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5. The system for content recognition, search, and retrieval in visual data as set forth in claim 4 , wherein the hierarchical content descriptor module comprises a second level for modeling a set of motion trajectories of at least one moving object or salient blob in the unlabeled visual data.

4. The system for content recognition, search, and retrieval in visual data as set forth in claim 3 , wherein the hierarchical content descriptor module comprises a first level for detecting a set of salient spatiotemporal regions which are abstracted into a set of activity-agnostic spatiotemporal visual words, wherein a collection of each of the sets of activity-agnostic spatiotemporal visual words form a visual vocabulary.

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11. The method of claim 9 , wherein selecting the output text to use comprises: for each OCR engine, setting a weight for the output text received from the OCR engine as equal to the confidence value of the OCR engine for the given text type of the unknown text; where the output text received from two or more OCR engines of the plurality of OCR engines is identical, summing the weights for the two or more OCR engines as the weight for the output text received from the two or more OCR engines; and, selecting the output text having a highest weight.

9. The method of claim 1 , further comprising: receiving, by the processor, an image of unknown text having a given text type; inputting the image of the unknown text, by the processor, into each OCR engine; receiving output text corresponding to the image of the unknown text, by the processor, from each OCR engine; where the output text received from each OCR engine is not identical, selecting the output text to use as at least provisionally correct for the unknown text, by the processor, based on the confidence values of the OCR engines for the given text type of the unknown text.

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40. The semantic network of claim 33 , wherein semantic applications being added to the plurality of semantic servers while the semantic servers operate without disrupting operation thereof.

33. A semantic network providing a network semantic graph comprising concept instances and relations between the concept instances, the semantic network comprising: a plurality of semantic servers in communication with each other and with distributed sources, wherein each of the plurality of semantic servers comprises: an input/output module to receive data including semantically descriptive annotations from the distributed sources; a processor programmed to process the data based on the semantically descriptive annotations of the data to form a local semantic graph that associates the concept instances with each other using the relations, to create at least one subscription of interest in response to a request from at least one client and to send at least one alert to the at least one client based on updates to the local semantic graph matching the at least one subscription of the at least one client; and memory for storing the local semantic graph; wherein each local semantic graph of each of the plurality of semantic servers comprises a portion of the network semantic graph distributed across the plurality of semantic servers.

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4. The method of claim 3 , further comprising overriding said styles by applying a local theme.

3. The method of claim 1 , further comprising organizing said styles into themes.

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22. The handheld electronic device of claim 12 wherein the operations further comprise: identifying as the particular language object a word object representative of a relatively lower-frequency ambiguous word, and identifying as the another language object a word object representative of a relatively higher-frequency ambiguous word, in response to said determining the contextual value, outputting the lower-frequency ambiguous word at a position of preference with respect to an output position of the higher-frequency ambiguous word.

12. A handheld electronic device comprising an input apparatus, a processor apparatus, and an output apparatus, the input apparatus comprising a number of input members, the processor apparatus comprising a processor and a memory having stored therein a plurality of objects comprising a plurality of language objects, a plurality of frequency objects, and a number of contextual values, at least some of the language objects each having associated therewith a frequency object having a frequency value, at least some of the language objects each having associated therewith at least a first contextual value, the memory having stored therein a number of routines which, when executed by the processor, cause the handheld electronic device to be adapted to perform operations comprising: detecting a first input and a second input, the second input comprising an ambiguous input that comprises a number of input member actuations; outputting as a first output an interpretation of the first input; determining that a particular language object having associated therewith a particular frequency object having a particular frequency value corresponds with the ambiguous input; determining that another language object corresponding to the ambiguous input has associated therewith another frequency object having another frequency value, the another frequency value being higher than the particular frequency value; determining, by the handheld electronic device, that a contextual value associated with the particular language object coincides with at least one of a representation of the first input and a representation of the first output; and in response to said determining the contextual value, outputting the particular language object as an interpretation of the ambiguous input in a position of preference with respect to a position represented by the particular frequency value.

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12. The non-transitory machine readable medium of claim 1 , wherein the set of property descriptions of the JSON file, based on the JS object that is instantiated, comprises a set of attributes that identifies a data storage from which the JS object retrieves data, the set of attributes comprising at least one of a location of the data storage, a name of the data storage, a set of fields of the data storage, and a set of field attributes of the data storage.

1. A non-transitory machine readable medium of a server storing a program for processing application programming interface (API) requests received from mobile devices, the program executable by one or more processors of the server, the program comprising: a runtime instantiator for instantiating JavaScript (JS) objects, said instantiated JS objects configured to process the API requests, each JS object instantiated based on a JS model that comprises (i) a JS file storing a set of behavioral descriptions of the JS objects and (ii) a JS object notation (JSON) file storing a set of property descriptions of the JS objects, wherein the JSON file includes at least one validation rule to reject a data tuple unless the data tuple meets a required constraint specified in the validation rule; a data abstractor for serving as an interface between the JS objects and a set of data storages from which the JS objects retrieve data while processing a plurality of the API requests; and a data connector for connecting the data abstractor with the set of data storages by implementing a data exchange logic for the set of data storages, wherein the set of property descriptions of the JSON file, based on a JS object that is instantiated, comprises a description of a control logic for restricting access to one or more data tuples that are available to the JS object upon processing an API request, and wherein the control logic comprises at least one access control list (ACL) rule to ensure that a data tuple that is exchanged as part of the API request with the JS object satisfies a set of access control criteria.

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6. A method comprising: determining a time allotted to consume a portion of a media item; determining a consumption rate; calculating a range of words to be included in the portion of a media item based at least in part on the desired time and the consumption rate; determining an endpoint located within the media item with the range of words, the endpoint being a logical break to define a segment of the media item, wherein the endpoint separates a continuous body of content included in the media item; associating the endpoint with the media item without modifying the media item; and causing presentation of the media item.

10. The method as recited in claim 6 , wherein determining the consumption rate includes analyzing consumption of a prior portion of the media item to determine the consumption rate associated with the media item.

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18. The computer program product of claim 17 , wherein the actual link corresponding to the hypothetical ontological link, comprises at least one of a corresponding link type from a plurality of possible link types, a link category, from a plurality of possible link categories, associated with the corresponding link type, and the score for the hypothetical ontological link.

17. The computer program product of claim 10 , wherein the computer readable program further causes the data processing system to output information associated with the hypothetical ontological link based on the score for the hypothetical ontological link at least by updating the ontology to include the hypothetical ontological link, as an actual link corresponding to the hypothetical ontological link, in the ontology between the selected information concept object and another information concept object in the ontology, in response to the score for the hypothetical ontological link meeting or exceeding a predetermined criterion.

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8. An email analytics system for performing email analytics on a configured email repository, the email analytics system comprising: a processor; a mail reconstruction module coupled to the processor to: group emails in the configured email repository into a plurality of mail groups based on identifying similarity of content in the emails, wherein each of the plurality mail groups is associated with a timeline; and determine a network graph for each of the plurality of mail groups based on a header information of emails within each of the plurality of mail groups, wherein the network graph indicates an association of emails in the plurality of mail groups; and an email analytics module coupled to the processor to perform email analytics on the plurality of mail groups, wherein the email analytics module performs the following: cluster the plurality of mail groups into a plurality of mail clusters based on a temporal analysis of the emails within each of the email groups wherein the temporal analysis identifies a temporal progression of the emails over the timeline of each of the plurality of mail groups by computing activity density distribution of each of the plurality of mail groups and wherein the plurality of mail clusters are plotted as activity density distribution graphs; determine key phrases from content of emails in the plurality of mail groups in each of the plurality of mail clusters; and associate the key phrases with the network graph of each of plurality of mail groups, wherein the key phrases are indicative of type of activity and state of activity of each of the plurality of mail groups.

13. The email analytics system as claimed in claim 8 , wherein the mail reconstruction module is further configured to determine the network graph for each of the plurality of mail groups based on analysis of the header information of emails within each of the plurality of mail groups.

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16. The non-transitory computer readable storage medium of claim 15 , wherein the first compiler output comprises a plurality of first internal decisions made by the first version of the compiler, the second compiler output comprises a plurality of second internal decisions made by the second version of the compiler, and wherein to execute the at least one test comprises comparing the first plurality of internal decisions with the second plurality of internal decisions to verify that all of the first plurality of internal decisions corresponds to all of the second plurality of internal decisions.

15. A non-transitory computer readable storage medium comprising a regression application comprising modules executable by a processor, the modules comprising: an execution module to: compile a code corpus comprising a plurality of test programs corresponding to a particular programming language, the code corpus being compiled by a first version of the compiler to generate first compiler output; and compile the code corpus using a second version of the compiler to generate second compiler output, the second version of the compiler including different functionality than the first version of the compiler; and an analysis module to: retrieve at least one test corresponding to the first compiler output and the second compiler output; and execute the at least one test to generate a regression result for the second version of the compiler.

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26. A computer-readable medium containing instructions for controlling a computer system to perform a method of extracting information comprising: receiving a plurality of first annotations, the first annotations comprising text; processing the plurality of first annotations using a reusable extraction operator, and in accordance therewith, generating a plurality of second annotations, wherein the extraction operator identifies text in the first annotations that satisfy one or more rules or match text in a predefined list of text, and generates one or more output annotations comprising the identified text; and processing the plurality of second annotations using a reusable context operator, and in accordance therewith, generating a plurality of third annotations, the second annotations comprising text, wherein the context operator receives each of the second annotations and a reference annotation and generates output annotations comprising a plurality of text adjacent to the reference annotation; processing the plurality of third annotations using a reusable composition operator, wherein the composition operator receives each of the third annotations, one or more first reference annotations, and one or more second reference annotations, and generates output annotations comprising text between the first and second reference annotations.

27. The computer-readable medium of claim 26 wherein the composition operator receives a rule, and wherein output annotations comprise text that satisfies the rule, and if an annotation in the plurality of third annotations does not include the first reference annotation or the second reference annotation or does not satisfy said rule, then no output annotation is generated by the composition operator.

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3. The system of claim 1 , wherein the hardware limitation is a memory capacity or a storage capacity of the computing device.

