a second date string expressed in a date format with a highest second confidence value for the second text string; and program code for merging a first subset of the first date string and a second subset of the second date string to obtain a date value for the attribute.

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11. A system of categorizing items to be sold by a retailer, the system comprising: a computer comprising one or more physical processors programmed to execute one or more computer executable instructions which, when executed by the one or more physical processors, cause the computer to: obtain an item attribute that describes an item to be sold by the retailer; obtain a data structure of the retailer that describes a plurality of categories including a first category and a second category of items sold by the retailer, wherein the data structure comprises a hierarchy that describes an association between the first category and the second category; determine that the item belongs to the first category based on the data structure of the retailer and the item attribute; determine that the item is associated with the second category based on the hierarchy and the first category; and provide an indication of the first category and the second category.

20. The system of claim 11 , wherein the second category includes the first category as a sub-category of the second category.

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8. The method of claim 1 wherein automatically translating the caption text comprises passing the source caption text as a parameter to a translation application-programming interface (API).

1. A computer-implemented method to provide automated translation of video captions and playback to one or more clients, the method comprising: receiving an indication of a video that includes associated caption text; identifying a source language associated with the caption text without playing the video; selecting a target language to which to translate the associated caption text from the identified source language; automatically translating the caption text from the identified source language to the selected target language without playing the video; storing the translated captions in a caption file after automatically translating the caption text; repackaging the received video and translated captions so that the video can be played with the new captions; and playing the received video and displaying each translated caption at appropriate points during the video, wherein the preceding steps are performed by at least one processor.

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11. At a computer system including one or more processors and system memory, a method for determining if a reference that is to be created or modified is a member of a set, the method comprising: an act of receiving a resource request corresponding to a specified resource; an act of accessing one or more membership conditions for the set, the one or more membership conditions having been previously translated from a set definition defining the set, matching at least one of the one or more membership conditions being an indication of membership in the set, each membership condition including one or more membership condition statements that are to be satisfied for a resource to match the membership condition, each membership condition statement including: a referent field, an attribute field, an operator field, and a value field that collectively represent the membership condition statement, each of the referent field, attribute field, operator field, and value field being defined within the membership condition grammar as: <Referent>::=<Referent Reference><Attribute>, <Attribute>::=a name of an attribute of a resource identified by an expression to its left, <Operator>::=<Relational Operator>|<Inverted Operator>, and <Value>::=<Literal Value>|<Function Value>|<De-referenced Value>, and further: the attribute field naming an attribute, the operator field indicating a relational operator, the value field representing a value, the referent field indicating a referent, the referent referring either directly to the resource currently being evaluated for membership in the set or to another resource that is related in some way to the resource that is currently being evaluated for membership in the set; for each of the one or more membership condition statements, an act of evaluating the named attribute of the specified resource against the value in the value field in view of the operator in the operator field to determine if the specified resource satisfies the membership condition statement; an act of determining that the specified resource satisfies membership condition statements for at least one of membership conditions based on the evaluations; an act of matching the specified resource to the condition statement as a result of the specified resource satisfying membership condition statements for the at least one of the membership conditions; and an act of including the specified resource as a member of the set in response to the specified resource matching the condition statement.

15. The method as recited in claim 11 , wherein the operator field indicates a relational operator selected from among: <, >, <=, =>, ==, and !.

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13. A method comprising: using an electronic message to manage changes to be made to a document, wherein one or more changes to be made to the document are viewable within a body of the electronic message; using a reply to the electronic message that includes a received change made directly from within the body of the electronic message and made outside of the document that is to be incorporated into the document; and after receiving the reply, automatically incorporating the received change into the document.

14. The method of claim 13 , further comprising displaying each change within a separate section of the electronic message including displaying a portion of document text before and/or after each change.

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19. The computer-implemented method of claim 3 , further comprising: determining at the server, for each document, a path length score from a path of the document; wherein determining the usage score from the frequency of visit value and the unique visit value associated with the document comprises determining the usage score from the frequency of visit value and the unique visit value associated with the document and the path length score of the document.

