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12. A system configured to route a facsimile, the system comprising a processor and logic in and/or executable by the processor to cause the processor to: receive text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by ascertaining a position of one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text of the facsimile for at least one of a meaning and a context of the text; route the facsimile or text thereof to one or more destinations based on the analysis; initiate a business process based on the analysis; detect a problem with the business process; generate a notification of the problem; and notify one or more entities of the problem, wherein the routing utilizes an outgoing communication device.

19. The system as recited in claim 12 , wherein at least one of the destinations corresponds to an intended recipient of the facsimile.

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10. The method of claim 1 , further comprising outputting in a list at a second location on the display the other disambiguated interpretations.

1. A method of enabling input on a handheld electronic device that comprises an output apparatus comprising a display, a memory having stored therein a plurality of stored words and a disambiguation routine structured to disambiguate ambiguous text input, and an input apparatus comprising a plurality of input members that comprise a multiple-axis input device and a number of linguistic input members, at least some of the linguistic input members each having a plurality of linguistic elements assigned thereto, the method comprising: detecting an ambiguous input comprising a number of linguistic input member actuations; deriving a plurality of disambiguated interpretations of the ambiguous input, at least one of the plurality of disambiguated interpretations being an orphan prefix which consists of k linguistic elements, k being the number of linguistic input member actuations, wherein the orphan prefix is different from the first k characters in each of the plurality of stored words; displaying one of the disambiguated interpretations as an output at a first location on the display; detecting an input from the multiple-axis input device; and responsive to each input from the multiple-axis input device, replacing the output at the first location on the display with a successive disambiguated interpretation from the plurality of disambiguated interpretations.

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14. The system of claim 13 , wherein the information relating to the user's interaction with the resource comprises information indicating one or more of a linger time, a user selection, a query term entered by the user, or a transaction completed by the user.

13. The system of claim 9 , the operations comprising: receiving information relating to a user's interaction with the particular resource; and updating the information about the user based on the information.

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9. The method of claim 1 , further comprising: receiving input to change at least one display property of digital content; and rendering a new portion of digital content based on the at least one display property that is changed, wherein the rendered new portion of digital content corresponds to a text unit that was most recently played or most recently compiled to be played.

1. A method for synchronizing the playing and displaying of digital content in an electronic device, comprising: inserting bookmarks into a segment of digital content that is to be played by a text-to-speech engine, wherein each bookmark is associated with a particular position in the digital content; rendering a first portion of digital content for display on the electronic device; displaying the rendered first portion of digital content on the electronic device; determining a position of a last word in the rendered first portion of digital content; playing the segment of digital content as audio using the text-to-speech engine; processing the bookmarks as the segment of digital content is being played; comparing a current bookmark with the position of the last word in the rendered first portion of digital content; and rendering a second portion of digital content for display when the current bookmark is greater than the position of the last word in the rendered first portion of digital content.

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1. A computer-implemented method comprising: receiving a first search query from a first member of a member network; responding to the first search query with a first result set that is based on the first search query and that comprises a plurality of electronic articles and, for one or more electronic articles of the plurality of electronic articles, rating information that corresponds to the one or more electronic articles, and a rating system control that corresponds to a particular one of the plurality of electronic articles, wherein the rating system control is a selectable item adapted to receive an endorsement rating regarding the corresponding particular one of the plurality of electronic articles, and wherein the rating information comprises text or indicia that indicates a prior selection by one or more members of the member network of rating system controls corresponding to the one or more electronic articles of the plurality of electronic articles; receiving a selection, by the first member, of the rating system control that corresponds to the particular one of the plurality of electronic articles; updating, based on the received selection of the rating system control that corresponds to the particular one of the plurality of electronic articles, the rating information that corresponds to the particular one of the plurality of electronic articles; receiving a second search query from a second member of the member network; and responding to the second search query with a second result set based on the second search query, wherein the second result set comprises the particular one of the plurality of electronic articles and, based on the second member's membership in the member network, the second result set comprises the updated rating information that corresponds to the particular one of the plurality of electronic articles.

10. The method of claim 1 , further comprising: ranking the second local result set presentation using a strength of relationship factor for an association between the first member and the second member in the member network.

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7. The method of claim 1 , wherein each of the plurality of assertions in the assertion base are defined based on at least one of: (i) user input, and (ii) auto-retrieval of one or more existing assertions.

1. A method, comprising: selecting, based on a context relating to a domain of a regular expression, an ontology and an assertion base; parsing the regular expression to identify at least one fragment of the regular expression; identifying one or more assertions in the assertion base corresponding to one of the identified fragments; identifying, for each identified assertion, an associated node in the ontology; and returning, based on the associated nodes, a concept in the ontology as representing the associated fragment of the regular expression.

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28. A computer accessible storage hardware having stored thereon computer-executable instructions for providing application layer functionality between one or more database clients and one or more database servers, the computer executable instructions operable to: at a decoding layer above a network layer at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; extract query-language statements from the database messages; at a decoding layer above a network layer at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations: receiving database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decoding the database messages; and extracting query-language statements from the database messages; at an application layer above the decoding layer, a caching application operable for: receiving query-language statements extracted at the decoders comprising queries; receiving query-language statements extracted at the decoders comprising query results corresponding to the queries; and recording the queries and the query results corresponding to the queries in a cache residing at the first network location wherein the queries are associated with a corresponding query result; and a monitoring application operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders, wherein at least one observation is associated with a query result stored in the cache and communicate one or more observations associated with the queries to one or more computing systems at a fourth network location according to the needs of the one or more computer systems, wherein at least one of the computer systems maintains a web cache and is operable to modify the web cache based upon the communicated observations wherein observations on the database messages based at least in part on the query-language statement extracted at the decoders comprise the following: subject database instances of the query-language statements; network protocols and versions of the network protocols used to communicate the database messages; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; devices hosting the clients; and a number of queries communicated from each of the clients to each of one or more database instances; and at an application layer above the decoding layer at the first network location, process the query-language statements extracted at the decoding layer.

40. The computer accessible storage hardware of claim 28 , wherein the network layer comprises a Transport Control Protocol over Internet Protocol (TCP/IP) interface or an Interprocess Communication (IPC) interface.

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12. The non-transitory media of claim 10 , wherein the method further comprises receiving input from a user for changing in the text in the source language at least one word indicated as potentially erroneous and displaying, by a processor, resembling substitution alternatives for the at least one word in the document indicated as potentially erroneous.

10. The non-transitory media of claim 8 , wherein the method further comprises enabling a user to provide input for changing in the text in the source language at least one word or fragment indicated as potentially erroneous.

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9. A computer-readable tangible storage medium encoded with a computer program product for controlling actions in a computer-based process, the computer program product comprising: a status schema model repository for status schema models, stored in a computer-readable medium, each status schema model corresponding to a data object node; and including preconditions for performing actions, a precondition identifying how a status affects whether an action is to be allowed to be performed at runtime by a data object node instance having the status, and-instructions stored in a computer-readable medium that, when executed, perform operations comprising: creating a status schema instance for a particular data object node instance being used in a computer-based process, the status schema instance corresponding to the status schema model, and the data object node instance including a status variable, multiple status values for the status variable, and actions variables and methods capable of being performed by the data object node instance, each status value of the status variable being a precondition for at least one of the actions, the precondition identifying whether the associated action is to be allowed to be performed at runtime by the data object node instance; based on the status schema instance, monitoring a status of the status value of the status variable of the data object node instance to determine whether a precondition associated with a particular action is satisfied allowed to be performed by the data object node instance; and in response to the determination that the precondition is satisfied particular action is allowed, enabling the particular action to be executed; and in response to executing the particular action, altering the status value of the status variable.

11. The computer-readable tangible storage medium of claim 9 wherein creating the status schema instance for the particular data object node instance comprises setting a status variable of the status schema instance to a corresponding value of the status variable for the data object node instance.

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4. The method of claim 1 further comprising: the plurality of descriptors pointing to a same data block with different offsets.

1. A computer-implemented method of manipulating a structured document, the method comprising: creating, by a computer, fragments of the structured document, comprising one or more message blocks having access caches and lseek pointers that point to a descriptor in an ordered list along with an offset of a data referred; creating the ordered list including a plurality of descriptors pointing to the structured document fragments; and modifying the ordered list for the manipulating of the structured document.

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15. The device of claim 13 wherein the method avoids at least one calculation using the Viterbi algorithm.

13. A computer-readable storage device encoded with instructions for controlling a computer system to determine a score for a recognition alternative, by a method comprising: receiving a digital ink segment that makes up part of a word; adjusting a score based on output of a shape classifier for a recognition alternative of the digital ink segment; if the digital ink segment is the last segment in a letter, adjusting the score based on the probability that the letter ends in the digital ink segment; if there are more ink segments in the word, adjusting the score based on a bigram probability between the letter and a subsequent letter, the bigram probability selected according to the letter and the subsequent letter from among a set of bigram probabilities computed in advance from a corpora, wherein each bigram probability indicating a probability that two letters appear in succession in a word; and if the digital ink segment is the last segment in the word, providing the score for the recognition alternative by applying a weak-constrained language model that recognizes words not present in a dictionary of words of a currently selected language, the weak-constrained language model comprising probabilities that segments are last segments of letters.

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9. A server system for converting visual content information in an image into audio content and providing the audio content for presentation, the server system comprising: one or more network interfaces configured to provide access to a network; one or more servers, coupled to the one or more network interfaces, the one or more servers to execute instructions to: transmit first content via the network to a first end-user device to facilitate a user interface presented by an application of the first end-user device to prompt input comprising an image; process a first transmission received from the first end-user device via a network by the server system, the first transmission (a) comprising an image, the image comprising visual content information and provided as input via the user interface, and (b) corresponding to a request from an advertiser; responsive to the request from the advertiser, generate, audio content based at least in part on the image included in the visual content information at least in party by: analyzing the visual content information to extract meaningful words from the visual content information; identifying one or more limits associated with the audio content; generating a summarized text for the audio content (a) based on the meaningful words extracted from the visual content information, (b) using natural language processing to link the meaningful words based on a heuristic model and a database of words commonly used in similar content, and (c) based at least in part on the one or more limits associated with the audio content, wherein the linking of the meaningful words based on the heuristic model and the database of words commonly used in similar content generates grammatically correct text; and converting the summarized text into speech to generate the audio content and storing the audio content in an audio file; transmit via the network, the audio file storing the audio content for presentation via a second end-user device; and process a second transmission received consequent to a selection of the audio content, via the second end user device, that initiates a real-time communication connection for a call from the second end user device to the advertiser upon selection of the audio content; determine whether the call from the second end user device has been connected to the advertiser via the audio content; and responsive to determining that the call from the second end user device has been connected to the advertiser via the audio content, generating a record entry in a connection record data structure indicating that the call from the second end user device was connected to the advertiser via the audio content; and one or more storage media coupled to the one or more servers to retain the instructions.