1. A system that facilitates tracking content of a plurality of repositories, the system comprising: one or more processors; one or more memories having stored thereupon a plurality of processor-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform actions comprising: monitoring imported metadata that corresponds to content received into the plurality of repositories to determine that a change occurs with respect to the content; executing a query that monitors the plurality of repositories for metadata that indicates the change with respect to the content; and defining the query based on a hardware limitation of a computing device, the defining including sending a command to omit a notification of the change with respect to the content in response to determining that new content associated with the change has a characteristic that exceeds the hardware limitation of the computing device.

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21. A computer implemented method for classifying an object contained in digital representation of an image, the method comprising: receiving one or more reference shape models; receiving one or more reference appearance models; generating one or more shape models of the object based on shape features extracted from the image, a shape model corresponding to a part of the object, generating a shape model comprising: generating one or more histogram of oriented gradient (HOG) cells for a number of pixel of the image; and grouping two or more HOG cells into a HOG bundle based on similarity of orientations of the HOG cells with respect to the maximum magnitude of orientations of the HOG cells; comparing the generated shape models with the reference shape models; selecting one or more candidate shape models of the object based on the comparison; augmenting each candidate shape model with a corresponding appearance model of the object; and determining classification of the object based on the augmented candidate shape models.

22. The method of claim 21 , wherein determining classification of the object comprises: determining whether there is an object in the image based on the augmented candidate shape models; and responsive to the determination that there is an object in the image, determining location and type of the object.

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13. A non-transitory, machine-readable medium having stored thereon instructions, which if executed by a machine causes the machine to perform a method comprising: retrieving a plurality of streams of modal input data from a user, each stream of modal input data received from a different one of a plurality of modal input devices; interpreting each of the plurality of retrieved modal input data streams into a corresponding of set of actions; assigning each corresponding set of actions to control one of a plurality of displayed objects rendered on a display device; implementing a user interface to enable the user to explicitly assign each stream of modal input to a display object; controlling each displayed object by its assigned set of actions; and dynamically changing a control assignment of a first displayed object of the plurality of displayed objects from a first modal input data stream of a second type of input device having a second type of data different from the first type of data to a second modal input data stream of a second type of input device having a second type of data different from the first type of data, wherein each of the plurality of modal input devices captures a different type of modal input data corresponding with a different type of gameplay action.

18. The non-transitory, machine readable medium of claim 13 , wherein at least one modal input device of the plurality of modal input devices is one of a video camera and a microphone.

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26. A computer-readable storage medium having instructions stored thereon that direct a computing system to, at least: submit a query to a plurality of search indexes, each search index associated with a relevance ranking function for ranking items according to an individual ranking scale, at least two of the individual ranking scales being different; queue a plurality of search index result sets received from the plurality of search indexes, each of the plurality of search index result sets being ordered lists identifying items related to the query and ranked according to one of the individual ranking scales; determine a query index association for each of the plurality of search indexes; and create a universal query result set that includes a list of items obtained from the plurality of search index result sets, the list being ordered based on at least a probability of those items satisfying the query, the list of items containing items obtained from different search index result sets, wherein the probability of the items of the list satisfying the query is determined at least in part by: computing an allocation score for each of the plurality of search indexes, the allocation score for each search index being computed based at least in part upon a relative number of search results in the corresponding search index result set; for each of the plurality of search index result sets, computing a universal item score for at least one item identified in the respective search index result set, the universal item score for each item being computed at least in part by normalizing the individual ranking scale for each of the plurality of search index result sets to a common ranking scale; and determining a probability of each item satisfying the query based at least upon a combination of the allocation score for the search index associated with the item and the universal item score for the item.

34. The computer-readable medium of claim 26 , wherein the probability is a predicted probability.

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20. The computer program product of claim 7 further including removal function indicating means recorded on said data storage medium for generating a removal function indicator in said document display separate from but adjacent to said data field, said removal function indicator being positioned to provide a visual indication of a removal direction in which said data field can be removed, and removing means recorded on said data storage medium responsive to said pointer positioned at said removal function indicator and to a second control input from said cursor control device representing a data field removing command for removing said data field in said document representation.

7. A computer program product for use in a data processing system for providing a menu-driven graphical user interface for the display of text data, the data processing system having a data processing unit, a video display terminal, a keyboard, a cursor control device for providing control inputs to said system and a data storage resource, and the graphical user interface providing a document form display separate from but representation (document representation) on said video display terminal including at least one data field for text entry and display, said computer program product comprising: a data storage medium for storing machine readable information thereon; replication function indicating means recorded on said data storage medium for generating a replication function indicator in said document display separate from but adjacent to said data field, said replication function indicator being positioned to provide a visual indication of a direction in which said data field can be replicated; means recorded on said data storage medium for generating a pointer in said document display; means recorded on said data storage medium for positioning said pointer in said document display in response to a first control input from said cursor control device: and replicating means recorded on said data storage medium responsive to said pointer positioned at said replication function indicator and to a second control input from said cursor control device representing a data field replicating command for replicating said data field in said document representation.

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14. A method comprising: accessing, with a processor, at least a portion of a diagnostic network model that associates a plurality of components and symptoms based upon causal relationships therebetween, wherein the causal relationships associate a failure of respective components and occurrence of the at least one symptom; associating, with the processor, a probability with the causal relationship between a symptom and a respective component whose failure contributes to the symptom, wherein associating a probability comprises providing the probability which was obtained from an individual participating in construction of the diagnostic network model; displaying, with the processor, a representation of the plurality of components and symptoms including a plurality of parent nodes representative of the components, a plurality of child nodes representative of the symptoms and a plurality of influence arcs extending between respective parent and child nodes and associated with respective probabilities; receiving a selection, with the processor, of at least one of the plurality of components and symptoms from among the plurality of components and symptoms that are displayed; and in response to the selection and with the processor, obtaining and displaying additional information related to the at least one of the components and symptoms that is selected.

17. A method according to claim 14 further comprising defining an additional causal relationship between a symptom and a respective component that have been selected.

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12. The computer-implemented method of claim 8 , further comprising: if the specificity score is below the threshold and users likely submit the search query with the intention of general searching, presenting the users with search-result items from a plurality of categories that may be relevant to the search query.

13. The computer-implemented method of claim 12 , wherein a category label is associated with each the search-result items.

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1. An interactive television system configured to allow monitoring of at least one individual, the interactive television system comprising: a communication interface for establishing a communication link between the interactive television system and a server remotely situated from the interactive television system through at least one communication medium; a display for presenting (i) one or more queries and one or more predefined response choices corresponding to the one or more queries provided by a script program received from said server, wherein said script program includes (a) general information, (b) information specific to said individual, and (c) a message corresponding to said individual from a health care professional associated with said individual and (ii) entertainment or advertisement content received from the server through the at least one communication medium, wherein said one or more queries, said one or more predefined response choices, and said message from said script program are displayed along with said entertainment or advertisement content received from said server; a user interface for receiving responses to the one or more queries selected from said one or more predefined response choices by the at least one individual; a processing unit connected to the communication interface, the display and the user interface, wherein the processing unit comprises a non-transitory computer readable medium initialized with a unique identification code for the at least one individual by the healthcare professional prior to the at least one individual receiving the processor unit and the processor unit is configured to execute the script program to (i) present the one or more queries and the one or more predefined response choices on the display, (ii) receive the responses from the user interface, and (iii) transmit the responses to the server through the at least one communication medium, wherein said processor unit is further configured to send said unique identification code for the at least one individual to said server in order to receive said script program and said script program includes a program identifier received from said server by said processing unit and said program identifier (a) is transmitted back to said server with said responses and (b) causes said server to associate said responses with said script program sent by said server to said processing unit; and a device interface connected to the processing unit and configured for receiving measurements from at least one glucose monitoring device, wherein the at least one monitoring device is adapted for producing measurements of a blood glucose level of the at least one individual.

2. The interactive television system according to claim 1 , wherein the processing unit comprises a multimedia processor.

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10. A non-transitory computer-readable storage medium storing executable computer program instructions for document content reconstruction, the computer program instructions comprising instructions for: ingesting a document page in an unstructured document format, having a specified layout; extracting one or more images and metadata associated with the images from the document page; extracting text, and fonts associated with the texts, from the document page, wherein extracting the texts comprises: determining Unicode mappings of the texts in the document page by: mapping a first glyph of a letter to a standard code number in a Unicode chart table, and mapping each of the one or more glyphs of the same letter to a unique code number in Private Use Area (PUA) of the Unicode, wherein each code number in PUA is obtained by masking the standard code number of the first glyph with a unique highest byte offset, extracting all text characters and glyphs from the document page, identifying horizontal and vertical positions of the extracted text characters and glyphs, and extracting fonts associated with every character extracted; coalescing the text into paragraphs; and creating a structured document page in a markup language format using the extracted images, the text and the fonts rendered in accordance with the specified layout of the original ingested document page.

11. The storage medium of claim 10 , wherein extracting one or more images comprises: identifying graphical operations within the page; determining one or more bounding boxes for the identified graphical operations and intersections of the bounding boxes; combining intersecting bounding boxes; and extracting images within each of the combined bounding boxes.

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13. One or more non-transitory computer-readable media storing computer executable instructions that, when executed on processing logic, perform a verification operation, the non-transitory media storing one or more instructions for: initiating the verification operation, the verification operation verifying at least a portion of a model, the model having executable semantics; identifying a first location in the at least a portion of the model, the first location having a complexity that interferes with the verification operation; identifying a source of the complexity at a second location in the model, the second location having a dependency with the first location; eliminating or reducing, at the second location, the source of the complexity; and performing the verification operation, the performing producing a verification result.

14. The one or more non-transitory computer-readable media of claim 13 wherein the source of the complexity is an input, the non-transitory media storing one or more further instructions for: substituting a constrained input for the input that is the source of the complexity.

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13. The integrated customer communications computer system of claim 1 , wherein the communications computer system provides the communications automatically, responsive to a predetermined configurable trigger event or alert.

1. An integrated customer communications computer system, comprising: at least one computer database; and a communications computer system, in communication with said at least one database and at least one component of an account opening system, and configured to provide outbound customer communications, wherein the communications computer system generates documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from said at least one component of the account opening system, and static content for the templates received from a content repository, and wherein the communications computer system includes: a communication manager, comprising: a communication controller receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; a document manager managing documents associated with the communications; and a communication history component maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; a plurality of transmission channels for transmitting the communications; an interface for managing the templates and the content; and a document repository storing, retrieving, and managing storage of the documents wherein the interface for managing the templates is configured to provide a user functionality to create, preview, edit, maintain and delete communication templates for different channels, define what data items are included in the communication, insert dynamic variables that vary by at least one of channel and communication type, define a source of the dynamic data for the communication, and make deployments to various environments for validation.