3. A computer-implemented method comprising: identifying at a server a plurality of documents responsive to a search query, wherein the plurality of documents include at least one document visited by multiple distinct counted visitors during a time period; accessing, at the server, usage information associated with the plurality of documents, the usage information including, for each document, (i) a frequency of visit value based on a total number of times the respective document was visited by all counted visitors visiting the document during a time period, and (ii) a unique visit value based on a number of unique visitors among all counted visitors visiting the respective document during the time period; determining at the server, for each document, a usage score from the frequency of visit value and the unique visit value associated with the respective document; and organizing at the server the plurality of documents based, in part, on the usage scores for the documents.

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16. The node of claim 13 , further comprising a hangover addition block configured to produce said speech decision based on said primary speech decision, wherein the speech decision further is based on the music decision which is provided to the hangover addition block.

13. A node in a telecommunication system comprising a voice activity detector comprising: a first primary voice detector; a feature extractor; a background estimator, said voice activity detector being configured to output a speech decision (vad_flag) indicative of the presence of speech in an input signal based on at least a primary speech decision (vad_prim_A) produced by said first primary voice detector, the input signal being divided into frames and fed to the feature extractor, said primary speech decision being based on a comparison of a feature extracted in the feature extractor for a current frame of the input signal and a background feature estimated from previous frames of the input signal in the background estimator; said first primary voice detector having a memory in which previous primary speech decisions are stored, said voice activity detector further comprises a short term activity detector, said voice activity detector is further configured to produce a music decision (vad_music) indicative of the presence of music in the input signal based on a short term primary activity signal (αvad_act_prim_A) produced by said short term activity detector based on the primary speech decision produced by the first primary voice detector, said short term primary activity signal is proportional to the presence of music in the input signal, said short term activity detector is provided with a calculating device configured to calculate the short term primary activity signal based on the relationship: vad_act ⁢ _prim ⁢ _A = m memory + current k + 1 where vad_act_prim_A is the short term primary activity signal, m memory+current is the number of active decisions in the memory and current primary speech decision, and k is the number of previous primary speech decisions stored in the memory.

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21. A memory section for an electronic controller which performs inference operations according to rules, each rule comprising at least one preposition and at least one implication, wherein a membership function, defined for a finite number of points of a universe of discourse, appears in the preposition of at least one of the rules, the membership function having a value for each of the finite number of points, which value is indicative of a degree of membership, wherein the memory section stores for each point of the finite number of points the values of only those membership functions for the point which are not zero.

22. The memory section of claim 21 which stores, for each point of the finite number of points, a memory word comprising an indication of the membership functions with non-zero values for the point and the corresponding non-zero values.

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7. The method of claim 6 , wherein the input concept object is provided by a third third-party developer, the intermediate concept object is provided by a fourth third-party developer, and the output concept object is provided by a fifth third-party developer.

6. A computer-implemented method for a dynamically evolving cognitive architecture system based on third-party developers, the method comprising: matching a first object and a second object with a user input, the first object comprising one of an input action object, an input concept object and an output concept object, the second object comprising another one of the input action object, the input concept object, and the output concept object; forming an intent based on the user input; creating a plan based on the intent, the plan comprising the input action object selected from a plurality of action objects and provided by a first third-party developer that transforms the input concept object associated with the intent into an intermediate concept object, and the output action object selected from the plurality of action objects and provided by a second third-party developer that transforms another intermediate concept object into the output concept object associated with a goal of the intent, the other intermediate concept object being one of the same as the intermediate concept object and different from the intermediate concept object; executing the plan, and outputting a value associated with the output concept object to a user interface associated with the user input.

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8. The method as recited in claim 1 , wherein the business capability is received in response to receiving a decision for responding to a change trigger event from normal operations of a course of business for the organization.