12. The server system of claim 9 wherein the audio content is transmitted for presentation on behalf of the advertiser in accordance with a callable time window associated with the advertiser.

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4. The method of claim 1 , wherein: the method further includes parsing key-value properties in the configuration files to identify control widgets; each control widget is declared to have a control widget type selected from a group that includes at least list selector, range selector and date selector types; each control widget selects a value or range of values of at least one associated dimension that is used to generate a query; and execution of the query generated from the control widget is linked to updating data in the panels that have the facet property set.

1. A method of generating a dashboard that includes multiple panels from a declarative representation of queries, widgets, bindings and facets, the method including: accessing one or more configuration files that represent interaction among queries, widgets, bindings and facet property settings to generate multiple panels of a dashboard; parsing key-value properties in the configuration files to identify queries, wherein each query specifies a value or range of values of at least one dimension and, when processed, returns a data set that includes at least one dimension and at least one measure; providing a plurality of visualization widgets, wherein each visualization widget, when invoked on a computer including a processor, accepts as input the dimension returned in the data set as an independent variable and the measure as a dependent variable; generates a specified chart or graph from the dimension and the measure to form a first view of segments in the specified chart or graph, each segment of the segments having a starting position in the first view and each segment in the specified chart or graph illustrating a first measurement of data from the data set with respect to a first particular constraint; invokes a tweener to morph each of the segments to second view from the first view by morphing each of the segments from the starting position in the first view to multiple intermediate positions and then to an ending position in the second view, each segment in the second view of the specified chart or graph illustrating a second measurement of data from the data set with respect to a second particular constraint; and invokes the tweener to morph to a third view from the second view by morphing each of the segments from the ending position in the second view to multiple intermediate positions and then to an ending position in the third view; parsing key-value properties in the configuration files to identify panels, wherein each panel declares a binding that links an associated visualization widget to an associated query; wherein each panel declares the specified chart or graph into which the data set returned by the associated query will be rendered by the associated visualization widget; and wherein at least some of the panels set the facet property, wherein the facet property links operation of data filtering controls among the panels, whereby selection of a data filter control in one panel causes the selected data filter to be applied to additional panels that have the facet property set; and generating data representing a dashboard and the panels based at least in part on the configuration files.

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13. The system of claim 12 , further comprising a module for establishing an account for the user application with the system.

14. The system of claim 13 , wherein the user application is enabled to access the system only open payment or prepayment to the account.

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14. A method executed on a computing device to provide a metadata based search in an e-reader environment, the method comprising: determining search terms based on a selected portion of displayed content; generating a query for a search based on the selected portion; determining the metadata associated with one or more objects within a predefined vicinity of the selected portion by processing the one or more objects to retrieve metadata, wherein the one or more objects include embedded images, embedded graphical objects, and one or more interactive objects, interactive puzzle objects, embedded video objects, and embedded audio objects, and wherein the interactive objects are associated with the search terms; performing optical character recognition on each of the embedded images and the embedded graphical objects to retrieve textual content and key terms from each of the embedded images and the embedded graphical objects; indexing the metadata, wherein the metadata includes the textual content and the key terms; augmenting the query based on the metadata, wherein the metadata is associated with one or more attributes of each of the one or more objects and includes at least one from a set of dimensions, types, titles, and tags of the one or more objects; categorizing a summary of query results based on the metadata; and presenting the summary of the query results in a results pane on a user interface.

15. The method of claim 14 , further comprising: generating the query in response to detecting one of the selection of the portion of the displayed content and activation of a search control following the selection of the portion of the displayed content.

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22. The method of claim 20 wherein the action comprises providing a notification that identifies the matching portion of the phonetic index.

20. A method comprising: accessing a phonetic index of a sequence of phonemes and associated source information wherein: each phoneme in the phonetic index corresponds to a basic unit of speech content of an audio segment comprising speech content from a plurality of sources, such that different speech segments of the speech content correspond to different ones of the plurality of sources; and the source information associates a corresponding one of the plurality of sources with the phonemes in the sequence of phonemes of the phonetic index; determining at least one phonetic search criterion in association with a search query wherein the phonetic search criterion corresponds to phonetic content; identifying a matching portion of the phonetic index that meets the at least one phonetic search criterion; and taking an action in response to identifying the matching portion of the phonetic index.

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2. The system of claim 1 , further comprising a communication mechanism coupled to the mixed media processor.

6. The system of claim 2 , further comprising the device coupled to the communication mechanism capable of receiving one of digital data and an image representing a portion of the commercially printed document.

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25. The server of claim 24 , wherein the one or more processors are further configured to select the negative keywords to further maximize the number of search criteria identified as being off-topic to the advertisement item.

24. The server of claim 23 , wherein the one or more processors are further configured to select the negative keywords to increase the number of search criteria identified as being off-topic to the advertisement item.

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12. The system of claim 8 , wherein the processor is further configured to identify discriminative features of a part of a sample complex-image, the discriminative feature characteristic of the part of the complex-object.

8. A system for identifying a complex-object in a query image, the system comprising: a processor configured to: process at least one pixel patch from the query image with a cascade of classifiers, each of the classifiers of the cascade configured to identify at least one discriminative feature characteristic of a part of the complex-object, wherein each successive classifier of the cascade uses a number of discriminative features greater than a number of the discriminative features used in prior classifiers of the cascade; and select an additional pixel patch from the query image for processing after a last classifier of the cascade has identified the distinguishing feature, wherein the selecting is based on a known positional relationship between the part and an additional part of the complex-object.

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1. A method comprising: presenting to a first player of a computer-generated crossword puzzle, a first clue to derive a first solution of the computer-generated crossword puzzle; receiving, from the first player, an alternate clue request identifying a desired level of difficulty for an alternate clue, different that the first clue, to derive the first solution; and upon a determination that an alternate clue, different than the first clue, of the desired level of difficulty is available, presenting, to the first player, the alternate clue to derive the first solution.

3. The method of claim 1 , further comprising: receiving, from the first player, an improvement feature request identifying an improvement feature to be applied to the computer-generated crossword puzzle; and applying the improvement feature identified by the improvement feature request to the computer-generated crossword puzzle, wherein the improvement feature provides additional information to derive the first solution.

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6. The method of claim 3 , further comprising associating a ranking with each of the plurality of unique attributes based on how indicative each of the plurality of unique attributes is of the likelihood of an electronic document being spam.

3. The method of claim 2 , further comprising: analyzing each of the plurality of known spam electronic documents; and determining a plurality of unique attributes for each of the known spam electronic documents.

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1. A computer-implemented method implemented using instructions stored on a computer-readable medium and executable by a computing device, the method comprising: initializing event parameters to identify a number of salient events from a corpus of documents, wherein the events comprise occurrences that are described in the corpus of documents and are identified based on a salient score calculated from the distance between peaks on a graph, the peaks on the graph corresponding to each respective one of the events; probabilistically determining, using a generative model, whether documents are associated with a first event to detect representative events of the number of salient events, wherein probabilistically determining comprises: estimating parameters for the generative model using the event parameters; generating event clusters to cluster events reported by the documents using estimated generative model parameters; for each event cluster: increasing or decreasing a number of events to represent a corresponding event; if the number of events is not a minimum or a maximum number of events: (a) again performing operations associated with initializing the event parameters to generate re-initialized event parameters; and (b) using the generative model to probabilistically detect events from salient ones of the documents using the re-initialized event parameters; and if the number of events is a minimum or a maximum number of events, summarizing event(s) associated with the event cluster to assign content of one or more documents to respective events; selecting the first event reported by one or more of the documents; and for each entity associated with the first event: generating a respective news article for the first event; and determining a time for the respective news article.

5. The method of claim 1 , wherein document content associated with an event of the respective events comprises one or more of information associated with persons, locations, and keywords and wherein probabilistically determining further comprises: modeling the document content with mixtures of different respective unigram models; and modeling the timestamps with a mixture model that is not one of the different respective unigram models.

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12. The method of claim 1 , wherein determining the time derivatives of magnetic field strength measured by the magnetometer device along each of the three orthogonal measurement axes comprises: during at least a portion of the time interval W, measuring orthogonal magnetic field components H x , H y , and H z of a magnetic field vector {right arrow over (H)}=[H x , H y , H z ] at consecutive discrete times t i , i=1, . . . , N, wherein N≧2, to obtain samples of the of H x , H y , and H z at the consecutive discrete times t i , i=1, . . . , N; and computing discrete time derivatives of the measured orthogonal magnetic field components H x , H y , and H z from discrete differences between successive samples.

14. The method of claim 12 , wherein t i for i=1 is one of t 1 <T start , t 1 =T start , and t i >T start .

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9. The computer-implemented method of claim 8 , wherein identifying the terms from the text comprises using a vocabulary driven parser.

8. A computer-implemented method, comprising: accessing text by a processing system; identifying, by the processing system, a plurality of terms from the text; determining, by the processing system, a plurality of term vectors associated with the identified terms; calculating a weight of each of the determined term vectors; clustering, by the processing system, the determined term vectors into a plurality of clusters, each of the clusters being related to a distinct concept of the text, each cluster comprising at least one of the determined term vectors, the clustering comprising selecting the at least one of the determined term vectors based on the determined weights of the term vectors and distances between the determined term vectors; creating, by the processing system, a first pseudo-document according to a first cluster of the plurality of clusters and a second pseudo-document according to a second cluster of the plurality of clusters; identifying, by the processing system using latent semantic analysis (LSA), a first set of terms associated with the first cluster and a second set of terms associated with the second cluster; determining a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the determined weights of the term vectors of the first cluster, and wherein the second weight is based at least on the determined weights of the term vectors of the second cluster; determining a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; selecting one or more terms from the first set of terms according to the determined first percentage; selecting one or more terms from the second set of terms according to the determined second percentage; creating, by the processing system, the list of output terms using at least a portion of the selected terms from the first and second sets of terms, the list of output terms having the distinct concepts of the plurality of clusters; and storing the list of output terms in one or more memory units.