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3. The method of claim 2 , wherein the sequences of words is at least five words long.

2. The method of claim 1 , wherein the plurality of sequences of words appears in a minimum percentage of the each verbal record in the training set.

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11. An educational toy as claimed in claim 10, wherein means are provided for enabling the images in the second window area and the third window area to be displayed sequentially but not simultaneously.

12. An educational toy as claimed in claim 11, wherein the said means comprise light sources which are energized sequentially.

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9. The computer implemented method of claim 8 , wherein the identifier comprises at least one of a title for the job listing page, a filename for the job listing page, a metadescription for the job listing page, a meta-keyword for the job listing page, and a uniform resource locator (URL) for the job listing page.

8. The computer implemented method of claim 1 further comprising creating an identifier for the job listing page and populating the identifier with the keyword sequence.

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7. The computer system of claim 1 , wherein the taxonomy that is output by said taxonomy manager is a tree having labeled nodes.

1. A computer system including instructions stored on one or more computer-readable medium and executable by one or more processors, the computer system comprising: a statistic calculator configured to receive a plurality of content files and to determine at least one statistical measure of the content of the plurality of content files, said statistic calculator configured to store the at least one statistical measure within a statistics repository; a cluster controller configured to cause the one or more processors to generate a hierarchy of clusters based on the at least one statistical measure stored in the statistics repository, wherein the hierarchy of clusters comprises at least two levels, each cluster within a first level of the hierarchy of clusters comprising at least one content file, each cluster within a second level of the hierarchy of clusters comprising at least one cluster of the first level of the hierarchy of clusters; an aggregator configured to aggregate the content files of each cluster, and transmit the aggregated content file to said cluster controller to form a third level of the hierarchy of clusters; a label manager configured to cause the one or more processors to determine a label for each cluster within the hierarchy of clusters based on the at least one statistical measure, the label identifying a topic of information contained within each cluster, the topic related to at least one of a problem experienced by a user and a request for assistance in solving the problem; and a taxonomy manager configured to cause the one or more processors to output a taxonomy based on the hierarchy of clusters and the determined labels.

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35. A system to select a profile model for use in examining a structure formed on a semiconductor wafer using optical metrology, the system comprising: an optical metrology device configured to provide a measured diffraction signal; a first machine learning system trained using an initial profile model having a set of profile parameters that characterize the structure to be examined, the first machine learning system configured to generate a simulated diffraction signal for an optimized profile model having a set of profile parameters with the same or fewer profile parameters than the initial profile model, wherein the optimized profile model is modified by selecting at least one profile parameter of the optimized profile model to eliminate or fix to a value and the first machine learning system generates another simulated diffraction signal using the modified optimized profile model.

46. The system of claim 35 , wherein if one or more termination criteria are met, at least one profile parameter of the optimized profile model is selected and set to a determined value.

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9. The method of claim 1 , further comprising: determining whether all of the plurality of communication goals have been met; and routing information obtained from the spoken dialog system interactions with the user for task completion if the determining step determines that all of the plurality of communicative goals have been met.

1. A method comprising: receiving a single input communication from a user in a spoken dialog system; generating, via a processor and in response to the single input communication, a plurality of communication goals, wherein the plurality of communication goals are based on a dialog strategy; generating a plurality of sentence plans corresponding to the plurality of communication goals, wherein each sentence plan of the plurality of sentence plans comprises elementary speech acts and is a viable and potentially usable prompt in response to the single input communication; and presenting to the user a selected sentence plan from the plurality of sentence plans as a response to the single input communication.

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8. A device comprising memory storing instructions that, when executed by a computer processor of the device, cause the device to perform a method of speech recognition comprising: processing a speech input to produce a sequence of representative speech vectors; and performing a first recognition pass using a first acoustic model to produce at least one intermediate recognition hypothesis corresponding to the speech input; performing a second recognition pass using a second acoustic model to re-evaluate the at least one intermediate recognition hypothesis and produce a final recognition result corresponding to the speech input; and wherein the second recognition pass is a generic recognition pass that is based on a generic speech recognition arrangement using generic acoustic modeling of a broad general class of input speech; and wherein the first recognition pass is an adapted recognition pass that is based on a speech adapted arrangement using pre-adapted acoustic modeling of a specific sub-class of the general class of input speech.

13. The device according to claim 8 wherein the speech adapted arrangement is based on adapted feature transforms and the first and second recognition passes use the same acoustic models.

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22. The system of claim 15 , where the means for identifying that the particular search result document is similar to the selected search result document, includes: means for determining that the search result document and the selected search result document are located on a same web site, means for determining that the search result document and the selected search result document have a same ratio of images to text, means for determining that a majority of words, in the search result document and the selected search result document, match, means for determining that a majority of uncommon words, in the search result document and the selected search result document, match, means for determining that the search result document and the selected search result document have a plurality of outgoing links pointing to the same documents, means for determining that the search result document and the selected search result document have a plurality of incoming links coming from the same documents, means for determining that the search result document and the selected search result document have same meta-data tags, means for determining that the search result document and the selected search result document have a same format, and means for determining that the search result document and the selected search result document have a same layout.

15. A system, comprising: one or more computer devices comprising: means for receiving, from a user, a first request to perform a search, where the first request includes a first search query; means for performing a first search of a collection of documents, based on the first search query, to identify a set of search result documents; means for receiving a request to save a selected search result document of the plurality of search result documents; means for saving information associated with the selected search result document in response to the request to save the selected search result document; means for receiving, from the user, a second request to perform a search, where the second request includes a second search query, and where the second request is received after the first request is received; means for performing a second search, based on the second search query, to generate a list of search result documents; means for identifying a particular search result document, in the list of search result documents, that is similar to the selected search result document based on the saved information and, where the means for identifying includes at least two of: means for determining whether the particular search result document and the selected search result document have a plurality of outgoing links that point to the same documents, means for determining whether the particular search result document and the selected search result document have a plurality of incoming links that come from the same documents, means for determining whether the particular search result document and the selected search result document have a same format, or means for determining whether the particular search result document and the selected search result document have a same layout; means for boosting, based on identifying whether the particular search result document is similar to the selected search result document, a score for the particular search result document to obtain a boosted score; and means for providing the list of search result documents, where the means for providing includes means for providing the particular search result document based on the boosted score.

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3. The method of claim 2 , wherein the homography comprises the transformation matrix, and the transformation matrix is a 3×3 projective transformation matrix.

2. The method of claim 1 , the transforming further comprising: determining a transformation matrix to correct the distortion of the region of interest in the image; transforming the pixels in the region of interest to a substantially rectangular region; and recognizing, from the substantially rectangular region, characters of text.

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10. The computer program product of claim 9 wherein the updating a search term comprises a user selecting one of the displayed search results.

9. A computer program product for implementing a floating index navigation tool, the computer program product comprising a non-transitory computer-readable medium having stored therein instructions for causing a computer to: in response to updating a search term using a floating text box, build first and second search queries; issue the first and second search queries to at least one database comprising a searchable index of content; responsive to receipt of search results from the first and second search queries, display the first query search results as a first floating index extending horizontally to the left and to the right of the floating text box and display the second query search results as a second floating index extending vertically above and below the floating text box.

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9. The method of claim 7 , wherein the determined format of both the received source language text phrase and the generated target language narrative includes at least a caption.

7. The method of claim 1 , wherein the determined format of the generated target language narrative is the same as the determined format of the received source language text phrase.

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14. The computer program product of claim 13 , wherein the method further comprises: generating, with a workflow editor tool, the second metadata describing the customized workflow; and storing the second metadata in a metadata store.

13. A computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a computer system to perform a method for analyzing workflows associated with a computer application installed in a client environment, the method comprising: identifying first metadata describing an original workflow, the original workflow providing an original configuration of the computer application, the original configuration providing original functionality; identifying second metadata describing a customized workflow, wherein the customized workflow is a modified version of the original workflow, the customized workflow providing a customized configuration of the computer application, the customized configuration providing customized functionality different from the original functionality; comparing, by a computer processor, the first metadata and the second metadata; and generating, based on the comparing, analysis results representing the customized functionality; identifying third metadata describing an updated original workflow, wherein the updated original workflow is a second modified version of the original workflow, the updated original workflow providing an updated configuration of an updated version of the computer application, the updated configuration providing updated functionality different from the original functionality and different from the customized functionality; further comparing, by the computer processor, the third metadata with the first metadata and the second metadata; generating, based on the further comparing, second analysis results representing customized updated functionality, the customized updated functionality including merging the customized functionality with the updated functionality; and creating a merged workflow based on the second analysis results, the merged workflow and the updated version of the computer application providing the customized updated functionality.

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14. The method of claim 12 such that higher order features comprise contextual and periodic patterns of states and actions of RWEs known to the network.

12. The method of claim 1 such that the combined graph is a feature vector of RWEs known to the network.

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28. An apparatus for capturing human-readable text displayed on a unit dose package, said apparatus comprising: means for capturing identification information associated with a unit dose package; means for determining, based at least in part on the identification information, a location on the unit dose package at which human-readable text is displayed; and means for electronically capturing the human-readable text at the determined location, wherein the means for determining, based at least in part on the identification information, a location on the unit dose package at which the human-readable text is displayed comprises means for accessing a mapping of the identification information associated with one or more unit dose packages to information describing the location on the corresponding unit dose package at which the human-readable text is displayed.

31. The apparatus of claim 28 , wherein the means for electronically capturing the human-readable text further comprises: means for translating the human-readable text into machine-readable text using optical character recognition.