1. In a computer architecture including at least one processor, a method, performed by the at least one processor, for determining whether a change should be made to the adaptability of a business capability, the method comprising: an act, performed by the at least one processor, of receiving a business capability for a first organization, wherein the business capability has an associated adaptability indicating the business capability's ability to adapt, the adaptability being defined according to a common vocabulary for business capability adaptability that is employed by a plurality of organizations to represent the adaptability of a business capability of each organization, the common vocabulary comprising an adaptability spectrum that defines a range of business adaptability including a first adaptability that indicates that the corresponding business capability is ready to adapt to changing requirements within specified time constraints, a second adaptability that indicates that the corresponding business capability is ready to adapt to changing requirements, and a third adaptability that indicates that the corresponding capability is not ready to adapt to changing requirements; an act, performed by the at least one processor, of determining that the performance of the received business capability can be improved by changing the adaptability of the business capability, including: comparing the performance of the received business capability to one or more performances of one or more different versions of the received business capability, the received business capability having an associated adaptability from the adaptability spectrum that is different than the adaptability associated with the received business capability, wherein at least one of the different versions of the received business capability is a business capability from a second organization that uses the common vocabulary to define the business adaptability of at least one of the different versions; and identifying that a first of the different versions of the received business capability would provide better performance than the received business capability; and an act, performed by the at least one processor, of applying one or more defined adaptability changes to the received business capability to change the adaptability of the received business capability in accordance with the adaptability of the first of the different versions of the received business capability.

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94. The computer program product of claim 86, wherein the definition of additional content includes a function to be evaluated in context with an element to which the definition is applied.

86. A computer program product for producing a digital form of a digital document, wherein the document can be one of several different types and with varying content, the product comprising: a computer readable medium having computer program logic stored thereon, wherein the computer program logic defines: a data requesting component which produces a request for at least part of a document at an output; a data access component which accesses a definition of additional content for a type of the document; a data generation component which receives the type of the document as an input and produces additional content at an output, wherein the data processing component generates the additional content according to the definition of additional content for the type of the document; and a data processing component which receives a selected portion of the content of the document at one input and the output of the data generation component at another input and produces a digital form of the document at an output, wherein the portion was selected in accordance with the request, and wherein the data processing component combines the additional content and the content of the selected portion.

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11. A method for controlling an alarm system, comprising: providing a packet data network interface port; communicating, by an automated controller, with security alarm sensors through a security alarm system interface port; receiving, by the automated controller, at least one input from the security alarm system interface port; processing, by the automated controller, the at least one input to determine an alarm condition; and communicating, by the automated controller, information defining a markup language interface comprising the alarm condition through the packet data network interface port.

13. The method according to claim 11 , further comprising communicating information defining an environmental system control markup language interface through the packet data network interface port, for controlling an environmental control system.

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8. A conversation based search system, functioning as a search engine, for searching the internet from a user terminal, comprising: an utterance section configured to extract a keyword from an initial query input into a search window by a user through the user terminal, wherein the search system is configured to search the internet for documents, wherein the documents are comprised of websites, web data and databases, and to propose at least one predetermined utterance phrase corresponding to the initial query, based on the extracted keyword, wherein the predetermined utterance phrase has been selected from a database that includes a plurality of keywords stored therein, with each of said keywords being associated, in the database, with at least one utterance phrase; and wherein the utterance section is configured to present the utterance phrase associated with the extracted keyword to the user via the user terminal into the search window, and further wherein the utterance section is also configured to receive an answer to the presented utterance phrase from the user by a touch on a touch-detection surface separated from the search window; a search section configured to reform the initial query based on the answer of the user to the utterance phrase that was proposed to the user by the search system, provide the reformed query to the search window, search the internet based on the reformed query, and offer a search result to the user via the user terminal, where the search result corresponds to the search based on the reformed query, wherein the search result includes a listing of a plurality of websites, wherein searching the internet based on the reformed query is performed after receiving the user's answer to a final utterance phrase presented to the user, without conducting a search of the internet based on the initial query, and wherein the reformed query is always made from the answer from the user to the utterance phrase in combination with at least one of the keywords contained in the initial query.

9. The system according to claim 8 , wherein, when a plurality of the utterance phrases are proposed, the utterance section proposes the utterance phrases one by one in sequence.