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1. A method, comprising: generating, by one or more computing devices in response to input, a digital sketch comprising one or more panels, one or more sketches each at least in part included in a respective one of the one or more panels, and one or more textual elements each included in a respective one of the panels, said generating the digital sketch comprising: generating the one or more panels according to panel input specifying a border for each of the one or more panels on a page; generating the one or more sketches according to drawing input specifying one or more strokes on the page, at least a portion of the one or more strokes being drawn in at least one of the one or more panels; erasing a portion of the border for at least one of the panels according to an erase input; determining for each of the one or more panels, based on a windowing algorithm, which of the one or more strokes or portions of the one or more strokes are to be displayed in the digital sketch and which of the one or more strokes or portions of the one or more strokes are hidden in the digital sketch, the windowing algorithm recognizing the erased portion of the border and said determining that the one or more strokes or portions of the strokes that pass through the erased portion of the border are to be displayed and the one or more strokes or portions of the strokes that do not pass through the erased portion of the border are to be hidden from display, and for a panel, the windowing algorithm performing: determining at least one of the strokes crosses the border of the panel; splitting each stroke that crosses the border of the panel to generate at least two separate strokes from the respective stroke; marking each stroke that lies inside the border of the panel to be displayed; determining at least one remaining unmarked stroke that intersects a marked stroke; and marking each remaining unmarked stroke that intersects a marked stroke as to be displayed and additional remaining unmarked strokes are hidden from display.

2. The method as recited in claim 1 , wherein the digital sketch is generated according to vector graphics technology.

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2. The system of claim 1 wherein said unique expandable container image includes the phrase and a decoration.

3. The system of claim 2 wherein the decoration comprises a pattern through which the phrase is visible.

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12. The system of claim 10 , wherein the second trigger uses the reference field metadata framework to: determine a value for the reference field of each parent database object of the inserted non-root database object; apply the reference field inheritance function for the class of the inserted non-root database object to determine a value for the reference field of the non-root database object; and assign the non-root database object to a partition according to the determined value.

10. A system for reference partitioning database objects by values in a reference field, the system comprising: at least one hardware processor; at least one database environment, the database environment supporting triggers and partitioning; at least one application program; and memory storing: a reference field metadata framework that: identifies classes in a hierarchy of database objects, identifies at least one class as a root of the hierarchy, identifies, for each non-root class, a reference field inheritance function for the class, and identifies, for each parent class-child class pair in the hierarchy, a relation-join query, the relation-join query being a join between tables in the database environment onto which the parent class and child class are persisted, and triggers that use the framework to maintain values for the reference field for non-root database objects, including at least a first trigger invoked after a reference field of a database object in a root class is changed, a second trigger invoked responsive to a non-root database object being inserted, and a third trigger invoked responsive to a non-root database object having a change in parent.

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10. The computer-implemented method of claim 8 , wherein the web page comprises a second content item, and wherein the method further comprises: receiving a translation of the second content item, the translation of the second content item generated by a selected one of the first machine translation service or the second machine translation service; and presenting the translation of the second content item in the user interface.

11. The computer-implemented method of claim 10 , wherein the selected machine translation service is selected based upon the first rendered location of the second content item on the web page.

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13. A computer program product for processing complex queries, the computer program product disposed upon a non-transitory computer readable storage medium, the computer program product comprising computer program instructions that, when executed by a computer processor of a computer, cause the computer to: detect a first query directed towards a dataset which satisfies a size criterion, wherein the first query includes a set of initial predicates and results in a first result set; identify one or more new predicates from the result set, wherein the one or more new predicates are not within the set of initial predicates; detect a second query directed towards the dataset, wherein the second query is the same as the first query; determine that predicates of the one or more new predicates filter a threshold amount of tuples of an initial set of tuples; determine an order of the one or more new predicates such that a new predicate which filters relatively more tuples of the initial set of tuples is before a new predicate which filters relatively less tuples of the initial set of tuples; and utilize the one or more new predicates to process the second query in the order and determine a second result set for the second query.

14. The computer program product of claim 13 , wherein the computer program product further comprises computer program instructions that, when executed by a computer processor of a computer, cause the computer to: detect one or more modifications to the dataset; determine that the one or more modifications invalidate a new predicate of the one or more new predicates; and invalidate the new predicate.

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13. The method of claim 1 , wherein the finite alphabet consists of no more than 400 characters.

1. A method comprising: building a target background model using words occurring in training data, the target background model being adaptable to accept subsequences of an input semantic representation, the training data includes training pairs, each training pair including a semantic representation and a corresponding reference sequence in a natural language; receiving human-generated utterances in the form of speech or text; predicting a current dialog state of a natural language dialog between a virtual agent and a user, based on the utterances; generating a semantic representation of a next utterance, based on the current dialog state, the semantic representation including a sequence of characters; and generating a target sequence in a natural language from the semantic representation, comprising: after generating the semantic representation, adapting the target background model to form an adapted background model, which accepts all subsequences of the semantic representation; representing the semantic representation as a sequence of character embeddings; with an encoder, encoding the character embeddings to generate a set of character representations; and with a decoder, generating a target sequence of characters, based on the set of character representations, wherein at a plurality of time steps, a next character in the target sequence is a function of a previously generated character of the target sequence and the adapted background model; and outputting the target sequence.

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10. A text processor according to claim 5, wherein said look-up table is comprised by format templates.

5. A text processor according to claim 1, further comprising a look-up table, wherein said text generator generates text in accordance with said look-up table.

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7. The system of claim 1 , wherein the processor further facilitates the execution of the computer-executable instructions to update the mash-up in response to a change in the information.

1. A system, comprising: a memory that stores computer-executable instructions; and a processor that facilitates execution of the computer-executable instructions to at least: link information received from at least two sources in an industrial control system; and generate a mash-up of the information received from the at least two sources.

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14. The one or more non-transitory, machine-readable storage media of claim 12 , further comprising a plurality of instructions that in response to being executed cause the computing device to update the hardware transaction tracking field associated with the cache line for the data address to the accessed value and set a tracking flag for subsequent synchronous execution of handler code in response to decoding the transactional memory access instruction, the hardware transaction tracking field holding an un-accessed value, and the execution mode value representing the execution mode including an explicit mode of execution.

15. The one or more non-transitory, machine-readable storage media of claim 14 , wherein the mode instruction referencing the transactional execution mode comprises a convert transactional execution mode instruction.

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10. The system of claim 1 , wherein the configuration directory is configured to provide faster runtime access than the configuration repository.

1. A computer system comprising: a first computer comprising a storage device storing: a configuration repository storing multiple entries of configuration information for a software application program, each entry designed for customizing the software application program for a specific situation and the software application program being designed to remotely request configuration information as needed, wherein each configuration information entry includes 1) a configuration component available to be requested for the software application program and 2) a configuration attribute and an associated attribute value that define terms for the software application program to apply to a business transaction of a business enterprise in the specific situation, wherein the configuration repository stores the multiple entries of configuration information in XML format, and a configuration directory storing at least a first configuration information entry selected for the specific situation from among the multiple entries, the first configuration information entry selected based on a user input during a process to customize the software application program for use in the specific situation by a particular business enterprise, the configuration directory being remote from the software application program and different from the configuration repository, and the configuration directory storing the at least one configuration information entry in a database table format in which access to the first configuration information entry is faster than in the XML format; a processing device, coupled to the storage device, for providing the first configuration information entry having the database table format from the configuration directory to the software application program in response to a request; and a second computer that operates the software application program and that is outer to the first computer, the software application program being configured to send, from the second computer over a communications link to the first computer, the request for the first configuration information entry for use by the software application program to process the business transaction of the business enterprise.

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23. The machine-readable volatile or non-volatile medium as recited in claim 14 , wherein at least one suggested query candidate is selected by performing: determining the current date; determining an event taking place within a certain time window from the current date; in response to determining, generating a suggested query term containing said event.

14. A machine-readable volatile or non-volatile medium storing instructions, wherein said instructions are instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: receiving a not-yet-submitted user search query from a client node; wherein the not-yet-submitted user search query is a partial, not completely formed search query; wherein the not-yet-submitted user search query is received after the steps of: prior to the user finalizing and submitting the search query, determining that the not-yet-submitted user search query meets search initiation criteria; in response to receiving the not-yet submitted user search query, generating a set of suggested query candidates; generating a biased parameter, wherein the parameter is associated with a suggested query candidate of the set of suggested query candidates, and the parameter is biased based on an attribute associated with the suggested query candidate; selecting one or more of suggested query candidates of the set of suggested query candidates to be suggested queries for the search query based on the biased parameter associated with the suggested query candidate; determining relevance of at least one of the suggested queries of the one or more suggested query candidates; in response to determining that the relevance of said at least one of the suggested queries meets or exceeds a relevance threshold, providing said at least one of the suggested queries to the client node; receiving, from the client node, a search request including one of the suggested queries as a completely formed query; and in response to receiving the search request including one of the suggested queries as a completely formed query, sending search results back to the client node; wherein search results include a list of links to files or pages.

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2. The non-transitory, computer-readable medium of claim 1 , wherein the reset configuration request includes a plurality of flags each indicating whether corresponding configuration details in the receiving device are to be reset in response to the reset configuration request.

1. A non-transitory, computer-readable medium having stored thereon instructions for enabling control of a receiving device in a remote network using a device control profile, wherein the instructions are configured to cause a processor of the receiving device to: receive a reset configuration request that includes an indication of a network configuration, a fabric configuration, a service configuration, or a combination thereof to be reset in the receiving device by setting the corresponding to a known state; and transmit a status report from the receiving device indicating a status of a configuration reset invoked by the reset configuration request.

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6. The method of claim 1 , further comprising determining if a change in a highlight color for text corresponding to a note flag is desired.

1. A computer-implemented method for customizing note flags comprising: receiving notes from an input device; selecting a note; receiving an ink gesture; wherein the ink gesture received is inked in a shape of a note flag on a display; automatically processing the received ink gesture to determine the shape of the note flag that was inked on the display; wherein processing the received ink gesture comprises comparing the shape of the received ink gesture to a shape for each of the note flags until a match is found; automatically selecting a note flag whose shape matches the shape of the note flag that was inked on the display; wherein each note flag is associated with a different shape; displaying formatting options for the selected note flag; displaying a preview of changes made to the selected note flag; saving changes made to the selected note flag on storage medium; and displaying a note flag summary; wherein displaying the note flag summary comprises extracting each note that has an associated note flag; and displaying the extracted notes with each associated note flag separately from a display of the notes and initiating action in another application program in response to determining that the note flag is selected within the note flag summary.

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36. The apparatus as recited in claim 34 wherein a first virtual assistant comprises the first personality, and a second virtual assistant comprise s the second personality.

34. The apparatus as recited in claim 1 wherein the logic that provides the personality comprises providing the voice user interface with a first personality and a second personality.