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10. A computer program product, comprising computer readable program code instructions, embedded in a non-transitory computer storage medium, that when executed implement a method for processing a communication sequentially transmitted across a chain of links, each link in the chain of links comprising at least one characteristic selected from the group consisting of an identifier of said each link, identifier of a sender of the communication at said each link, and a date on which the communication was sent from said each link, and combinations thereof, said method being implemented by execution of program code instructions on a data processing system at a second link in the chain for the communication directly received at the second link from a first link in the chain, said communication comprising an electronic document with an attached file, said method comprising: selecting the file from the communication; determining an existing filename of the selected file, said existing filename comprising a generic filename component denoted as Filename.ext that does not relate to the at least one characteristic of any link in the chain; identifying from an encoding rule at least one field in the document; selecting referential data from the at least one field in accordance with the encoding rule, said referential data including a subset of the at least one characteristic of the first link; generating a new filename for the selected file by encoding the selected referential data and merging the encoded referential data with Filename.ext in accordance with the encoding rule and in accordance with at least one lexicographic rule of a file manager of the data processing system; renaming the selected file with the new filename, said new filename comprising Filename.ext; detaching the selected file from the document; storing the detached file on a first storage of the data processing system, said stored file on the first storage having the new filename; parsing the new filename in accordance with the encoding rule and in accordance with the at least one lexicographic rule to generate a parsed filename from the new filename; decoding the referential data from the parsed filename; and displaying the decoded referential.

18. The computer program product of claim 10 , wherein each link in the chain is independently selected from the group consisting of an e-mail link, a database link, and a website link.

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17. A method for recording text subtitle stream, the method comprising: recording, by a device, at least one text subtitle stream, the text subtitle stream including a style segment and one or more presentation segments, the style segment defining at least one region style and the presentation segment containing at least one region of text linked to one of the at least one region style defined in the style segment by an identifier, wherein the presentation segment contains a continuous presentation flag to indicate that whether continuous presentation is required or not between a current presentation segment and a previous presentation segment, and a presentation time information indicating a start time of the presentation segment and an end time of the presentation segment, wherein the at least one region of text included in one presentation segment is linked to the at least one region style specifying a same text flow, wherein if the continuous presentation flag indicates that the continuation presentation is required between the current presentation segment and the previous presentation segment, presentation of the at least one region of text in the previous presentation segment is preserved for presentation of the current presentation segment, wherein the at least one region of text including text data in which one of the at least one region style applied.

19. The method of claim 17 , wherein the continuous presentation flag is set to “1” to indicate that continuous presentation is required for the presentation segment with previous one.

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20. The non-transitory computer readable storage medium of claim 16 , wherein providing a news feed further comprises: generating a plurality of advertisements based on at least one determined affinity of the viewing user based on an aspect of the news stories; determining the story layout for the selected top news stories and at least one of the plurality of advertisements, the story layout comprising a placement of each of the selected top news stories and the at least one of the plurality of advertisements in the one or more of the plurality of columns, where the placement is based at least in part on the viewing user's affinity for the top stories and the at least one of the plurality of advertisements; and providing the at least one of the plurality of advertisements in the news feed for display to the viewing user, where the news feed comprises the selected top news stories and the at least one of the plurality of advertisements displayed according to the determined story layout.

16. A non-transitory computer readable storage medium storing one or more programs configured to be executed by a server system, the one or more programs comprising instructions for: obtaining a plurality of news stories that describe a plurality of activities performed by a plurality of other entities with whom a viewing user has established a connection in a social networking system; ranking the plurality of news stories based on a determined affinity of the viewing user for an aspect of each of the news stories; selecting a set of top news stories from the plurality of news stories based on the ranking; and determining a story layout for the selected top news stories, the story layout comprising a placement of each of the selected top news stories in one or more of a plurality of columns, the placements based at least in part on the viewing user's affinity for the top stories; providing a news feed for display to the viewing user, where the news feed comprises the selected top news stories displayed according to the determined story layout, by generating an aggregated story based on a plurality of news stories having a common topic, where the aggregated story comprises a selectable link for expanding the aggregated story for displaying the plurality of news stories having the common topic, determining the story layout for the selected top news stories and the aggregated story, the story layout comprising a placement of each of the selected top news stories and the aggregated story in the one or more of the plurality of columns, where the placement is based at least in part on the viewing user's affinity for the top stories and the common topic, and providing the aggregated story in the news feed for display to the viewing user, where the news feed comprises the selected top news stories and the aggregated story displayed according to the determined story layout.

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8. The system of claim 7 , wherein the instructions when executed further cause the system to: enable the customer to request generation of the second security policy, the second security policy enabling different levels of access to the one or more resource.

7. A system for generating multiple representations of a security policy, comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to: obtain a first security policy associated with a customer of a distributed environment, the first security policy including access parameters for determining whether to allow access to one or more resources of the distributed environment to which the customer has access; determine whether a first representation of a policy language of the first security policy is supported by each policy evaluation engine, of the distributed environment, that is associated with the one or more resources; translate content of the security policy to a second representation of the policy language when the first representation of the policy language of the security policy is only supported by a portion of the at least one policy evaluation engines, the different representation being supported by at least one of the at least one policy evaluation engine and being used to generate a second security policy; and provide at least a portion of at least one of the first security policy or the second policy to each policy evaluation engine associated with the one or more resources.

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10. A computing device configured to prevent fraudulent activity associated with typo-squatting procedures, comprising: a processor; memory in electronic communication with the processor; instructions stored in the memory, the instructions being executable by the processor to: detect an input of a uniform resource locator (URL) for an un-assessed website at a browser on the computing device; collect information relating to a predetermined number of prior websites accessed at and displayed on the browser of the computing device prior to the URL of the un-assessed website being input at the browser on the computing device; detect a data field on the un-assessed website for sensitive information; compare the inputted URL to a database of URLs for trusted websites associated with trusted entities; determine whether a difference between the inputted URL and the URLs in the database satisfies a threshold; compare the information relating to the predetermined number of prior websites to the database of URLs; determine whether the information relating to the predetermined number of prior websites includes a variation of a URL stored in the database of URLs; upon determining that the difference satisfies the threshold, generate a message regarding the un-assessed website; and upon determining that the information relating to the predetermined number of prior websites includes the variation of the URL stored in the database of URLs, include in the message information regarding the predetermined number of prior websites including the variation of the URL stored in the database of URLs.

11. The computing device of claim 10 , wherein the instructions are executable by the processor to: compare the collected information relating to the predetermined number of prior websites to the database of URLs for trusted websites.

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19. A method of speech recognition for use by a speech recognition engine to resolve unrecognized sound groups in a speech, said method comprising the steps of: preparing a plurality of grammar rules storing said plurality of grammar rules on a storage medium, each of said plurality of grammar rules having a context designation assigned thereto and comprising an ordered list of concepts, wherein each of the concepts are expandable to a plurality of words conceptually related to each of the expanded concepts; determining a conversation context of a speech being recognized by a speech recognition engine and recording said conversation context in a context history; if said conversation context corresponds to one of said context designations, assigning a ranking order to said context designation in a search sequence as a function of said context history; and directing said speech recognition engine to search said plurality of grammar rules following said search sequence and utilize grammar rules identified in said search to resolve unrecognized sound groupings in a speech, wherein each of said identified grammar rules are provided to the speech recognition engine with the concepts in the ordered list of concepts expanded to the plurality of words for use by the speech recognition engine to resolve the unrecognized sound groupings in the speech corresponding to the expanded concepts in the ordered list.

20. The method according to claim 19 , wherein said ranking order correlates to how recent said conversation context appears in said context history.

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8. A system comprising: a processor; and a computer-readable storage device having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving a voice message intended for delivery to a device associated with a recipient, the voice message being in a first language; receiving, from the recipient, an access number specific to a second language; translating the voice message into the second language, to yield a translated voice message; and transmitting the translated voice message to the device associated with the recipient.

12. The system of claim 8 , the computer-readable storage device having additional instructions stored which result in the operations further comprising selecting a type of speech pattern to be used in translating the voice message based on a preference designated by the recipient in advance.

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1. A computer program product comprising one or more computer-readable hardware storage device having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, causes the computing system to instantiate and operate a language service provider framework that comprises: an application context generation component configured to generate an application context of a dynamic language program being authored, the application context including one or more specific locations in the dynamic language program, a description of the dynamic language program, and runtime environment information corresponding to operation of the dynamic language program; a language service provider port component configured to hold one or more language service providers; and a management component configured to 1) receive the application context from the application context generation component, 2) provide the application context to a language service provider held by the language service provider port component, and 3) receive a set of available symbols corresponding to each of at least one of the one or more specific locations from the language service provider.

2. The computer program product in accordance with claim 1 , wherein when the language service provider port component holds a plurality of language service providers, the management component is further configured to select one of the plurality of language service providers to provide the set of available symbols.

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7. The search device according to claim 1 , wherein the second acquisition unit acquires the second recommended keywords in a case the number of first recommended keywords acquired by the first acquisition unit is equal to or below a predetermined value set in advance.

1. A search device comprising: a first storage configured to store therein keyword candidates for a search keyword in advance; an input unit configured to receive an input operation of a character string by a user; a first acquisition unit configured to acquire first recommended keywords each of which is a keyword candidate including an input character string, the input character string being a character string which is partially entered by the user as the search keyword; and a search unit configured to select one of the acquired first recommended keywords selected on a search screen as the search keyword to perform a search with the search keyword; an output unit configured to output a search result on the search screen, wherein the search device further comprises, a second storage configured to store therein keyword candidates in association with keyword groups, the keyword groups grouping the keyword candidates for a search keyword stored in the first storage according to a rule set in advance; a second acquisition unit configured to acquire second recommended keywords each of which is a keyword candidate included in a keyword group to which an acquired first recommended keyword belongs and which is the keyword candidate other than the acquired first recommended keyword, wherein when the first acquisition unit acquires a plurality of first recommended keywords each of which includes the input character string, the second acquisition unit selects, among keyword groups to which at least one of the acquired first recommended keywords belongs, a predetermined number of the keyword groups in a descending order of the number of the acquired first recommended keywords belonging thereto, and acquires, as the second recommended keywords, the keyword candidates included in the selected keyword groups, and the search unit configured to sequentially select one of the acquired first recommended keywords and the acquired second recommended keywords on the search screen to perform a search with the sequentially selected one while the input character string is not repeatedly inputted.

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13. The spine stabilization device of claim 10 , wherein the second element is a threaded mount adapted to connect to a spinal implant component.

10. A spine stabilization device comprising: a first element; a second element; and a self-centering joint connecting the first element and the second element; wherein the self-centering joint comprises: a housing having a socket; a rod with a retainer, with the retainer received in the socket; and a centering rod received at least partially within the rod and at least partially within the housing; whereby deflection of the rod bends the centering rod and the centering rod exerts a restoring force on the rod.