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2. The system of claim 1 , wherein the controlled access is through the UI and includes remote interactive manipulation of the reaction data synchronized to corresponding events of the media instance.

3. The system of claim 2 , wherein the manipulation includes at least one of dividing, dissecting, aggregating, parsing, organizing, and analyzing the reaction data.

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5. The method of claim 1 , wherein the creating of the new reordering file comprises assigning orientation types to the extracted phrase pairs from a predefined set of at least two orientation types.

8. The method of claim 5 , wherein the update of the reordering model comprises updating occurrences of each of the orientation types of each of the phrase pairs stored in the reordering table.

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14. A computer-implemented method that facilitates providing a query result with context, comprising: employing a processor to execute computer-executable instructions stored on a computer-readable medium to perform the following acts: receiving one or more query search terms targeted toward data; when the data comprises at least one data item including audio or video formatting, transcribing the audio or video formatting to locate the one or more search terms of the query in the data item; providing a query result identifying one or more data items; generating a search term location graph for each of the one or more data items, the search term location graph identifying locations within the data item of occurrences of the one or more search terms; and transmitting instructions to display the query result, including the identified one or more data items and corresponding search term location graphs, when the query result identifies a single data item, transmitting instructions to display the query result together with the search term location graph, wherein the search term location graph is integrated into a vertical scroll-bar having a partially transparent scroll thumb; and when the query result identifies a plurality of data items, transmitting instructions to display at least two of the plurality of data items together with the corresponding search term location graphs, wherein each search term location graph is displayed between the edges of one of a scroll-bar or slider.

15. The method of claim 14 , wherein the one or more data items comprises one or more of an electronic book, a book, an electronic book file, an electronic magazine, a magazine, an electronic magazine file, an electronic periodical, an electronic periodical file, a periodical, a one-dimensional electronic document, a one-dimensional file, an electronic document, a web page, a web site, an email, an audio file, a video file, data with a slider for navigation, data with a scroll-bar for navigation, an electronic file, a word-processing document, a text document, an audio clip, a video clip, or an instant messenger message.

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20. The method of claim 1 , wherein the different layout is displayed during a relevant timeframe associated with the data set.

1. A computer-implemented method, comprising: receiving a search query from a user, the search query including a keyword associated with a first category; accessing a data set that includes one or more items of the first category, one or more categories of the items, and historical data representing one or more actions of other users associated with the items; determining, by a computer system, at least one related category related to the data set from the one or more categories of items; determining that a frequency of the at least one related category is greater than a first threshold, the frequency determined by historical data representing selection of an item in the at least one related category by the other users after the other users have submitted the search query and received and accessed the data set; determining, by the computer system, a conversion rate for the at least one related category by the other users, the conversion rate representing an intended or actual purchase of the item in the related category, the conversion rate greater than a second threshold; when the frequency of the at least one related category is greater than the first threshold and the conversion rate is greater than the second threshold, providing data associated with the at least one related category to the user, the data provided including a navigation strip that is tailored to the at least one related category but not the first category; and adjusting a user experience based at least in part on the data and on the frequency, the user experience being adjusted at least by providing a different layout including the navigation strip on a user interface to browse through the data set that corresponds with the at least one related category but not the first category.

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1. A conversation processing method, comprising: acquiring task-related user requirement data; updating a user conversation state based on the user requirement data and a pre-configured task-related task parameter, the pre-configured task-related task parameter comprising multiple slots to indicate states of task parameters; generating at least one piece of candidate action data according to the user conversation state; and generating response text data according to the at least one piece of candidate action data, wherein the user requirement data comprises a parse result obtained by natural language parsing of text data of a user requirement, wherein the updating the user conversation state based on the user requirement data and the pre-configured task-related task parameter comprises: assigning a default or a null value to the multiple slots of the pre-configured task-related task parameter based on the parse result, wherein the default value is determined from a task customization condition or a user model information; generating a conversation parameter based on the pre-configured task-related task parameter and situation prior information; and updating the conversation parameter according to the parse result, and wherein generating the at least one piece of candidate action data according to the user conversation state comprises: checking whether the user conversation state includes an ambiguous slot or an ambiguous value; and generating a clarification candidate action in response to determining that an ambiguous slot or an ambiguous value is included in the user conversation state.