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1. A bill of material (BOM) management system for processing a product data or configuration change of a product between a plurality of BOMs, each BOM with a corresponding functional domain, comprising: a plurality of product elements associated with each BOM, each product element defining at least one assembly, each assembly having at least one component of a corresponding assembly, both the assembly and the component being listed in a corresponding BOM as a product element of the product; a dynamic link that maps and connects each component of the assembly in a first BOM disposed in a first file server of a first functional domain to a corresponding component of the assembly in a different, second BOM disposed in a second file server of a second functional domain; a semantic network having a product knowledge that interacts with the corresponding BOM using a computing network connecting the first and second file servers, the product knowledge having information about the dynamic link; and a Decompose/Recompose/Multi-arrange (DRM) process module that manages product configuration information of the product, the DRM process module having a computer processor, executing computer-executable instructions, to perform a decompose process, a recompose process, and a multi-arrange process, wherein, using the computer processor, the DRM process module detects a changed product having the product data or configuration change of the product in each BOM of the corresponding functional domain, the DRM process module transmits product information relating to the product data or configuration change, including the dynamic link, from the first BOM to the second BOM so that each component of the changed product in the first BOM is linked to the corresponding component of the second BOM, wherein, using the computer processor, the DRM process module performs the decompose process by grouping the product elements based on the product knowledge of the semantic network, performs the recompose process by regrouping the product elements in a selected domain context, and performs the multi-arrange process by rearranging the product elements to propagate the product data or configuration change of a product structure in the first BOM of the first functional domain to another product structure in the second BOM of the second functional domain via the computing network, and wherein, using the computer processor, the DRM process module automatically creates and adds a new dynamic link in the product knowledge for the propagation for reflecting the same product data or configuration change of the changed product in the first BOM into the second BOM based on determining that the product data or configuration change of the changed product in the first BOM does not exist in the second BOM.

6. The BOM management system of claim 1 , wherein BOM-related product information is linked according to product knowledge stored in the semantic network.

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17. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing: receiving a first speech input including at least one word; determining a first phonetic representation of the at least one word, the first phonetic representation comprising a first set of phonemes selected from a speech recognition phonetic alphabet; mapping the first set of phonemes to a second set of phonemes to generate a second phonetic representation, the second set of phonemes selected from a speech synthesis phonetic alphabet that is different from the speech recognition phonetic alphabet, wherein the speech recognition phonetic alphabet and the speech synthesis phonetic alphabet are phonetic alphabets of a same language; and storing the second phonetic representation in association with a text string corresponding to the at least one word.

18. The device of claim 17 , further comprising instructions for performing, prior to receiving the first speech input, providing the text string.

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6. The method of claim 1 , wherein processing the plurality of objects includes: applying a matcher to a pair of objects in one of the plurality of buckets.

1. A computer-implemented method of identifying duplicate objects in a plurality of objects, wherein each object in the plurality of objects is associated with one or more facts, and each of the one or more facts has an attribute and a value, the method comprising using a computer processor to perform: associating facts extracted from web documents with the plurality of objects; for each of the plurality of objects, normalizing a value of a name fact, the name fact being among one or more facts associated with the object; based on the normalized values of the name facts, grouping the plurality of objects into a plurality of buckets, each object in a bucket having the same normalized value of a name fact; processing the plurality of objects in a bucket to identify at least one pair of duplicate objects in the plurality of objects in the bucket, based on a similarity of values of facts other than the name fact for the objects in the bucket; and merging the duplicate objects together, the merging including removing one of the duplicate objects from a memory repository.

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13. The receiver apparatus as in claim 12 wherein the virtual multiple media collections include information obtained from a broadcasted television signal and the Internet.

14. The receiver apparatus as in claim 13 wherein the I/O controller further comprising an input for receiving television programs, including additional information through the television program and an electronic program guide information, the filter being coupled to the I/O controller for filtering information from the television program input in accordance with the adaptive user profile database.

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13. A method comprising: parsing inputs received from a plurality of sources into surface semantics represented in a semantic representation by utilizing a language model, each of the plurality of sources corresponding to a different modality; providing environmental data associated with at least one of the inputs, the data comprising one or both of current data or historical data; adapting the language model to enhance accuracy of the parsing by utilizing the environmental data to compute at least one environmentally-specific conditional probability of at least one phrase of the inputs received from the plurality of sources; utilizing the semantic representation to generate discourse semantics; utilizing the discourse semantics to synthesize one or more responses to the inputs received from the plurality of sources; further comprising: generating, as a function of the environmental data, a confidence level for an intent associated with the inputs received from the plurality of sources; evaluating a first input of the inputs, the first input having a first modality initially employed as a primary modality; based on the generated confidence level, providing feedback to request a second input of the inputs having a second modality different from the first modality, and substituting the second modality for the first modality as the primary modality until the environmental data changes.

14. The method of claim 13 , further comprising utilizing one modality to complete or refine input associated with another modality.

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6. The method according to claim 3 , wherein the calculating step comprises calculating the target cost and the transition cost.

7. The method according to claim 6 , wherein the step of identifying the sample with the smallest distance comprises identifying the sample with the smallest target cost.

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26. A method according to claim 25, further including the step of displaying an interpretive message with the readability output.

25. A method of claim 24, further including the step of storing a table of common words together with an indication of the syllable count of a word, and wherein a measure of the text includes at least one of word length in syllables and a measure of familiar words occurring in the text.

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5. A method comprising: receiving first input data; accessing an ontology for a data store, wherein the ontology comprises a plurality of object property types; determining whether the first input data matches one or more parser definitions that specify two or more parser sub-definitions, wherein each of the two or more parser sub-definitions specifies how to transform a portion of the first input data into a portion of modified input data that is compatible with a component of one of the object property types of the ontology for the data store; wherein each component is associated with a data type of data; using a matching one of the one or more parser sub-definitions, creating a property instance of the object property type that is associated with the matching one of the one or more parser sub-definitions, and storing the portion of the modified input data in a component of the property instance; wherein the method is performed by one or more computer systems.

7. The method of claim 5 , comprising: using a transformation expressed in the matching one of the one or more parser definitions to transform the portion of the first input data into the portion of the modified input data that is compatible with a component of said one object property type of the ontology for the data store; storing the portion of the modified input data in a component of the object property type that is associated with the matching one of the one or more parser definitions.

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7. A method for providing input into a tagging interface, the method being performed by one or more processors of an electronic device that is external to a database system, the method comprising: providing the tagging interface on an enhanced web browser displaying an external web page; receiving a tag-type selection input designating one of a plurality of tag-types for a tag, wherein the plurality of tag-types comprises an object tag type and a property tag-type; receiving a create-tag selection input creating a tag with a designated tag-type and associating the tag with a selected portion of content from the external web page; and receiving an export selection input exporting the tag and the external web page to the database system.

12. The method of claim 7 , wherein the enhanced web browser has been updated using a bookmarklet or a plugin.

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6. The method of claim 5 , further comprising: compiling the received one or more comments into a blog.

5. The method of claim 1 , further comprising: receiving one or more comments related to the clusters of documents; and storing, in the memory, the received one or more comments.

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9. The apparatus of claim 8, wherein the superword selecting means inputs each of the candidate phrases into the database and determines whether the inserted candidate phrase decreases the perplexity value of the database.

10. The apparatus of claim 9, wherein the superword selecting means determines that if the perplexity value decreases, the inserted candidate phrase is added to the database as a superword, and if the perplexity is not decreased, the inserted candidate phrase is not added to the database.

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13. The method of claim 9, further comprising the step of displaying said target word in a box.

9. The method of claim 1, wherein said initial text and said further text are contextual phrases including a target word and words immediately preceding and following said target word.

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1. A method comprising: identifying a set of training images previously used to train an image relevance model that generates relevance measures of images to a query based on content feature values of the images, the query being a unique set of one or more query terms; identifying typical visual features for the set of training images, including: for two or more visual features: determining that at least a given portion of the training images from the set of training images that were used to train the image relevance model each include the visual features, and in response to determining that at least a given portion of the training images each include the visual features, identifying the visual features as typical visual features for the set of training images; identifying, as a subset of training images from the set of training images, training images having at least a threshold portion of the identified typical visual features, wherein the subset does not include all images within the set of training images; assigning, to each training image in the subset of the training images, a weight that increases in proportion to the number of the identified typical visual features that the training image has, wherein each training image in the subset has a higher weight than weights assigned to other images from the set of training images that are not in the subset of training images; and generating a re-trained image relevance model based on visual features of the set of training images and the weights assigned to the training images in the subset of training images that have at least the threshold portion of the identified typical visual features.

5. The method of claim 1 , further comprising assigning a multiplier value to each image in the subset of training images, the multiplier value being greater than one.

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43. The method of claim 37 wherein each of the plurality of templates is associated with at least one of: a government issued identity document, a student identity document, an employment identity document, a driver's license, a passport, and a travel document.

37. A computer-implemented method comprising: receiving an image of an identity document, the image being produced using a video stream; improving the image, wherein the improving includes removing blurring, adjusting brightness, and adjusting colors; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; and making the completed form accessible on a system.

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1. A method, for use with a processor, the method comprising: accessing information for use in determining payload information conveyed in a watermarked image, the accessed information having been produced prior to watermarking an image to produce the watermarked image, said payload information being associated with a watermark included in said watermarked image, said watermarked image and said image being arithmetically encoded by an arithmetic code, said watermark modifying at least one syntax element of said image and having watermarked said image by replacing arithmetically coded bits directly without prior arithmetic decoding and re-encoding of said image, and the accessed information including: location information that identifies a location of a set of pixels in the watermarked image, wherein the set of pixels conveys the payload information in a pixel-domain representation of the set of pixels of the watermarked image, one or more values for a feature in the pixel-domain representation of the set of pixels, wherein the one or more values for the feature indicate whether first payload information or second payload information is conveyed in the pixel-domain representation by the set of pixels, and wherein the one or more values comprise: a first value for the feature in the pixel-domain representation of the set of pixels, wherein the first value for the feature indicates that the first payload information is conveyed in the pixel-domain representation by the set of pixels; and a second value for the feature in the pixel-domain representation of the set of pixels, wherein the second value for the feature indicates that the second payload information is conveyed in the pixel-domain representation by the set of pixels; accessing the watermarked image said watermarked image having a test value for the feature based on said modified at least one syntax element; determining the a-test value for the feature of the set of pixels in the accessed watermarked image; comparing the test value with at least one of the first value and second values for the feature; and determining the payload information based on a result of the comparing of the test value.

11. The method of claim 1 further comprising: repeating the operations of accessing information, determining the test value, and comparing the test value, the repeating being done one or more times for additional locations in the watermarked image.

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15. The method according to claim 14 , wherein updating the mapping comprising updating the sorting table.