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1. A method for enabling search of visual media data items from a collection, the method being implemented by one or more processors that perform steps comprising: enabling search operations on select data items that include content other than speech and text, but which have one or more associated files or data that includes speech, by programmatically converting the speech in said associated files or data into text for use with search operations that specify text; wherein enabling the search operations includes: identifying the one or more associated files or data, each of the one or more associated files or data pertaining to a respective data item from the collection; generating a respective text file for each of the one or more associated files or data; for each of the one or more associated files or data, associating the respective text file with the respective data item; and in response to receiving a textual selection criteria, comparing the selection criteria against text contained in the one or more text files.

10. The method of claim 1 , further comprising storing the collection of visual media data items.

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13. The mobile system according to claim 1 , wherein the communicatively coupled services include at least one remotely located service and the selected domain agent includes data for controlling or communicating with the remotely located service.

15. The mobile system according to claim 13 , wherein the speech unit and the natural language speech processing system each include respective transceivers that communicate via a communication network.

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11. The apparatus according to claim 8 , wherein the parameter of each weak classifier determined by the determining module comprises a location and a size of a rectangular frame of the weak classifier, and the processing module comprises: an average grayscale value determining unit, configured to divide an area, the area having a same size as the rectangular frame of the weak classifier and the area using a location of the rectangular frame of the weak classifier as a center, into at least two subareas, and to calculate an average grayscale value of each of the at least two subareas; a setting unit, configured to select a reference area from the at least two subareas, and to set, for each of the at least two subareas except the reference area, a sign bit that includes one of a first sign bit or a second sign bit; and a sketch value determining unit, configured to obtain a sketch value of the weak classifier according to the average grayscale values of the at least two subareas except the reference area, the sign bits of the at least two subareas except the reference area, and the preset threshold of the weak classifier.

8. An apparatus for generating a strong classifier for face detection, the apparatus having a processor comprising: a determining module, configured to determine, according to a size of a prestored image training sample, a parameter of each of one or more weak classifiers of the image training sample; a processing module, configured to obtain, according to a preset threshold of each of the one or more weak classifiers and the parameter of each weak classifier, a sketch value of each of the one or more weak classifiers of the image training sample; a selecting module, configured to calculate, according to the sketch value of each weak classifier obtained by the processing module and an initial weight of the image training sample, a weighted classification error of each of the one or more weak classifiers of the image training sample; and to obtain, according to the weighted classification error of each of tweak classifier, one or more optimal weak classifiers at least one optimal weak classifier according to the weighted classification error; and a generating module, configured to generate a strong classifier for face detection according to the one or more optimal weak classifiers selected by the selecting module.

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2. The computer program product of claim 1 , wherein the computer usable code, if executed, further causes a computer to sort each of the plurality of candidate social communities based on the question-community affinity value to identify the one or more relevant social communities from the plurality of candidate social communities.

1. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the non-transitory computer readable storage medium, where, if executed by a processor, the computer usable code causes a computer to: determine a user-question affinity value between a user and a question based on one or more user metrics and one or more question metrics, wherein the user-question affinity value is to indicate an extent of affinity between the user and the question; determine a user-community affinity value between the user and each of a plurality of candidate social communities based on at least one of the one or more user metrics and one or more community metrics, wherein the user-community affinity value is to indicate an extent of affinity between the user and each of the plurality of candidate social communities, and wherein at least one of the plurality of candidate social communities includes a pre-existing online social community having a candidate member that is to proactively establish a relationship with another candidate member and is to form a group of candidate members that are to interact with each other; and determine a question-community affinity value between the question and each of the plurality of candidate social communities based on the user-question affinity value and the user-community affinity value to identify one or more relevant social communities for the question, wherein the question-community affinity value is to indicate an extent of affinity between the question and each of the plurality of candidate social communities, and wherein the question is to be routed to one or more of the relevant social communities based on the question-community affinity value and is to be available to each member of the group of candidate members to respond to the question when it is determined that the pre-existing online social community is to be one of the one or more relevant social communities.

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28. An associative memory method according to claim 26 : wherein observing comprises: observing into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; and observing into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; and wherein querying comprises imagining associations of entities, users and/or tasks from the network of entity associative memory networks and the network of feedback associative memory networks in response to user queries.

26. An associative memory method comprising: providing a network of networks of associative memory networks, comprising: a network of entity associative memory networks, a respective entity associative memory network comprising associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on a plurality of input documents; and a network of feedback associative memory networks, a respective feedback associative memory network comprising associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; observing associations into the network of networks of associative memory networks; imagining associations from the network of networks of associative memory networks; and displaying information corresponding to at least one of the associations on a result display.

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14. The system of claim 12 wherein the parser rules are represented as pattern expression trees.

12. The system of claim 9 wherein said parser comprises a pattern-matching engine, for matching a pattern within a sequence of tokens in accordance with the parser rules accessed by said rules accessor.

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1. A method of controlling a function of a wearable electronic device, comprising: detecting a predetermined gesture by a motion sensor of the wearable electronic device, for activating a voice recognition function of the wearable electronic device, wherein the wearable electronic device is worn on a wrist of a user; driving a timer for calculating a time period from an instance when the predetermined gesture is detected; recognizing eyeballs of the user through one or more cameras of the wearable electronic device; activating a touch screen and the voice recognition function when the time period calculated by the driven timer exceeds a predetermined time period and the eyeballs of the user are recognized; displaying, on the touch screen, a screen of the activated voice recognition function for receiving a voice input to control the voice recognition function of the wearable device; receiving the voice input through the activated voice recognition function; determining whether one or more functions executable by the received voice input include a user's personal information of the wearable electronic device; if the one or more functions executable based on the voice input do not include the user's personal information, analyzing the voice input by using the activated voice recognition function, and executing a function that does not include the user's personal information, based on the voice input; and if the one or more functions executable based on the voice input include the user's personal information of the wearable electronic device, outputting, through the activated touch screen, a message indicating that the one or more functions including the user's personal information are not executable, wherein the output message includes a function list of one or more functions that are executable by at least one voice input different from the received voice input and do not include the user's personal information.

7. The method of claim 1 , further comprising outputting the function list with a voice.

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13. A method for controlling a speech recognition function for a data processing system, the data processing system having a display, a speech recognition input device, and a cursor control device, the cursor control device having a selector, the method comprising the steps of: (a) displaying at least one object and a moveable cursor on the display; (b) controlling the moveable cursor on the display in x and y directions simultaneously in response to user-manipulation of the cursor control device; (c) selecting one of the at least one object displayed on the display; (d) activating the speech recognition function in response to engagement of the selector of the cursor control device; (e) inputting a spoken command for the data processing system by the speech recognition input device; (f) applying the spoken command inputted for the data processing system to only the selected one object; and (g) deactivating the speech recognition function in response to disengagement of the selector of the cursor control device.

16. The method of claim 13, wherein the selector includes a voice button and the activating step (d) includes the step of activating the speech recognition function in response to depression of the voice button.

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8. The system of claim 6 , wherein the area of interest comprises a predicted weather track.

6. The system of claim 5 , wherein the map display further includes an area of interest.

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7. The method of claim 1 , wherein displaying the calculation result comprises displaying a pop-up window containing the calculation result close to the arithmetic expression.

8. The method of claim 7 , wherein displaying the calculation result further comprises replacing, when the pop-up window is touched, the arithmetic expression with the calculation result.

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24. The system of claim 22 , wherein the at least one communication network comprises at least one internet-based network.

22. A system for evaluating compliance of at least one agent reading at least one script to at least one client, the system comprising at least the following: at least one communication network adapted to support at least one voice interaction between the at least one agent and the at least one client, wherein the at least one agent follows at least one script at an agent workstation; at least one automatic speech recognition component adapted to analyze the at least one voice interaction and to determine whether the at least one agent has adequately followed the at least one script, wherein the at least one voice interaction is divided into viewable panel-level segments and a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding expected text, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding expected text, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding expected text, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding expected texts; and at least one set of action rules applied to the output of the determination by the at least one automatic speech recognition component as to whether the at least one agent has adequately followed the at least one script, the at least one set of action rules including a quality assurance action determination.

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1. A method, implemented at least in part by a computing device, for identifying topics in source code using Latent Dirichlet Allocation (LDA), the method comprising: receiving software source code; identifying domain specific keywords from the software source code; generating a keyword matrix, wherein the keyword matrix comprises weighted sums of occurrences of the domain specific keywords in the software source code; processing, using LDA, the keyword matrix and the software source code; and outputting, from the processing, collections of domain specific keywords and probabilities, wherein the collections corresponds to respective topics identified by LDA in the software source code.

10. The method of claim 1 wherein the collections of domain specific keywords and probabilities are output in the form of a topic-keyword matrix whose entries correspond to probabilistic associations between the topics and the domain specific keywords.

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19. The system of claim 13 , wherein the subset of documents is selected based on a predetermined threshold similarity score.

13. A computer-implemented system for searching for documents, comprising: a memory storing an index containing a plurality of topics and references to documents, each entry in the index storing a topic of the plurality of topics with a reference to each of the documents containing the topic; and a processor programmed to: enable a user to select a source document; receive information for the source document, the information including at least one topic and a weight for each topic, where the topic relates to content of the source document, and the weight represents how strongly the topic is associated with the source document; access the index; select a set of documents in the index by comparing the at least one topic of the source document to the entries of the index to obtain each reference in the index that is stored with one or more entries in the index matching the at least one topic of the source document, each of the set of documents having a respective document signature formed of at least one topic relating to content of the document and a weight for each topic; generate similarity scores based on the weight of a topic in the source document and a weight of the same topic in each document within the set of documents having that topic as indicated by the document signature; select a subset of documents from the set of documents based on the similarity scores; and output an identity of the subset of documents for display to the user.

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12. A computer-implemented method comprising: identifying a textual indicator of secondary content in a string of text, the string of text including a first string prior to the textual indicator and a second string subsequent to the textual indicator, wherein the secondary content is at least one of data relating to formatting of the string of text or additional data associated with the string of text; and outputting first audio including an audio tone corresponding to the textual indicator that is preceded by first speech corresponding to the first string and followed by second speech corresponding to the second string, the audio tone based on a type of the secondary content.