9. The method of claim 1 , wherein the updating the conversation parameter according to the parse result further comprises: performing a data conflict detection on a value of the conversation parameter to be updated, and emptying the value of the updated conversation parameter or sending a message for confirming whether the value of the conversation parameter to be updated is correct in response to a data conflict being detected.

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2. A method comprising: displaying a tabstrip widget including at least first and second tabs, each of the at least first and second tabs further including a tab conditions panel and a tab summary panel, the tab summary panel configured to display a first statistic associated with a term of a Boolean expression defined by the corresponding tab conditions panel, a first update element operable to, in response to user selection, update the first statistic, a second statistic associated with the entire Boolean expression, and a second update element operable to, in response to user selection, update the second statistic, and the tabstrip widget being configured to display one tab conditions panel of the at least first and second tabs at a time; receiving a first user input defining a first term of a Boolean expression including a first number of condition statements; displaying the first term of the Boolean expression in the tab conditions panel of the first tab; superimposing the tab conditions panel of the second tab on the tab conditions panel of the first tab; receiving a second user input defining a second term of the Boolean expression including a second number of condition statements, the second number of condition statements being different than the first number of condition statements; displaying the second term of the Boolean expression in the tab conditions panel of the second tab; in response to user selection of the first update element included in the tab summary panel of the second tab, updating the first statistic included in the tab summary panel of the second tab based on the second term of the Boolean expression including the second number of condition statements; in response to user selection of the second update element included in the tab summary panel of the second tab, updating the second statistic included in the tab summary panel of the second tab based on the entire Boolean expression defined by the first term of the Boolean expression including the first number of condition statements and the second term of the Boolean expression including the second number of condition statements; and outputting data satisfying the first and second terms of the Boolean expression.

4. The method of claim 2 , further comprising receiving user selection indicative of the second tab, wherein the tab conditions panel of the second tab is superimposed on the tab conditions panel of the first tab based upon receiving the user selection.

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3. The metric-converter watch device of claim 1 , wherein the clock is a digital clock on a screen.

1. A metric-converter watch device comprising: (a) a watch housing having a first side, a second side, a third side, a fourth side, a top surface, and a bottom surface; wherein a cavity is disposed on the top surface; wherein a battery compartment may be disposed in the bottom surface of the housing, wherein a battery is disposed in a battery compartment; and (b) a watch panel having a first side, a second side, a third side, a fourth side, a top side, and a back side, wherein the watch panel is pivotably attached to the watch housing such that the watch panel is pivotably moveable between an open position and a closed position, wherein the watch panel resides entirely within the cavity at the closed position such that the top side of the watch panel aligns with the top surface of the watch housing; wherein a functioning clock is disposed on the top side of the watch panel and a back side screen is disposed on the back side of the watch panel; (c) an inside touch screen disposed within the cavity of the watch housing, wherein the inside touch screen faces the back side screen when the watch panel is at the closed position; wherein when the touch screen is powered on, a first conversion icon, a second conversion icon and a plurality of touch screen keypad icons are displayed on the touch screen; (d) a microprocessor disposed within the watch housing, wherein the microprocessor is operatively connected to the battery, the back side screen, the touch screen; wherein when the first conversion icon, the second conversion icon or the touch screen keypad icons are pressed, the touch screen generates corresponding input signals and sends the input signals to the microprocessor; wherein the microprocessor is configured to perform mathematical operations and configured to convert a first English numeric value to a first metric numeric value and convert a second metric numeric value to a second English numeric value, wherein the microprocessor is configured to: receive a first numeric value input from the touch screen when one or more keypad icons are depressed, subsequently generate a first output command to the back side panel to display the first numeric value on the back side panel as a first English numeric value; subsequently receive a first input signal from touch screen when the first conversion icon is depressed, subsequently calculate a first metric numeric value by multiplying the first English numeric value by a first conversion factor, and the microprocessor then generates a second output command to the back side screen to display the first metric numeric value; and receive a second numeric value input from the touch screen when one or more keypad icons are depressed, subsequently generate a third output command to the back side panel to display the second numeric value on the back side panel as a second metric numeric value; subsequently receive a second input signal from touch screen when the second conversion icon is depressed, subsequently calculate the second English numeric value by multiplying the second metric numeric value by a second conversion factor, and the microprocessor then generates a fourth output command to the back side screen to display the second English numeric value.