14. The method according to claim 11 wherein determining the mapping comprises using a sorting table to determine the mapping.

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11. The method of claim 8 , further comprising processing the new ECG waveform and/or the extracted feature with a general interpretation module to provide a general interpretation output, wherein the general interpretation module is trained on a general database of existing ECG datasets.

8. A method for adaptive interpretation of ECG waveforms, the method comprising: receiving a new ECG waveform; extracting at least one feature from the new ECG waveform; selecting a cluster interpretation module based on the feature; processing the new ECG waveform and/or the extracted feature to provide a cluster interpretation output; displaying the cluster interpretation output on a user interface; receiving a clinician input via the user interface rejecting the cluster interpretation output; and using the clinician input as negative feedback to train the cluster interpretation module.

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15. The computer program product of claim 11 wherein the RaCL provides the following capabilities using the upper merged ontology, the domain models and the semantic web APIs: model creation, automated reasoning and search and query operations.

11. A computer program product for developing an operational model for an IT architecture application comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to develop an information technology (IT) architecture upper merged ontology for a given IT architecture application comprising: an upper merged ontology that is a representation framework for combined knowledge sources that are used in business and information technology, the upper merged ontology including a plurality of business, architecture and service domain models; an upper merged ontology knowledge base containing information derived from an analysis of business and technical services pertaining to the IT architecture application; a plurality of semantic web APIs that allow access to the upper merged ontology as a semantic web; and a reasoning and constraint language (RaCL) that is a scripting language having the capabilities of model creation, automated reasoning and search and query operations such that scripts developed in the reasoning and constraint language can be executed through use of the semantic web APIs; computer readable program code configured to populate the upper merged ontology knowledge base with information derived from an analysis of business and technical services pertaining to the IT architecture application; computer readable program code configured to execute RaCL processes to search the upper merged ontology knowledge base and extract knowledge pertaining to the IT architecture application and computer readable program code configured to process the results to generate dependency and interface relationships within an operational model domain ontology; and computer readable program code configured to create an architecture for the IT architecture application from the operational model domain ontology, dependency and interface relationships.

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18. A method according to claim 14 , wherein said step of analyzing further comprises comparing band-limited energy content of the sound in said each block to a first sound energy threshold.

14. A method according to claim 9 , wherein said step of analyzing comprises observing zero crossings of the sound in said each window.

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16. The method of claim 12 , wherein the candidate topic word comprises one or more Hanzi characters.

12. A computer-implemented method, comprising: selecting a topic dictionary comprising topic words related to a topic; determining a topic word divergence value based on a topic word, a document corpus and a topic document corpus, wherein the topic document corpus is a corpus of topic documents related to the topic, and the document corpus is a corpus of documents that includes the topic documents and other documents, and the topic word is a word that is related to the topic; determining a candidate topic word divergence value for a candidate topic word based on the document corpus and the topic document corpus, wherein the candidate topic word is not a topic word in the topic dictionary; and determining whether the candidate topic word is a new topic word for the topic based on the candidate topic word divergence value and the topic word divergence value.

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1. A training device comprising: at least one sensor configured to measure at least one physical performance characteristic of a user during a workout; a first computing device that is portable and selectively attachable to the user, including: a receiver configured to electronically receive an electronic training script defining a sequence in which the user is instructed to perform a plurality of activities, and a presentation unit configured to prompt the user to perform a next activity of the plurality of activities in the sequence based on a measurement of the at least one physical performance characteristic indicating completion of a previous activity in the sequence.

18. The training device recited in claim 1 , wherein the training script includes a plurality of steps, and wherein each of the steps has a defined performance data, and wherein the plurality of steps each automatically start a subsequent step when the defined performance data of the previous step has been measured.

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8. The method of claim 5 , wherein adjusting relevancy scores involves: boosting relevancy scores for documents which are annotated as being related the specific topic; reducing relevancy scores for documents which are annotated as being spam documents; and changing the rankings of search results based on the adjusted relevancy scores.

5. The method of claim 1 , wherein the method further comprises: receiving a new query; determining whether the new query is related to the specific topic; and processing the new query to produce query results, wherein if the new query is related to the specific topic, processing the new query involves adjusting relevancy scores for documents based on annotations associated with the documents.

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9. The apparatus according to claim 3 , wherein the processor is further configured to store information indicating a relationship with a predetermined feature quantity, wherein when a predetermined word is selected from words displayed in a format different from the other words as a word having served for the selection of the item, the control section is configured to select the feature quantities related to the selected predetermined word on the basis of the information stored in the other storage section, and is configured to display a list of the selected feature quantities.

3. An information processing apparatus for presenting information on an item selected in accordance with a user's preference, the information including a comment on the item, the apparatus comprising: a processor, wherein the processor is configured to: store comment data on the item, wherein the comment data includes comment information in the form of sentences describing the item; select a keyword from words in the comment data; store content data on the item, wherein the content data includes content information representing the item; extract a feature quantity of the content data; verbalize the feature quantity in the form of a word corresponding to the feature quantity, based on a dictionary that shows a relationship between the feature quantity and the word; match the keyword and the word corresponding to the feature quantity with user preference information; and control presentation of information on the item selected in accordance with the user's preference by displaying the word corresponding to the feature quantity in a format different from other words out of words constituting the comment, the word contributing to the selection of the item.

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1. A non-transitory computer readable medium comprising instructions, the instructions operable when executed by a processor to: receive a database selection message from a database client; transmit an unconditional acknowledgement to the database client in response to the database selection message; access a database query from a queue of queries from the database client, the database query comprising a user identifier and a database identifier; determine whether a matching backend database connection exists, the matching backend database connection having a user identifier equivalent to the user identifier of the database query and a database identifier that is equivalent to the database identifier of the database query; if a matching backend database connection exists, forward the database query to the matching backend database connection; and determine, in response to determining that the matching backend database does not exist, whether a similar backend database connection exists, the similar backend database connection having a user identifier equivalent to the user identifier of the database query and a database identifier not equivalent to the database identifier of the database query, or having the user identifier not equivalent to the user identifier of the database query and the database identifier that is equivalent to the database identifier of the database query; if the similar backend database connection exists and the user identifier of the similar backend database connection is equivalent to the user identifier of the database query, transmit a request to a database server to switch the database identifier of the similar backend connection to the database identifier of the database query; and if the similar backend database connection exists and the database identifier of the similar backend database connection is equivalent to the database identifier of the database query, transmit a request to switch the user identifier of the similar backend database connection to the user identifier of the database query.

2. The non-transitory computer readable medium of claim 1 , wherein the instructions are further operable when executed by the processor to, if the similar backend database connection does not exist, transmit a request to the database server to establish a new connection using the user identifier and database identifier of the database query.

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6. The method of claim 1 , wherein performing the at least one second processing stage comprises performing at least one speech processing stage including at least one of automatic speech recognition on the acoustic input, at least one classification processing stage, and at least one natural language processing stage to understand the meaning of the voice command.

7. The method of claim 6 , wherein performing the at least one second processing stage comprises performing limited vocabulary automatic speech recognition on the acoustic input to detect whether the acoustic input includes an explicit voice trigger.

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1. A method for tracking known topics in a plurality of interactions, the method comprising: extracting, by a processor, a plurality of fragments from the plurality of interactions, the plurality of interactions occurring over a particular time period, each fragment of the plurality of fragments comprising one or more words; initializing, by the processor, a collection of tracked topics to an empty collection; computing, by the processor, a similarity between each fragment of the fragments and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic; adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value; and returning, by the processor, a collection of the tracked topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the tracked topics occur in the plurality of interactions during the particular time period.

7. The method of claim 1 , further comprising: generating, by the processor, a visualization of the tracked topics.

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15. The method of claim 14 , further comprising: selecting a format for display of the results data by activating a control in the GUI.

14. A method for operating a graphical user interface (GUI) for a system for querying web data, comprising: entering a query language (QL) statement in a query entry window of the GUI, wherein the QL statement identifies one or more QL tables associated with one or more web data sources, wherein each of the one or more QL tables includes binding data which includes instructions for a QL web service on creating a universal resource locator (URL) to access and retrieve data from a web data source, and for interfacing with the web data source and interacting with the web data source in order to query the web data source for specific data present at the web data source, and wherein the binding data of each of the one or more QL tables informs the QL web service as to what types of data are present within the web data source; generating a QL web service URL defined to execute the QL statement, the QL web service URL defined to access one or more QL tables identified in the QL statement through the Internet and retrieve direction from the one or more QL tables regarding access and retrieval of data from the one or more web data sources associated with the one or more QL tables identified in the QL statement; executing the QL statement through a QL web service underlying the graphical user interface via the generated QL web service URL; displaying results data generated by execution of the QL statement in a results display window of the GUI; and displaying the QL web service URL defined to execute the QL statement in a URL display window of the GUI.

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26. The apparatus of claim 22 , wherein said client system uses said raw data and presentation components to create displays to a user.

22. An apparatus for a framework architecture for client systems, comprising: a server proxy client; said server proxy client for receiving a client information request from a client system; said server proxy client determining the proper server to service said client request; sending said client request to said proper server; receiving said proper server's response to said client request; and sending presentation and logic component updates to said client system; wherein said server proxy client acts as a proxy client for said client system, performing the bulk of data processing for said client system; wherein said server proxy client, upon receipt of a request for specific up to date presentation components from a client system, checks if the client system's original presentation components and/or executable bytecodes have expired; wherein said server proxy client updates said client system with raw data, said presentation, and said logic components using a universal data format; wherein said server proxy client separates raw data and presentation components of said response and places said raw data component into said universal data format, wherein said raw data and said presentation components are sent independently by said server proxy client to said client system; sending said raw data component to said client system; wherein said server proxy client receives presentation and logic component updates for said client system; wherein said presentation component updates are for a specific client device type; wherein said logic component updates comprise updates to a common code base that is shared between different client device types and which enables said server proxy client to control a feature set of said client system independently of an implementation supplied by native client code and without modifying said native client code; wherein said client system reuses at least a portion of said raw data component for other display purposes; and saving state information on said client.

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14. A system as in claim 3 , wherein processes include one or more process outputs.