13. The computer-implemented method of claim 12 , further comprising: inserting the textual indicator in the string of text based on a location of the secondary content within the string of text.

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18. The system of claim 16 , wherein the computer program further performs operations to analyze the plurality of features for one or more indications of phishing behavior, and wherein the analyzing of the plurality of features further comprises: applying a phishing policy to the plurality of features, wherein applying the phishing policy results in an indicator that the website information is associated with a phishing website, and wherein the phishing policy includes applying one or more phishing models to the plurality of features.

16. A system comprising: one or more processors; and a computer product coupled to the one or more processors, the computer product comprising code, executable by the one or more processors, to provide a computer program configured to identify phishing websites, the computer program performing operations to: receive website information from a server computer corresponding to a website; render a document object model (DOM) object of the website using the website information; extract a plurality of features from the DOM object; identify a subset of features in the plurality of features; apply a phishing model to the subset of features to determine an indication of whether the website is performing phishing, wherein the phishing model includes a hierarchical decision logic defined by a plurality of nodes, each of the plurality of nodes having a different one of a plurality of phishing rules, wherein each of the plurality of phishing rules is a conditional statement for assessing one or more of the subset of features, and wherein applying the phishing model to the subset of features includes: identifying a subset of nodes in the plurality of nodes, the subset of nodes defining a decision path in the hierarchical decision logic, wherein the subset of nodes are identified by traversing the hierarchical decision logic based on an outcome of assessing a phishing rule of each of the subset of nodes, wherein the subset of nodes includes an initial node and a final node, and wherein after the initial node is identified, each subsequent node of the subset of nodes is identified based on the outcome of assessing a phishing rule of a node that is a parent of the subsequent node in the decision path; and determining a final phishing rule of the final node of the subset of nodes of the decision path, the final phishing rule being one of the plurality of phishing rules, wherein the indication of whether the website is performing phishing is determined based on an outcome of assessing the final phishing rule; determine a classification about whether the website is performing phishing based on the indication determined by the applying of the phishing model to the subset of features; and report a phishing occurrence based on determining that the classification specifies the website is performing phishing.

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5. The method of claim 2 , further comprising, for each of the p times the second loop code is executed: applying at least one profile of a set of profiles to each document of the UNVDS, the at least one profile defining rule to be applied to each document of the UNVDS; comparing at least one document of the UNVDS to all of the documents included in the first set of documents; and deleting the at least one document from the UNVDS based on the comparison.

10. The method of claim 5 , further comprising, for each of the p times the second loop code is executed: forming a third set of documents by merging documents included in the first set of documents with documents not deleted from the UNVDS ; and clustering the third set of documents using the flat clustering or the hierarchical clustering technique.

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1. A system comprising: one or more processors; memory; a map segmentation module maintained in the memory and executable by the one or more processors to segment a map of an area into a set of sections; a function distribution module maintained in the memory and executable by the one or more processors to infer a distribution of functions for each section in the set of sections according to a topic model framework which uses mobility patterns of users leaving from and arriving at each section and uses points of interest (POIs) in each section; a section aggregation module maintained in the memory and executable by the one or more processors to group sections of the set of sections based at least in part on a similarity of the distribution of functions between each section to create functional groups; a functionality intensity estimator maintained in the memory and executable by the one or more processors to estimate a functionality intensity for each of the functional groups; and a group annotation module maintained in the memory and executable by the one or more processors to annotate each of the functional groups on a visual representation of the area.

2. The system of claim 1 , wherein the topic model framework is a Dirichlet Multinomial Regression (DMR)-based topic model.

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1. A speech recognition method, comprising: receiving a speech input signal in a first noise environment which comprises a sequence of observations; determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, comprising, providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognise speech in a second noise environment, said model having a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation, and adapting the model trained in the second environment to that of the first environment; the speech recognition method further comprising, determining the likelihood of a sequence of observations occurring in a given language using a language model; and combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein adapting the model trained in the second environment to that of the first environment comprises using second order or higher order Taylor expansion coefficients derived for a group of probability distributions and wherein the same expansion coefficient is used for the whole group; the speech recognition method further comprising estimating noise parameters used to determine the Taylor expansion coefficients, wherein the noise parameters comprise a component for additive noise and a component for convolutional noise, and an observation in the first noise environment is related to an observation in the second noise environment by: y=x+h+g ( x, n, h )= x+h+C ln(1+ e C −1 (n−x−h) )  (1) where y is the observation in the first noise environment, x is the observation in the second noise environment, n is the additive noise, h is the convolutional noise in the first environment with respect to the second environment and C is the discrete cosine transformation matrix.

4. A speech recognition method according to claim 1 , wherein the model parameters comprise the static mean and static variance.

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5. The computer system of claim 1 , wherein at least one of the identified additional terms comprises a multi-word phrase contextually related to the search query object.

1. A computer system for returning a list of playable media objects to a user, comprising: a server configured to receive a search query object from the user; a first module configured to: identify additional terms related to the search query object by providing the search query object to at least one internet search engine and processing results returned by the internet search engine, wherein processing includes: receiving a page identified in the result returned by the internet search engine, parsing the received page to extract terms from the page and identify sections in the page, generating relationship vectors based on the extracted terms, scoring sections of the received page based on the generated relationship vectors, and selecting additional terms based at least in part on the scores; and a second module configured to query one or more video storage web sites based on the identified additional terms to obtain a list of playable media objects stored on the one or more video storage web sites, the playable media objects comprising the identified additional terms.

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31. The method of claim 18 , further comprising, for each page in the source document, applying a variable length encoding to the page record; and wherein compressing the page record using a compression technique comprises compressing the optimum filtered and variable length encoded page record using a lossless compression technique.

18. A method for optimizing a source document comprising a plurality of pages of content, the method comprising: obtaining a source document, wherein the source document comprises markup information for a plurality of pages of content; creating an optimized document corresponding to the source document; and for each page in the source document: creating a page record for the page, each page record comprising the reflowable content for that page, wherein the page record comprises references to drawing representations of contours and vertices of textual content in the source document; for each set of values in the page record: selectively filtering the set of values to minimize the storage requirement for the set of values, wherein at least some of the values comprise references to drawing representations of the contours and vertices of textual content in the source document; wherein selectively filtering the set of values to minimize the storage requirement for the set of values comprises: establishing a base value for the set of values and adjusting the values in the set to be offsets from the base value; and from the base value, further adjusting each value in the set as a relative offset of its previous value in the set of values; compressing the page record using a compression technique; and storing the compressed page record in the optimized document.

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5. A method of validating EDI documents comprising: providing an inventory of all rules, the inventory including a common set of rules for the plurality of entities dynamically adjusting said inventory of all rules based upon the entity specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; creating a rules analyzer to analyze the content of companion guides and to build an organizer of companion guide rules where each companion guide is associated with one of the plurality of entities; employing the organizer of companion guide rules to add companion guide rules to the inventory of rules; creating a profiles engine to create a current rule set for each of said plurality of entities; creating a companion guide profile for each of the plurality of entities where each companion guide profile indicates that entity's companion guide rules and provides pointers to the rules in the inventory of rules that are associated with the current rule set of that entity, and creating a runtime checker engine to validate EDI documents by comparing each EDI document to the current rule set associated with a corresponding one of the plurality of entities, by forwarding the EDI document to the corresponding one of the plurality of entities if the EDI document matches its current rule set, wherein the EDI document is validated and by returning the EDI document to the sender if the EDI document does not match the current rule set, wherein the EDI document is invalidated.

18. The method of claim 5 wherein validating the EDI Document further comprises checking an entity identification code with the runtime checker engine to determine whether the document matches the entity's rule set.

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14. A computer readable storage medium comprising instructions that cause a computing device to: provide a metadata model including model objects representing the data source, the metadata model having a query layer and a package layer, the query layer providing a business view of the data in the data source, the query layer including query subjects, wherein the query subjects directly describe actual physical data within an underlying database, are used in creating reports, and are abstracted and separate from the underlying database that includes physical data from one or more data sources, and wherein the package layer includes packages having direct references to the query subjects; generate a query specification based on a user input using the client application, the query specification is not in a form applicable to the data source directly; translate the generated query specification by the computer into a query applicable to the data source based on the query subjects referred to by the packages in the package layer in the metadata model, wherein the query is executed using a data source specification language of the data source, and wherein the query includes data query language statements that are embedded within the query subjects in the metadata model; and provide the query to the data source for execution.

18. The computer readable storage medium of claim 14 , wherein the query layer includes query items that are attributes of the physical data.

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3. The method of claim 1 , wherein said context information also includes supplemental information that is obtained from a source other than the content that is presented to the user.

1. A method, performed using at least one computing device, for identifying a set of resources associated with respective domains, comprising: providing context information that pertains to interaction, by a user, with a user device, the context information including textual information associated with content presented to the user by the user device; providing, for each of a plurality of individual domains, individual-domain score information that indicates relevance of the context information to a corresponding individual domain, plural instances of the individual-domain score information comprising plural-domain score information, the providing including (i) receiving data from an entity associated with corresponding individual domain, the data characterizing at least goods or services of the entity, and (ii) generating a language model that identities characteristics of the entity, based on the received data; and identifying a set of resources based on the plural-domain score information for presentation to the user, the set of resources assisting the user in performing an action within a task having plural parts.

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40. The device of claim 29 where the audio output device receives the speech audio signal and outputs the speech audio signal such that the text-based content is presented as spoken audio.

43. The device of claim 40 where the speech audio signal is automatically output at the audio output device in response to receipt of the encoded content at the device.

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7. The computer-readable storage device of claim 1 wherein each element may have from 0-n bindings.

1. A computer-readable storage device having computer-executable components executable by a processing device to perform a method, the processing device accessing a local memory, comprising: (a) receiving a web-page including elements defined to access a plurality of resources in a JavaScript framework provided to the processing device in local memory, the resources including methods interpreted by a browser to create resource objects; (b) parsing the web-page to define instances of objects based on bindings to the resources defined by elements in the web-page; (c) downloading a base set of resources in a core framework library of the JavaScript framework to the local memory; (d) determining if additional resources not included in the local memory are needed based on the bindings declared in the web-page and if so, downloading the additional resources to a resource cache in local memory; (e) managing instances of the objects by maintaining a global list of binding declarations maintained by the JavaScript framework; and (f) displaying the web-page in the browser using one or more of the objects.