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24. The non-transitory computer program product of claim 23 , the at least one program further including instructions for crawling the respective website at a rate no greater than the current crawl rate limit for crawling the respective website.

23. A non-transitory computer readable storage medium storing at least one program for execution by a computer system, the at least one program comprising instructions for: storing, for each website of a multiplicity of websites, a corresponding current crawl rate limit; comparing a maximum crawl rate for the respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; and performing a website crawling management function in accordance with the determination of whether the current crawl rate limit is the limiting factor in crawling the respective website; and providing a crawl rate control mechanism to a respective owner of the respective website, wherein the crawl rate control mechanism enables selection of a new crawl rate limit corresponding to the respective website by the respective owner.

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1. A computer-implemented method executed by a processor that performs operations for reducing ambiguities present in electronically stored words, the operations comprising: receiving a plurality of characters in electronic form, the received plurality of characters corresponding to a sequence of words and including an ambiguous word that has one or more characters whose value is substantially uncertain; comparing at least some of the words in the sequence to a first ontology, the first ontology defining a plurality of nodes, each node being associated with a word, and each node being connected to at least one other node by a link, each link being associated with a concept that relates the words associated with the nodes connected by the link in a predetermined context, wherein at least some of the nodes are associated with non-textual image information that identifies an enhancement to character-based text.

9. The method of claim 1 , wherein the operations further comprise: identifying nodes in the first ontology that correspond to the ambiguous word based on the comparison to the first ontology; comparing at least some of the words in the sequence to a second ontology, the second ontology defining a plurality of nodes, each node being associated with a word, and each node being connected to at least one other node by a link, each link being associated with a concept that relates the words associated with the nodes connected by the link in a predetermined context, wherein at least some of the nodes are associated with non-textual image information that identifies an enhancement to character-based text; identifying nodes in the second ontology that correspond to the ambiguous word based on the comparison to the second ontology; scoring each of the identified nodes from the first ontology and the second ontology, wherein the scoring is at least partially based upon non-textual image information that identifies an enhancement to character-based text and is associated with at least some of the identified nodes; and selecting a node having the highest score from among the identified nodes in the first ontology and the second ontology.

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8. A computer-implemented data processing method of providing one or more activities to subsequent viewers of a piece of multimedia in a time-shifted manner according to an activity map, comprising: identifying, by one or more activity management servers, a plurality of segments that make up a piece of multimedia; receiving, by the one or more activity management servers, a plurality of activities from one or more users prior to a first time, each particular activity of the plurality of activities being associated with a respective particular segment of the plurality of segments; generating, by the one or more activity management servers, an activity map for the piece of multimedia based at least in part on the plurality of segments, the activity map indicating: the association between each particular activity of the plurality of activities and the respective particular segment of the plurality of segments; and one or more associations between one or more particular activities of the plurality of activities and one or more other activities of the plurality of activities; receiving, by the one or more activity management servers, from a client device, a first request to display one or more activities associated with the piece of multimedia; in response to the first request, generating a graphical display of the one or more activities associated with the piece multimedia based at least in part on the activity map, the graphical display comprising a word cloud generated based at least in part on a graphic density of one or more particular words that appear in the one or more activities; and causing the client device to display the graphical display.

13. The computer-implemented data processing method of claim 8 , wherein generating the graphical display comprises determining which of the one or more activities to display based at least in part on one or more factors selected from the group consisting of: an activity density for each of the plurality of segments, and a type of activity that makes up the activity density for each of the plurality of segments.