3. A system for defining a human resources system, comprising: a processor; a storage module for storing data associated with the human resources system; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive at least one new metadata model that defines at least one new object class in the human resource system, wherein the new metadata model includes one or more attributes, one or more relationships, and one or more methods associated with the new object class; receive process definitions; store the new metadata model including data associated with the new metadata model, and the process definitions in a minimalistic metamodel for persistence, wherein the minimalistic metamodel for persistence comprises three tables comprising an instance table, an attribute table, and a reference table for all of the objects in the human resources system, wherein the new metadata model including data associated with the new metadata model is stored by storing one or more instances of the new object class in the instance table, the one or more attributes in the attribute table, and the one or more relationships in the reference table, wherein: the instance table stores all instances of object classes in the human resource system as defined by a plurality of metadata models; the attribute table stores attribute data associated with all the instances of the object classes as defined by the plurality of metadata models; the reference table stores relationship data associated with all the instances of the object classes as defined by the plurality of metadata models; the instance table, the attribute table, and the reference table store data that has been specified; metadata model definitions and the process definitions are able to be interpreted using an interpretive engine; and the interpretive engine is configured to process the metadata model definitions and process definitions without compilation of any code; at a time of execution by the interpretive engine, all the objects specified in the instance table, the attribute table, and the reference table and processes are loaded into the memory for easy modification of instances of objects defined by the plurality of metadata models and the new metadata model; and for a process of one or more processes defined by the process definitions: defining an element to which the process responds; defining one or more process steps in response to the element; and defining an output response, wherein the process when interpreted by the interpretive engine are sufficient to define a fully functional human resource system; receive an update, wherein the update includes a change to an existing instance of an object class in the human resource system; update the human resource system by adding, removing, or changing a plurality of entries associated with the existing instance of the object class in at least one of the instance table, the attribute table, and the reference table, comprising: validate a transaction request relating to the existing instance of the object class, comprising: ensure a requestor has privileges to perform a requested transaction; check whether the transaction request corresponds to a metadata definition of an element of the transaction request; and ensure that data in the requested transaction is of a correct type and in a correct range of values; determine whether a controlling object to be updated exists, wherein the instances of the object class are organized in a tree structure, the controlling object relating to a trunk of the tree structure; in the event that the controlling object to be updated does not exist create the controlling object; and in the event that the controlling object to be updated exists, locate the controlling object associated with an instance of the object class; transfer the plurality of entries associated with the existing instance of the object class in the at least one of the instance table, the attribute table, and the reference table to the storage module after the updating of the human resource system is performed, wherein the transferring of the plurality of entries to the storage module is performed after each of the adding, removing, or changing to the plurality of entries have been completed to avoid inconsistencies in the human resource system the storage module including permanent storage; and execute the updated human resources system by interpreting the stored metadata model definitions and process definitions using the interpretive engine.

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5. The method of claim 1 , wherein the statistical training comprises a k-means clustering algorithm.

1. A method for generating patterns for use in online character recognition, the method comprising: performing one or more pre-processing operations on a character sample; performing one or more feature extraction operations on the character sample, wherein the one or more feature extraction operations produce a feature vector for the character sample, wherein said performing the one or more feature extraction operations utilizes a Gabor filter, wherein the one or more feature extraction operations comprise: extracting directional features based on the direction of the character sample's points; generating directional pattern images based on the directional features; filtering the directional pattern images using a Gabor filter; and forming the feature vector based on the filtered directional pattern images; performing statistical training to generate patterns based on the feature vector of the character sample; storing the patterns in a memory, wherein the patterns are configured to be used to recognize handwritten characters.

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13. The non-transitory computer readable medium of claim 9 , wherein the instructions, when executed, further comprise functionality for: assigning the URL class to the URL and assigning the IP tag to the Internet end point if the URL domain name comprises the phrase.

9. A non-transitory computer readable medium, embodying instructions executable by a computer to perform method steps for profiling an Internet endpoint associated with an Internet Protocol (IP) prefix, the instructions, when executed, comprising functionality for: generating a profiling rule using an Internet search engine; obtaining a search result by inputting the IP prefix to the Internet search engine; and classifying the Internet endpoint based on the search result using the profiling rule, wherein the profiling rule comprises a IP tag and a key phrase list having a phrase associated with a URL class, the URL class being associated with the IP tag, wherein the profiling rule further comprises a data structure having an entry, the entry having a first domain name associated with the phrase, wherein the data structure is a cache having a plurality of indexes corresponding to a plurality of values, the plurality of indexes comprising the first domain name, the plurality of values comprising the phrase, wherein the search result comprises: a Uniform Resource Locator (URL) having a second domain name; and a hit text associated with the URL, the hit text comprising a phrase in the key phrase list, wherein classifying the Internet endpoint comprises: assigning the URL class to the URL and assigning the IP tag to the Internet end point if the first domain name is the same as the second domain name, wherein generating the profiling rule comprises: adding an index comprising the second domain name to the cache if the plurality of indexes do not comprise the second domain name; setting a counter to an initial count; obtaining another search result by inputting another Internet endpoint domain name to the Internet search engine, the another search result comprising another hit text associated with another URL; the another hit text comprising another phrase in the key phrase list; incrementing the counter if the another URL comprises the second domain name; and setting a value in the cache corresponding to the index based on at least one selected from the group consisting of the phrase and the another phrase if the counter exceeds a pre-determined threshold.

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1. A method performed on at least one processor for managing speech resources for a plurality of applications, the method comprising the steps of: providing data from a client workstation regarding a first speech application and a first set of speech resources being used by the first speech application, the first speech application being a natural language speech recognition application, wherein the first set of speech resources comprises at least a first language model and a first user profile used by the first speech application to convert audio to text, and wherein providing the data regarding the first speech application and the first set of speech resources comprises: initiating the first speech application at the client workstation, transmitting identification of a client initiating the first speech application at the client workstation, and delivering the first set of speech resources based on at least one of the first speech applications or the identification of the client; receiving data from the client workstation indicative of a switch from the first speech application to a second application; on receiving the data indicative of the switch from the first speech application to the second application, saving a transcription generated by the first speech application using the first set of speech resources; determining whether the second application being used at the client workstation requires a second set of speech resources, wherein the second set of speech resources comprises at least a second language model and a second user profile used by the second application to convert audio to text, wherein the first language model and the first user profile are different than the second language model and the second user profile; and loading the second set of speech resources that comprise at least the second language model to facilitate operation of the second application, wherein the client does not log out of the first speech application prior to initiating the second application.

4. The method of claim 1 wherein receiving the data from the client workstation indicative of the switch comprises receiving an indication that the second application is an active application.

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15. The computer system in accordance with claim 10, wherein said processing means looks up a variable name associated with each said program variable in said static scope means, and, if a corresponding name/value pair is not found in said static scope means for any of said program variables, looks up the variable names for said any program variables in said dynamic scope means.

10. A computer system comprising: A) processing means for processing a computer program, during which a plurality of program values are assigned to a plurality of program variables for evaluating a plurality of functions included in said program; B) a memory for storing a plurality of name/value pairs, each comprising a variable name and an associated value, said memory including i) static scope means for storing a first set of said name/value pairs for which the values for the associated variable names are defined when, during processing of said program by said processing means, a first set of said functions is defined, said first set of said functions including a first plurality of said program variables that correspond to said variable names of said first set of name/value pairs; and ii) dynamic scope means for storing a second set of said name/value pairs for which the values for the associated variable names are defined when, during processing of said program by said processing means, a second set of said functions is applied, said second set of said functions including a second plurality of said program variables that correspond to said variable names of said second set of name/value pairs; and C) during said processing, for each program variable, said processing means checks whether a corresponding name/value pair is stored in said static scope means, and if said static scope means does not store a corresponding name/value pair, said processing means both retrieves a value of one of said name/value pairs corresponding to said program variable from said dynamic scope, and binds said retrieved value as said program value to said program variable.

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9. The method of claim 7 , comprising identifying a portion of the audio message that contains a telephone number, and sending the portion to an ASR component specially configured to automatically recognize telephone numbers.

7. A method for converting an audio voice message from a caller to a recipient to text, the method comprising: processing the audio voice message to identify at least one portion of the audio voice message which contains content of a type for which one of a plurality of ASR components is specially configured to automatically recognize; sending the identified at least one portion of the audio voice message to the one of the plurality of ASR components specially configured for the type of content identified in the at least one portion of the audio voice message to be automatically recognized; receiving, from the ASR component to which the at least one portion of the audio voice message was sent, a text portion corresponding to the automatic recognition of the at least one portion of the audio; assembling the text portion into the text; and outputting the text to the recipient.

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22. The system of claim 14 , wherein the one or more processors are further operable when executing the instructions to: receive an additional information item; determine to which one of the plurality of information topics the additional information item belongs; and decide whether to recommend the additional information item to the first user based on the interest score of the one information topic to which the additional information item belongs.

14. A system comprising: a memory comprising instructions executable by one or more processors; and the one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: for each information item of a plurality of information items in a collection of information associated with a first user; construct a vector space model; and adjust the vector space model by an importance score of the information item, wherein the importance score indicates a level of importance the information item is to the first user; calculate a degree of similarity for every two information items in the collection of information; based on the degree of similarity calculated for every two information items in the collection of information, cluster the plurality of information items in the collection of information associated with the first user to generate a plurality of information topics using the adjusted vector space model of each information item; and for each information topic of the plurality of information topics generated from the collection of information associated with the first user, determine an interest score, which indicates a level of interest the first user has in the information topic relative to other information topics within the plurality of information topics; for each information topic of the plurality of information topics, determining a second interest score, which indicates a level of interest a second user has in the information topic relative to other information topics within the plurality of information topics; determining that the first user shares a common interest in a plurality of common-interest information topics with the second user, wherein the determining that the interest is a shared common interest is based on the difference between the first user's level of interest in an information topic and the second user's level of interest in an information topic, as determined by the interest score and the second interest score respectively, being less than a threshold difference; determining a common-interest strength between the first user and the second user, wherein the common-interest strength is calculated based on: the number of common-interest information topics shared between the first user and the second user, a respective level of interest, as determined by the interest score and the second interest score, by each of the first and the second user in the plurality of common-interest information topics, and a correlation and difference between the respective level of interest in the plurality of common-interest information topics by the first user and the second user, the common-interest strength measuring the strength of connection between the first user and the second user; and establishing a connection in a social network between the first and second users based on the common-interest strength.