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3. The method of claim 1 , where the topical score is higher for a more relevant one of the documents than a less relevant one of the documents, and the distance score is higher for one of the documents with the geographic location nearer to the geographic location associated with the query than another one of the documents with the geographic location further from the geographic location associated with the query.

4. The method of claim 3 , where the function is a monotonic function of the topical scores and a monotonic function of the distance scores.

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2. The method of claim 1 , wherein storing the frequently updated portions of the documents comprises: extracting the frequently updated portions from the updated version of the document; and storing the frequently updated portions in the second structure and not in the first structure; wherein no other portion of the updated document is stored; and wherein a controller for accessing the storage device cannot write to or read from the storage device only a portion of the first structure or the second structure.

1. A method of storing data, the method comprising: storing a first version of a document in a first structure on a storage device; receiving an updated version of the document; identifying one or more frequently updated portions of the document; storing on the storage device the one or more frequently updated portions of the document, in a second structure separate from the first structure; receiving a request for the document; retrieving the first version of the document from the first structure and the frequently updated portions of the document from the second structure; merging the updated portions with the first version to obtain a merged version of the document, by writing the updated portions to the first version of the document; and returning the merged version of the document in response to the request.

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11. A method of selecting content items based on prior interactions with information resources, comprising: identifying, by a data processing system having one or more processors, a first plurality of content items based on a first match between a query and a keyword associated with the first plurality of content items, the query received subsequent to a client device performing a pre-specified interaction; identifying, by the data processing system, a second plurality of content items based on the first match and on a second match between an account identifier associated with the client device and a retargeting identifier of a retargeting set, the retargeting identifier included into the retargeting set responsive to the client device performing the pre-specified interaction; selecting, by the data processing system, from the first plurality of content items and the second plurality of content items, a content item based on selection criteria associated with each of the first plurality of content items and with each of the second plurality of content items, the second plurality of content items including the content item; and providing, by the data processing system, to the client device, the content item to present on an information resource.

16. The method of claim 11 , comprising: inserting, by the data processing system, the retargeting identifier into the retargeting set, responsive to receiving an interaction data indicating that the pre-specified interaction with a code segment executing at the client device occurred, the client device associated with the retargeting identifier.

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20. A method as described in claim 16 , wherein the descriptions of the one or more application programming interfaces are further used to construct valid executable code by exposing a user interface.

16. A method implemented by one or more computing devices, the method comprising: parsing a first collection of statically-typed machine-executable code of a web browser application to locate one or more application programming interface (API) descriptions; projecting the descriptions of the one or more application programming interfaces from the first collection of statically-typed machine-executable code of the web browser into an alternate form consumable by a dynamically-typed language; and checking compatibility of the first collection of statically-typed machine-executable code of the web browser with a second collection of dynamically-typed machine-executable code by verifying that one or more call sites of the second collection of dynamically-typed machine-executable code are mapped to at least one said application programming interface (API) referenced in the projected description from the first collection of statically-typed machine-executable code of the web browser.

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1. A method of generating a barcode with a human readable interpretation where the barcode uses an application identifier, comprising the steps of: inputting characters as an input data set that is equivalent to the complete human readable interpretation with a first special character immediately before the application identifier, a second special character immediately after the application identifier, wherein each and every individual character in the input data set has a one to one correspondence with an individual symbol in the human readable interpretation, wherein the input data set comprises a series of unique data sets each comprising a unique application identifier and a unique data portion a third special character is inserted between each of the series of unique data sets; generating a barcode encoding data set for encoding the barcode based on the input data set, includes interpreting the second special character as a field separator between the application identifier and a data portion following the application identifier, and interpreting the third special character as a separator between data sets; generating a data set for the human readable interpretation based on the input data set includes converting the second special character to a second symbol and converting the third special character to a “_” (space), wherein the second special character as inputted is a graphical equivalent to the second symbol; and generating the barcode with the human readable interpretation includes combining the barcode encoding data set and the data set for the human readable interpretation.

13. The method of claim 1 , wherein: the application identifier includes non-numeric data; generating the barcode encoding data set ignores the non-numeric data in the application identifier; and generating the data set for the human readable interpretation does not ignore the non-numeric data in the application identifier.

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13. A non-transitory computer readable storage medium having a program embodied thereon, the program executable by a processor to perform a method for automatically generating blog content, the method comprising: receiving information indicating that an in-game event has been detected based on gameplay of a user; generating partial blog content corresponding to the detected in-game event, wherein the partial blog content is generated from one or more predefined components associated with the detected in-game event; receiving one or more edits to the partial blog content, wherein the received edits are based on user input; and transmitting the generated and edited blog content over the communication network to a designated website, wherein the generated blog content is automatically published on the designated website.

17. The non-transitory computer readable storage medium of claim 13 , wherein the received one or more edits based on user input include new user generated text to be associated with the partial blog content.

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17. The program product of claim 10 , wherein said method further comprises: constructing and storing a user group interest analytic model (UGIAM) by including UIAM items associated with multiple users who utilize said BI application and belong to a user group, said UIAM items based on initial visits of said multiple users to said BI application, wherein said multiple users includes said user, and wherein said UIAM items include said first set of one or more UIAM items; updating said UGIAM based on updates of said UIAM items associated with said multiple users belonging to said user group, said updates of said UIAM items based on subsequent visits of said multiple users to said BI application, wherein said updating said UGIAM includes adjusting scores of said UIAM items associated with said multiple users belonging to said user group; and automatically generating reports based on top K scores of said adjusted scores of said UIAM items associated with said multiple users belonging to said user group, wherein K is a positive integer.

18. The program product of claim 17 , wherein said method further comprises: determining matching levels of said UIAM items, each matching level indicating whether said an interest represented by a corresponding UIAM item of said UIAM items is common among interests of said multiple users belonging to said user group according to predefined criteria; and distributing said generated reports to one or more users of said multiple users, said distributing based on said matching levels.

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32. The computer program product of claim 31 , wherein the attributes are utilized in combination with: (i) at least one of the attribute types, (ii) at least one sub-type of the at least one attribute type, (iii) a content of at least one field in the at least one document; (iv) a type of at least one field in the at least one document; and (v) information derived from the at least one field in the at least one document.

31. The computer program product of claim 27 , further comprising instructions, provided on the at least one computer readable medium, for utilizing the attributes as criteria for at least one of searching, retrieving, reporting, and viewing the at least one document.

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2. The computer program product of claim 1 , further comprising instructions operable to assign an output tag to an output method generating a response to the request, wherein the output tag triggers the comparison of the input tags with any of the sanitization tags.

1. A computer program product comprising a program stored on a non-transitory computer-readable medium containing an executable set of instructions for detecting a vulnerability in a software application in a database system, the set of instructions operable to: store defined vulnerabilities that identify operations in the software application vulnerable to the security risk and are each associated with one or more input tags and one or more sanitization tags; receive by the software application in the database system a request from a user system; at runtime of the application, assign one or more of the input tags to one or more objects associated with the request, wherein the input tags identify the request as potentially malicious and carrying a security risk; at runtime of the application, assign one or more of the sanitization tags to the one or more objects associated with the request to indicate security checks performed on the objects; at runtime of the application, compare the input tags assigned to the objects with any of the sanitization tags assigned to the objects; and at runtime of the application, identify at least one of the defined vulnerabilities as a vulnerability in a part of the software application when the assigned input tag for an identified one of the objects matches the input tag associated with an identified one of the defined vulnerabilities, and one or more of the sanitization tags associated with the identified one of the defined vulnerabilities is not an assigned sanitization tag for the identified one of the objects; and generating a report identifying the vulnerability in a part of the software application.

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19. The computer-implemented method of claim 1 , further comprising passing the one or more viewing instances with assigned layer indices and the one or more viewing instances relationships to a visualizer for generating a visualization of the one or more viewing instances and/or the one or more viewing instances relationships.

1. A computer-implemented method, comprising: receiving one or more viewing concepts of a software system; identifying one or more viewing instances comprising one or more concept instances or descendants of the one or more concept instances, the one or more concept instances or descendants of the one or more concept instances associated with at least one of the one or more viewing concepts or one or more sub-concepts of the one or more viewing concepts; and assigning layer indices to the one or more viewing instances based on one or more associated viewing instances relationships for use in generating a visualization of the one or more viewing instances and/or the one or more viewing instances relationships, the visualization generated for rendering on an output device in communication with a computer, wherein at least one of the one or more viewing instances relationships are inbound uses relationships; wherein the assigning layer indices to the one or more viewing instances comprises: a) initializing a current layer index value; b) selecting at least one unindexed viewing instance having no inbound uses relationships associated with at least one other unindexed viewing instance, wherein the selecting the at least one unindexed viewing instance comprises removing a cycle condition if respective of unindexed viewing instances have at least one inbound uses relationship associated with at least one other unindexed viewing instance; and c) assigning the current layer index value to the selected at least one unindexed viewing instance; wherein the removing the cycle condition comprises iteratively selecting at least one viewing instances uses relationship associated with at least one unindexed viewing instance until at least one unindexed viewing instance has no inbound uses associated with at least one other unindexed viewing instance based on viewing instances uses relationships associated with unindexed viewing instances minus the at least one selected viewing instances uses relationship or until viewing uses instances relationships with unindexed viewing instances have been selected at least once.

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14. The system of claim 13 , wherein: the determination of the measure of proximity to said common object is based on a determination that the first node is close to the second node said in the DOM, based on a predefined threshold value of physical closeness, based on the count, wherein the subset of said text is determined as a positive example, if the subset of said text is determined to be close to the common object.

13. The system of claim 9 , wherein: the determination of the measure of proximity to said common object is based on a determination of a predefined measure of proximity of the subset of said text to the common object, based on a count of a number of nodes in a document object model (DOM), in a path from a first node of the DOM that represents the subset of said text, to a second node of the DOM that represents the common object.

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3. The method as recited in claim 2 , wherein the finite state transducers include at least one language model (L) and at least one translation model (M).

4. The method as recited in claim 3 , further comprising computing the at least one translation model (M) offline, wherein the at least one translation model includes a word-to-phrase sequencer (P), a phrase translation transducer (T), a target language phrase-to-word transducer (W).