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8. The apparatus of claim 4 wherein the program instructions are further configured to: generate a readable data table of the one or more electronic documents from a user's tabulation definition inputs; generate a textual entry from each datum of said readable data table; and generate the one or more glossary components from each textual entry.

4. The apparatus of claim 1 , wherein each said electronic document further comprises: one or more narrative components, one or more reference components, one or more glossary components, and one or more index components.

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26. The computer-readable storage media of claim 21 , wherein the instructions to calculate result weights further comprise instructions to: calculate the result weights further based on a log file of frequently selected programs.

21. One or more tangible non-transitory computer-readable storage media for storing computer-executable instructions executable by a computer system, the media storing one or more instructions to: receive, at an interactive program guide, search criteria from a client device; receive, at the interactive program guide and from the client device, a user identifier and a selection from predetermined genres, wherein the predetermined genres are mapped to a set of television programming; determine, with the interactive program guide, one or more search results in response to the search criteria, the user identifier and the selection from the predetermined genres; query one or more databases of attributes with portions of the search results, wherein the attributes include genre terms; compare each of the search results to the attributes to determine matches between selection from the predetermined genres, the portions of the search results and the genre terms; customize search result attribute correlations and correlation weights for each of the search results based on the user identifier, matches between 1) the portions of the search results, 2) the genre terms and 3) the selection from predetermined genres; calculate result weights for each of the search results by summing the correlation weights associated with each search result; sort the search results so the search results are returned in order of relevance according to the result weights; and return the search results.

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18. The computer storage medium according to claim 15 , wherein said component is similar but not exactly the same as a component in said prototype information.

15. A computer storage medium storing thereon computer executable instructions configured to process text, comprising: an instruction configured to assign a label to a component according to a probabilistic model, wherein said probabilistic model includes incorporated prototype information; an instruction configured to determine whether said component is included in said prototype information; if said component is included in said prototype information, using said prototype information in said probabilistic model, otherwise not using said prototype information in said probabilistic model; and an instruction configured to store said label assigned to said component.

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1. A system for managing form-generated data related to a patient encounter, the system comprising: a form having designated information fields at different locations on the form; an electronic writing system configured to generate location information that identifies the location of a user writing on the form; a contextualizer configured to translate location information related to the user writing to a contextualized data element, wherein the contextualized data element comprises contextual information that is associated with the user writing, wherein the contextualizer includes a mapping data set that maps user areas on the form to labels that are associated with the designated information fields and wherein the contextualizer is configured to identify a label from the location information by comparing the location information to the mapping data set, the contextualized data element comprising the label; and an Electronic Medical Record (EMR)/Electronic Health Record (EHR) application that utilizes the label in the contextualized data element to perform a function that is related to the user writing on the form; wherein the contextualized data element is distributed to the EMR/EHR application via a publish/subscribe protocol in which the EMR/EHR application subscribes to a specific contextualized data element by identifying the label associated with the contextualized data element.

9. The system of claim 1 wherein the contextualizer is configured such that the mapping data set is changeable in response to changes in the locations of the designated information fields on the form.

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10. The method of claim 7 wherein the display windows are enabled by the processing system with an text hide option, and further including the step of: selecting the text hide option so that no text is displayed in the image grouping display windows.