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14. A fuzzy rule system in which a fuzzy inference is achieved based on a fuzzy knowledge stored in a knowledge base storage unit, said fuzzy knowledge including fuzzy rules each described in a format having an IF part and a THEN part, and membership functions defining meanings of propositions described in the IF part and the THEN part, said fuzzy rule acquisition system comprising: fuzzy inference execution means for performing a fuzzy inference for at least one input value by using said fuzzy rules of said fuzzy knowledge stored in said knowledge base storage unit, and obtaining a result of the execution of the fuzzy inference; fuzzy inference storage means for storing the execution result of the fuzzy inference; means for comparing the result of the execution of the fuzzy inference with a teaching value, and obtaining an inference error; means for obtaining errors of said fuzzy rules by referring to at least one of combinations of IF parts of said fuzzy rules, combinations of THEN parts of said fuzzy rules, and both of the combinations of the IF parts and THEN parts of said fuzzy rules using said inference error; fuzzy inference error storage means for storing said obtained errors of said fuzzy rules; contradiction determining means for determining whether a pair of said fuzzy rules are mutually contradictory, based on a pair of errors of corresponding rules of said fuzzy rules stored in said fuzzy inference storage unit; means for modifying a fuzzy rule determines as contradictory by using the errors of said fuzzy rules stored said fuzzy inference error storage unit; means for rewriting said fuzzy rule in said knowledge base storage unit determined as contradictory into said modified fuzzy rule; a fuzzy inference unit for performing a fuzzy inference and delivering an inference output, by using input data and said fuzzy knowledge stored in said knowledge base storage unit; means for obtaining ones of the errors and grades of said propositions based on said inference error by referring to at least one of combinations of IF parts of said fuzzy rules, combinations of THEN parts of said fuzzy rules, and both of the combinations of the IF Darts and THEN parts of said fuzzy rules and storing said at least one in said fuzzy inference storage unit; means for determining that there is a missing fuzzy rule if said contradiction determining means judges that there is no contradiction for all said fuzzy rules, and for generating said missing fuzzy rule as new combinations of said propositions based on ones of the errors and grades of said propositions stored in said fuzzy inference error storage unit; and means for adding said generated missing fuzzy rule to said knowledge base storage unit.

15. A fuzzy rule acquisition method according to claim 14, wherein said means for modifying a fuzzy rule modifies the fuzzy rule by changing combinations of IF parts of said fuzzy rules, combinations of THEN pares of said fuzzy rules, or both the combinations IF parts and THEN parts of said fuzzy rules.

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3. The method claim 2 further comprising the step of: for each record in the second comparison reference database, generating a second set of substrings based upon a second set of data fields from the plurality of data fields in the record; and comparing the second set of substrings against the set of strings to identify a longest substring match, if any, for each of the second set of data fields from the record; and filtering the second comparison reference database to generate a third comparison reference database by selecting each record that has a longest substring match for one or more data fields from the second set of data fields.

2. The method of claim 1 further comprises the step of: filtering the second comparison reference database based upon proximity within the set of strings of at least two of the longest substring matches of a record from the comparison reference database.

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10. A client device to receive server information, comprising: a web browser that receives authorization, via a digital certificate, to permit access of the client device to a web page content server, and that sends a request for web page content to the web page content server, the web page content including logging information associated with at least one of a plurality of monitored servers, the logging information comprising at least one of start/stop time information and error information; and a physical receiver associated with the web browser to receive the web page content; wherein the web page content is parsable to extract particular information about a particular server from the at least one of the plurality of monitored servers.

18. The client device to receive server information according to claim 10 , further comprising: a mobile library optimized for an underlying wireless protocol used by the web browser.

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5. The method of claim 4 , wherein the DAS received at the TPPD includes one or more spoken words provided by the user, and wherein at least a portion of the decompressed data in the TPPD corresponds to the one or more spoken words provided by the user.

4. The method of claim 3 , wherein processing of the DAS received at the TPPD includes decompressing the compressed data included in the received DAS.

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18. A system comprising: a knowledge base information module comprising one or more computer processor devices configured to access one or more memories that store document information about documents in a knowledge base, the document information identifying relationships between the documents and contributors to the knowledge base, and personal network information with respect to personal networks of respective contributors to the knowledge base, each personal network defining personal connections between respective contributors forming part of the personal network, wherein each personal network is structured such that nodes of the network are provided by the respective contributors, each personal connection comprises a connection defined directly between two of the nodes of the personal network; a ranking calculator comprising at least one computer processor device configured to perform one or more automated operations to calculate respective ranking values for two or more of the contributors, the ranking calculator comprising: a document factor module to calculate for each of the two or more contributors a document factor calculated as a quantified value based on one or more properties of the document information for the corresponding contributor, and a personal network factor module to calculate for each of the two or more contributors a personal network factor calculated as a quantified value based on one or more properties of the personal network information of the corresponding contributor, the ranking calculator being configured to calculate the respective ranking factors based at least in part on the corresponding document factor and based at least in part on the corresponding personal network factor.

33. The system of claim 18 , further comprising a search module to: receive a search query including one or more search parameters; identify candidate contributors in the knowledge base that satisfy the search parameters; and produce a search result based at least in part on the ranking values for the respective candidate contributors.

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1. A computer implemented system that facilitates graphical design of a regular expression, comprising a memory having stored therein the following computer executable components: a data store component that stores information; a data view component that enables a user to display one or more parts of the stored information, wherein the stored information is stored in a plurality of different data formats; a metadata component that defines how data files of each different data format type are to be parsed, such that a generic parser is usable for parsing the plurality of different stored data types; a data selection component that enables the user to graphically and arbitrarily select any portion of text from the displayed information, regardless of the data format; a rendering component that automatically generates a regular expression comprising one or more specialized characters or character sets that have a predefined meaning for parsing text, the regular expression being derived from and based on the graphically and arbitrarily selected portion of text, wherein the rendered regular expression comprises a custom metadata annotation applied by the generic parser indicating the data type of the selected portion of text, and wherein the automatically generated regular expression is displayed in syntactical form including the one or more specialized characters and/or character sets; and a processor that executes the computer executable components, wherein the rendering component comprises a heuristics component that employs at least one of a probabilistic-based or statistical-based analysis to automatically generate the regular expression.

4. The system of claim 1 , further comprising a dialog box that includes a data view area from which the user selects the text, an expression view area that displays the automatically generated regular expression, and a data tool area that renders a graphical link to at least one of data selection tools or annotation tools.

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31. The computer program product of claim 29 further comprising computer instructions for receiving information associated with the usage by the second client of the shared content.

29. A computer program product for distributing an electronic document, the computer program product being embodied in a non-transitory computer readable storage medium or memory device and comprising computer instructions for: maintaining the electronic document in a memory; associating with a copy of the electronic document one or more rights, wherein each of said rights defines an action capable of being performed on at least a portion of the copy of the electronic document; and providing the copy of the electronic document in a form that allows a first client to exercise the one or more rights associated with the copy of the electronic document, wherein one of the rights associated with the copy of the electronic document includes the ability of the first client to share with a second client rights to at least a portion of a body of content of the electronic document to enable the second client to access the shared content based on rights derived from the first client through an act of said sharing even if the second client is not otherwise entitled to access the shared content, and wherein said second client receives said at least a portion of said shared body of content from said central server only after the second client's rights to receive the shared content, as derived from the first client, are exercised by said second client such that the exercise of such rights by said second client directly causes the shared content to be delivered to the second client.

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4. A method comprising: providing configuration information to a user application configurable according to the configuration information, the configuration information, after provision, configuring the user application to communicate a plurality of user submissions receiving the plurality of user submissions from the user application configured according to the provided configuration information; and publishing the plurality of user submissions received from the user application configured according to the provided configuration information, the publishing being performed by a processor of a machine.

12. The method of claim 4 , wherein: the configuration information includes at least one of: a software module update of the user application, a category update of the user application, an attribute update of the user application, or a language update of the user application.

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38. The computer-implemented method of claim 32 , wherein the endorsements comprise endorsements of advertisements.

32. A computer-implemented method, comprising: receiving, from particular members of a network, endorsements of electronic articles that that are presented to members of the network, particular ones of the endorsements involving a member of the network affirmatively selecting an endorsement control that is displayed simultaneously with a reference to a corresponding electronic article being endorsed; receiving a local search query from a first member that is for a particular geographic locality; searching one or more article indexes to identify a plurality of local search results that are responsive to the received local search query and correspond to the particular geographic locality, the one or more indexes indexing the electronic articles that are presented to members of the network; identifying, for particular ones of the local search results, corresponding endorsements received from particular members; ranking the plurality of local search results based at least in part on the identified endorsements; and providing references to the ranked local search results for presentation to the first member, wherein the presentation identifies, for particular ones of the references to the search results, particular ones of the members identified as having provided endorsements for the corresponding electronic articles.

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17. The at least one non-transitory computer-readable storage medium of claim 15 , wherein each of the alternative hypotheses represents a different semantic meaning.

15. At least one non-transitory computer-readable storage medium encoded with computer-executable instructions that, when executed, perform a method comprising: accessing a text documenting a patient encounter; analyzing the text to identify a set of one or more features of at least a portion of the text; correlating the set of one or more features to a set of alternative hypotheses for an abstract semantic concept representing an intended semantic meaning of the at least a portion of the text; computing, using at least one statistical model implemented using at least one processor and for each of at least some of the alternative hypotheses of the set, one or more measures of estimated likelihood that the respective alternative hypothesis accurately represents the intended semantic meaning of the at least a portion of the text; identifying hypotheses, including some or all of the at least some of the alternative hypotheses, to be presented to a user, wherein identifying the hypotheses comprises, for each of the at least some of the alternative hypotheses of the set: in response to determining that the one or more measures of estimated likelihood for the alternative hypothesis satisfy one or more criteria, identifying that the alternative hypothesis is to be presented to the user; and presenting the identified hypotheses, to the user documenting the patient encounter, as alternative hypotheses for a medical fact that could be extracted from the text.

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18. The conversational sentence translation apparatus according to claim 17, further comprising an index for associating a semantic feature with a set composed of a conversational sentence example registered in the bilingual database and a semantic feature string that is one of the semantic feature strings for the conversational sentence example and that contains the pertinent semantic feature, such that the set of the conversational sentence example and the semantic feature string is obtained from the semantic feature, wherein the semantic searcher searches the individual semantic feature strings of each conversational sentence example registered in the bilingual database for the semantic features extracted by the analyzer by the use of the index.

17. The conversational sentence translation apparatus according to claim 1, wherein the information on a conversational sentence example registered in the bilingual database further includes one or more semantic feature strings of one or more assumed sentences semantically similar to the conversational sentence example, in addition to the semantic feature string of the conversational sentence example itself, and the semantic searcher performs the operation to search the bilingual database for the semantic features extracted by the analyzer to select a conversational sentence example, for each of the plurality of semantic feature strings of the pertinent conversational sentence example, independently.

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20. The system of claim 13 , wherein the digitized text for the representative word image is selected by: displaying the representative word image to a handwriting analyst; and receiving the selected digitized text from the handwriting analyst based on the displayed representative word.

13. A system for creating digitized text for a record from an image of the record, comprising: one or more processors; and a memory, the memory storing instructions that are executable by the one or more processors and configure the system to: obtain one or more digital images of a record; evaluate the digital images in order to locate each of multiple word images; for each located word image, identify multiple word features of that word image; assign, to one group of word images, designated ones of the multiple word images based on the distance between the multiple word images, the distance representing the similarity of word features between at least two of the word images; select a representative word image in the one group of word images, by calculating, at the system, word feature values for the word features of each of the multiple word images assigned to the one group of word images, and using the word feature values to determine, at the system, a word image that is representative of the word images in the one group of word images; select digitized text for the representative word image; and assign the selected digitized text to each of the word images in the one group of word images.

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9. The system of claim 7 , wherein the instructions include instructions executable to provide the user access to the database.

7. A system, comprising: a memory; and a processor configured to execute instructions stored on the memory to: receive a request from a user to access a webpage to apply for a product; in response to receiving the request to access the webpage, search the at least two disparate data sources to determine a set of common data elements that includes data items related to the identified user, at least some of the data items needed for a web document for applying for the product, the data items including information about the user previously entered by the user; store by a computing device, the set of common data elements and associated data items related to the identified user in a database; for at least one common data element in the set of common data elements: compare a first format of a first data item needed for the web document from the first data source with a second format of a second data item needed for the web document from the second data source, identify a difference in the first format and the second format based on the comparison, in response to identifying the difference in the formats, select a preferred format for the web document, generate a modified common data element in which at least one of the first data item or the second data item is modified in accordance with the preferred format; and automatically generate the web document using the modified common data element so that the user does not have to re-enter the information about the user.

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1. A computer system, comprising at least one processor coupled to at least one computer-readable storage medium storing instructions executable by the at least one processor to implement: an application component including computer executable functionality; a group component configured to facilitate execution of each of a positional, multi-member, and multi-level group operator specified by the application component, positional group operators being operators for which position within an ordering of one or more elements affects results of the operators, multi-member operators being operators that can cause a specific element to concurrently occupy a plurality of groups, multi-level group operators being operators that can cause a first group to be nested within a second group; and an injector component configured to identify a reference to a group operator in the group component, fetch functionality corresponding to the identified group operator from the group component and inject the functionality into the application component to produce new executable grouping functionality, the injector component being configured to identify, fetch, and inject when the application component is encoded in any of a plurality of program languages.

4. The system of claim 1 , wherein the group operator is executable across different data sources.

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1. A method of identifying attributes in a sentence, the method comprising: representing the sentence as a first feature vector; training a binary classifier a first time with a support vector machine based classification model using a one-against-all mechanism, based upon the first feature vector; obtaining a vector of probability for the sentence, wherein the vector of probability for the sentence stores a probability of the sentence belonging to an attribute category; concatenating the first feature vector with the vector of probability to obtain a second feature vector; and training the binary classifier a second time with the support vector machine based classification model using the one-against-all mechanism, based upon the second feature vector.

2. The method as recited in claim 1 , wherein the sentence comprises a plurality of attributes.

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18. The computing device of claim 17 , wherein the resource corresponding to the browser is unique to the instance of execution of the browser-executable component and the code is used to name the search record such that a local copy of the search record is not available in a cache of the browser.

17. The computing device of claim 15 , wherein the search record includes the code corresponding to the instance of execution of the browser-executable component, and wherein the browser-executable component is configured to request a resource corresponding to the browser from the computing device.

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9. The method of claim 1 , wherein when figures are input to a plurality of cells in the table, the table provides arithmetic function for the figures in the plurality of cells.

1. A method for creating a document using an electronic apparatus, the method comprising: displaying at least one addition visual element in or around a text box, in response to input of a text box generating command; and adding a cell to the text box and converting the text box into a table, in response to selection of one of the at least one addition visual element, wherein a number of addition visual elements displayed in or around a text box is configurable by a user, wherein when the table includes a plurality of rows and a plurality of columns, and one of a plurality of cells in the table is selected, displaying an addition visual element in at least one of up and down and left and right directions of the selected cell, and wherein insertion of an addition visual element is prevented by at least one computer processor of the electronic apparatus if the insertion of the addition visual element would duplicate functionality of an existing addition visual element based on a position of the existing addition visual element relative to the selected cell.

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8. The system of claim 6 wherein the normalization module converts the native data representation format for each security sensor into XML (Extensible Markup Language) format, and wherein the native data representation format encompasses native sensor data including text data and binary data represented in a proprietary format, and wherein the native sensor data includes at least one of a command or sensor state information.

6. A system comprising: an interface circuit interfacing to a plurality of security sensor types distributed throughout a plurality of sites, each sensor type configured to respond to a corresponding type of actionable event, each sensor type provided by a different manufacturer of a plurality of manufacturers; an integration circuit including a processing agent for each type of security sensor to accept sensor data from each security sensor in a native data representation format of each respective manufacturer of the plurality of manufacturers; a central security management processor coupled to the integration circuit and configured to manage individual user profiles and their respective access privileges and credentials in the system; a normalization circuit mapping the sensor data from each security sensor in the native data representation format of each manufacturer of the plurality of manufacturers to a common data representation format, the common data representation format including a data object and processing information for the sensor data, the normalization circuit further configured to generate unique physical access privileges and credentials to exclusively map a user's profile to a spatial hierarchy of physical sites along with security devices of the system, wherein the unique physical access credentials maintain a common representation of the user's identity across the plurality of sites and to associate specific user identities with respective actionable events; a visual policy manager circuit defining, at design time, physical security policies in the context of user profiles at all sites through actionable representations of physical, network and information technology resources of the sites, wherein the security policies define standardized rule definitions through visual rules depicted by live objects that contain attributes to define their spatial relationship to the actionable representations, and that are applied to the actionable events normalized to the common data representation format to produce normalized event data; and a signal processing circuit receiving the normalized event data and applying, at run time, relevant transformation and routing rules comprising condition-action sequences in order to maintain user profiles and physical security states across the plurality of sites and to resolve the actionable events through the associated specific user identities.

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3. A method for providing characters and character groups from a roundel image comprising the steps of: vertically-aligning a region of electronically represented text in the roundel image; determining a point at which the roundel image starts; electronically analyzing the region to produce characters and character confidences; dividing the roundel image into sections according to the point; selecting the characters associated with highest character confidence values of the character confidences; computing character group confidences by summing the highest character confidence values for each of the selected characters that form the character groups; selecting the character groups with highest character group confidence values of the character group confidences as the selected character groups; marking each of the selected character groups as flipped; creating flipped marked character groups if the selected character group meets pre-determined criteria; marking each of the selected character groups in one of the sections as unflipped if none of the selected character groups in the one section is flipped, or if the one section includes predetermined text that is unflipped; if there are the flipped marked character groups, creating an image by rearranging the underlying representation of the flipped marked character groups; electronically analyzing the image to produce new characters each associated with new character confidences; selecting final characters according to the associated new character confidences; and providing the final characters to an electronic sink.

5. The method as in claim 3 wherein said step of marking each of the selected character groups as flipped comprises the steps of: combining adjacent characters to form combined character groups; computing combined confidence values for each of the combined character groups; computing flipped combined confidence values for each of the flipped combined character groups; marking one the combined character groups as flipped after comparing if the flipped combined confidence value for the associated flipped combined character group is greater by a pre-determined amount than the combined confidence value for the corresponding character group; and performing pre-determined functions on the combined character groups according to the character length of the combined character groups.

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97. The computing system of claim 96 , wherein the query includes the tokens identified from the selected data record, and tokens that were identified from other received data records and that have a variant relationship to the tokens identified from the selected data record.

96. The computing system of claim 93 , wherein generating the query includes identifying tokens that each include at least one value or fragment of a value in a field or a combination of fields of the selected data record.

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11. The method recited in claim 9 wherein the predetermined phonemes are identified by: processing spectral values using a low variance filter to retain category-specific data points conjectured to encode the most relevant cognitive information pertaining to the corresponding category, and; processing the filter output with a principle component analysis processor to reduce the data to a feature vector.

12. The method recited in claim 11 further comprising high-activation filtering the auditory response values to retain category-specific data points that are robust toward interference.

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10. The method of claim 1 , further comprising determining for a distinguished one of the selected context attributes a processing technique to which a logged value of the distinguished context attribute is to be subjected at a time subsequent to logging.

11. The method of claim 10 wherein the determined processing technique is specified by user input.

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16. The system of claim 13 , wherein determining the respective likeness scores of the particular users in relation to the first user, comprises: identifying one or more discriminating attributes; obtaining a weighted vector of attributes for the first user and for each of the particular users; adjusting a respective weight of the discriminating attributes in each of the vectors; and calculating the respective likeness score of each of the particular users as a difference between the weighted vector of attributes of the particular user and the weighted vector of attributes of the first user.

21. The system of claim 16 , wherein a particular attribute comprises a profession, a company, time of employment, location of employment, or an attribute that is unrelated to employment.

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16. The processor-readable medium of claim 14 , wherein the additional information corresponds to at least one standard code.

17. The processor-readable medium of claim 16 , wherein the at least one standard code comprises at least one code selected from the group consisting of an ICD code, a CPT code, an E&M code, and a SNOMED code.

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27. The method of claim 24, wherein said group identifying step includes the step of identifying, as noise groups of connected components having a boundary with a height less than one-third of the ninetieth percentile height.

24. The method of claim 19, further including the steps of: (a) identifying those groups of connected components which represent noise in the image; and (b) removing the groups of connected components identified in step (a).

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20. The method according to claim 17 , further including receiving a second control signal from a wireless second mobile device associated with a second user.

17. A method, comprising: receiving with a speech recognition unit a first control signal comprising a radio signal from a wireless first mobile device associated with a first user, wherein the first control signal is unrelated to speech of the first user; receiving a first speech signal from the first user associated with the first mobile device; receiving an audio signal from the first mobile device and determining a distance of the first user by measuring a difference in transmission time between the radio signal and the audio signal; and identifying, using a computer processor, the first user from the first control signal and configuring speech settings for speech recognition of speech by the first user based on the identity of the first user and the determined distance.

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5. A method for analyzing human speech, comprising: providing a computer, providing a microphone operably connected to said computer and arranged to receive turns made by a human speaker, providing a software program operable in said computer for recognizing said turns, storing all of said turns in an archival database, analyzing said turns using said software program to identify said human speaker, to recognize words and sounds uttered by said speaker, to recognize both turns and arrays of turns taken by said speaker, and to store the resultant analysis of said turns and arrays of said turns in a data stream record, whereby said archival database contains a record of all of said turns and said data stream record contains said analysis of said turns.

6. The method of claim 5 wherein said software program includes voice recognition software for classifying said turns as either a pause, in-breath, word, vowel extension, question intonation, or sentence intonation.