7. A method of translating from one language selected by a user to another language selected by the user and using a processing system, the system having: an image library with a plurality of usage based image groupings wherein each image grouping has a plurality of images therein, each such image representing a word or phrase in such image grouping; and wherein each such image grouping has one or more translation text sub-libraries for each translation language the user can select; and wherein, each such translation text sub-library for an image grouping, contains a generic text for each image in the image grouping in such translation language and which is coupled to its respective image when the user selects such specific language as a ‘translation from’ language; and wherein each such image grouping has one or more translation audio sub-libraries for each translation language the user can select; and wherein, each such translation audio sub-library for an image grouping, contains a generic audio for each image in the image grouping in such translation language and which is coupled with its respective image when the user selects such specific language as the ‘translation from’ language; and one or more user devices coupled to the processing system wherein the display screens of the user devices are configured by the processing system with: a menu window for displaying a listing of the usage based image groupings from which the user can select, an identifier symbol coupled to each such image grouping and a language selection option for the user to select a language for the listing of the image groupings displayed in the menu window; one or more display windows for the usage based image groupings selected by the user; and one or more user work windows; the method of translating comprising the steps of: selecting a translation language for the listing of usage based groupings displayed in the menu window and the ‘translation from’ language for the generic text and audio coupled to and with the images in the image groupings to be displayed in the display windows; selecting, in the menu window, one or more usage based image groupings, the images of each such selected image grouping thereby being displayed in the display windows with the generic text and audio for each image in the selected ‘translation from’ language coupled thereto and therewith; selecting, in the display windows, one or more images with generic text and audio in the selected ‘translation from’ language coupled thereto and therewith, for placement and display in one or more of the user work windows and wherein the usage based image grouping identifier symbol for each such selected image is also coupled to such image and displayed in the user work windows; arranging, in one or more of the user work windows, the order of the selected usage based images; and selecting, in one or more user work windows, a ‘translation to’ language wherein the text and the audio language coupled to and with such work windows is changed from the ‘translation from’ language to the ‘translation to’ language and wherein, in response to the ordering of the images and the presence of images from certain image groupings in such user work windows, the system grammatically adjusts the text and audio to an applied ‘translation to’ language.

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2. The method of claim 1 , further comprising: receiving, by the computer system, from the user a selection of one of the plurality of candidates to represent the second portion of the text; and storing, by the non-transitory computer-readable storage device, the selection.

3. The method of claim 2 , further comprising creating, by the computer system, the electronic file comprising the digital characters representing the first portion of the text and the selection.

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17. The method of claim 1 , wherein the classification permits a first data element to be annotated with a label comprising information derived from the label of a second data element which is neither a parent node nor a child node of the first data element in the dependency network.

1. A method for annotating a document comprising: for a plurality of different types of data element, modeling data elements of an input document and dependencies between the data elements as a dependency network, at least some of the data elements being associated with a label; defining static features of at least some of the data elements, the static features each expressing a relationship between a characteristic of the data element and its label; defining a set of dynamic features, each of the dynamic features defining a link between a label of a first data element in a pair of the data elements and a label of a second data element in the pair of data elements; learning parameters of a collective probabilistic model for the document, the parameters expressing, for each of a plurality of the data elements, a conditional probability that the data element should be labeled with a neighbor label comprising information derived from a label of another data element linked to the data element by a dynamic feature, the learning including training a set of local learning models to generate estimations of the neighbor labels for at least one of the data elements based on static features and stacking the local learning models with higher level models to refine the estimations; and collectively classifying data elements in the collective probabilistic model based on the learned parameters, whereby at least some of the data elements are each annotated with a label comprising information derived from the label of another element.

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1. A method for navigating a group of information in a computer system, comprising the steps of: identifying said group of information associated with a selected data item; converting certain pieces of said group information into generated data items; associating unilateral and multilateral display relationships with said generated data items, each unilateral display relationship representing a direct relationship between two of said generated data items, and said multilateral relationships also representing an indirect relationship with other generated data items; associating unilateral and multilateral display relationships with said generated data items and said selected data item, each unilateral display relationship representing a direct relationship between said selected data item and one of said generated data items, and said multilateral relationships also representing an indirect relationship between said selected data item and said generated data items; and forming a display associated with said selected data item, including said generated data items, wherein said display distinguishes between said selected data item and said generated data items.

4. The method claimed in claim 1, wherein said step of converting certain pieces of said group information into generated data items further comprises the step of: converting certain pieces of said hierarchical group of information into a non-hierarchical group of information.

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2. The method of claim 1 , wherein translating the parametric query into the keyword search entry includes determining at least one search interval.

3. The method of claim 2 , wherein the operator is based on the search interval.

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20. The system of claim 19 , further comprising means for determining a return value of the function of the computational model based on the one or more method descriptions.

19. The system of claim 16 , further comprising means for determining a function of the computational model based on one or more method descriptions.