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9. The method of claim 1 , wherein inserting document content into the two-dimensional regions further comprises: determining whether the document content is an inline figure; and if the document content is an inline figure, further comprising placing the inline figure at a specified position in the content region of the element, wherein the specified position is determined by the placement of previous content in the element.

10. The method of claim 9 , further comprising scaling the inline figure to fill the width of a column within the content region of the element.

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6. The system of claim 1 , wherein the MT training module uses a training algorithm to tune a plurality of weights of an ASR language model that is used to model the ASR errors.

7. The system of claim 6 , wherein the training algorithm comprises a minimum error rate training (MERT) algorithm.

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12. The method of claim 11 , wherein the brand-store affinity matrix comprises the one or more values, for one or more instances of the brand, calculated based on normalized scores of one or more instances of the store.

11. The method of claim 1 , wherein the attribute affinity matrix corresponds to a brand-store affinity matrix, and wherein the base attribute is store.

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13. The system of claim 1 , wherein the object from the one or more objects is a first object, a second object from the one or more objects being associated with an image header having an indication that the second object is an object and having coordinate data associated with a position of the second object in relation to the background video.

1. A system for selective video recording, comprising: a video camera that provides output video; a video separator that separates the output video into object video including one or more objects and background video against which the one or more objects appear; a video analysis module that respectively identifies each of the one or more objects as a predetermined type of object by tracking each of the one or more objects over two or more video frames; and a storage control module that independently stores the object video and background video, an object from the one or more objects being associated with an image header having an indication that the object is one of several predetermined types of objects, the image header having coordinate data associated with a position of the object in relation to the background video, the background video being associated with an image header having an indication that the background video is a background video, wherein each of the one or more objects is recorded at a respective frame rate corresponding to the predetermined type of object identified by the video analysis module.

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11. The system according to claim 10 , the one or more program units further comprising: a webpage adjustment confirmation unit configured to determine whether the image display needs to be adjusted; wherein the first determination unit is further configured to determine whether the width for displaying the image is different from a default value, or whether the screen width of the mobile terminal has changed.

13. The system according to claim 11 , wherein the first determination unit is further configured to determine whether at least two brother nodes of the image are nodes representing other contents.

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23. A data processing apparatus according to claim 17, wherein said converting means includes means for producing second information indicating key operations of said push-button telephone which must be operated by the user when inputting an indicating code for indicating that following data is alphanumeric character data by said key operation of said push-button telephone, and for adding said second information to said first information.

17. A data processing apparatus comprising: inputting means for inputting alphanumeric character data representing a message to be transmitted; storing means for storing the alphanumeric character data input by said inputting means; displaying means for displaying said alphanumeric character data stored in said storing means; and means for causing said displaying means to display first information indicating to a user, key operations of a push-button telephone corresponding to said alphanumeric character data stored in said storing means so as to input a message corresponding to said alphanumeric character data by the user performing said indicated key operations of said push-button telephone connected to a public telephone network means; and wherein said causing means includes converting means for converting said alphanumeric character data stored in said storing means into said first information indicating a series of key operations of the push-button telephone, based on a preset data conversion format.

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2. The method of claim 1 , further comprising providing an in-depth article index, the in-depth article index storing data associated with each in-depth article in the plurality of in-depth articles.

1. A computer-implemented method executed by one or more processors, the method comprising: receiving, by the one or more processors, general search results that are responsive to a query; cross-referencing uniform resource locators (URLs) of the general search results with a site pattern of a publishing entity that is identified as publishing in-depth articles; determining, by the one or more processors, that one or more general search results to be provided in response to the query is an in-depth article search result based on the URL of the general search result corresponding to the site pattern of the publishing entity; and in response to determining that one or more in-depth article search results are to be provided in response to the query: obtaining, by the one or more processors, a topicality score for each in-depth article referenced by the one or more in-depth article search results responsive to the query, each topicality score indicating a degree of relevance of a respective in-depth article to the query; obtaining, by the one or more processors, a document score for each in-depth article referenced by the one or more in-depth article search results responsive to the query, each document score being based on a respective topicality score and a respective in-depth article score; selecting, by the one or more processors, one or more in-depth articles referenced by the one or more in-depth article search results responsive to the query based on respective document scores; and providing, by the one or more processors, the one or more in-depth article search results for display, each in-depth article search result representing an in-depth article of the one or more in-depth articles.

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25. The method of claim 24 , where the file identification data include different data sets, at least one data set includes the at least one data entry, and where the natural language is estimated for more than one of the data entries of the file identification data.

24. A method for automatically detecting the language of file identification data of a media file, the file identification data including a plurality of data fields in a header section of the media file allowing identification of the media file, the method comprising: receiving, with a processor, a selection of at least one media file out of a group of media files; retrieving, with the processor, a first data field and a second data field of the data fields in the file identification data; estimating a first language of the first data field of the file identification data of the media file with the processor based on a statistical model; estimating a second language of the second data field of the file identification data of the media file with the processor based on the statistical model; adding, with the processor, the estimated first language and the estimated second language to the file identification data; linking, with the processor, the estimated first language with the first data field and the estimated second language with the second data field; and identifying, by the processor, the media file in response to receipt of a voice control command by comparing the voice control command to phonetic data comprising a first phonetic representation of the first data field in the estimated first language and a second phonetic representation of the second data field in the estimated second language.

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1. A computing system that has access to a hierarchically-structured document having a plurality of elements that may each be associated with one or more namespaces, the computing system comprising: one or more computer-readable storage media having computer-executable instruction for implementing a method for establishing a plurality of abbreviated namespace identifiers for a hierarchically-structured document, wherein the method comprises: an act of associating each of a plurality of associated abbreviated namespace identifiers with a hierarchical namespace; an act of accessing a hierarchically-structured document; an act of determining that at least one group identifier is associated with the hierarchically-structured document, the group identifier representing that when any of the abbreviated namespace identifiers are found associated with an element in the hierarchically-structured document, that the associated namespace is also associated with that element; and at least one of: an act of associating each of the plurality of associated abbreviated namespace identifiers with the hierarchical namespace before the act of accessing the hierarchically-structured document, and an act of reading a pre-processor directive that indicates that the at least one group identifier is associated with the hierarchically-structured document.

19. A computing system in accordance with claim 1 , wherein the computing system comprises a mobile telephone.

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6. The method of claim 1 , wherein the incompatible input comprises unrecognized speech.

1. A method comprising: detecting, by a system including a processor, an input incompatible with an original script for an interactive communication over a communication network, wherein the detecting is performed during the interactive communication; generating, by the system and during the interactive communication, a dynamically updated script different from the original script in accordance with a type of the incompatible input; and providing, by the system and over the communication network, information to a device participating in the interactive communication in accordance with the dynamically updated script, wherein at least a portion of a remainder of the interactive communication is conducted in accordance with the dynamically updated script.

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2. The computer-readable media of claim 1 , wherein the set of most relevant terms is determined based upon use of a Bayesian algorithm.

3. The computer readable medium of claim 2 , storing instructions, which when executed by the machine, cause the machine to perform further operations comprising: creating a first representation of the content from the active desktop window for the query by performing at least the following, eliminating redundant terms in a corpus of terms contained within the content by using a first algorithm to generate a set of most relevant terms; determining one or more weighted values with each term in the set of most relevant terms; and creating a structure for the first representation of the content from the active desktop window to contain the set of most relevant terms from the content and the one or more weighted values associated with each term in the set of most relevant terms.

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15. The apparatus for selecting a language as in claim 14 wherein the means for using the indication as a pointer to a memory address further comprises means for inserting the pointer in a text retrieval routine.

14. The apparatus for selecting a language as in claim 11 wherein the means for programming the agent stations further comprises means for accessing a message display utility which displays messages from the automatic call distributor and using the indication as a pointer to a memory address.

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7. The non-transitory computer-readable medium of claim 5 , wherein the probability is at least partially based on an amount of information returned by each API module associated with the at least one determined keyword.

5. A non-transitory computer-readable medium storing instructions that upon execution cause at least one processor to: determine keywords likely to appear in natural language queries, the determining based on source code text of application programming interface (API) modules executable in response to the natural language queries to obtain data; associate each of the determined keywords with a respective API module of the API modules; alter an association between a determined keyword of the determined keywords and a respective API module of the API modules, in response to determining that the altered association is more likely to trigger an accurate response to a natural language query of the natural language queries; determine whether at least one determined keyword of the determined keywords appears in a received natural language query; respond to the received natural language query with data produced by each API module, of the API modules, that is associated with the at least one determined keyword that appears in the received natural language query; and rank the data returned by each API module associated with the at least one determined keyword based on a probability that the data is a correct response to the received natural language query.

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1. A computer implemented eye detection system for detecting eyes in a digital image, the system comprising: a digital image capture device; and a processor, the processor including: a filter; a first eye candidate selector connected to the filter; a first profile validator connected to the eye candidate selector, the first profile validator including measurements of eye candidate pupil contours; a first eye candidate eliminator connected to the first profile validator and the first eye candidate selector; a second eye candidate selector connected to the first profile validator; a pair validator connected to the second eye candidate selector, the pair validator including a space measurer that determines if the first and second eye candidates are at an appropriate distance from each other; a second profile validator connected to the pair validator; and a second eye candidate eliminator connected to the second profile validator and the second eye candidate selector; wherein the first profile validator comprising a first profiler connected to the first eye candidate selector, and a first profile evaluator connected to the first profiler, the first eye candidate eliminator and the second eye candidate selector; wherein the second profile validator comprises a second profiler connected to the pair validator, and a second profile evaluator connected to the second profiler and the second eye candidate eliminator; wherein the first profiler comprises: a pupil region extractor connected to the first eye candidate selector; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the first profile evaluator; and wherein the second profiler comprises: a pupil region extractor connected to the pair validator; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the second profile evaluator.

2. The system of claim 1 , further comprising: a resulter connected to the first and second profile validators; and a stopper connected to the first and second eye candidate eliminators.

Generate a parent claim based on:

13. The method as in claim 12 , wherein the computer part also includes an editor which allows changing color schemes and music associated with the greeting that was recorded on the telephone.

12. A method, comprising: using a computer part in a telephone to record a first video of a telephone user speaking using a camera in a telephone associated with the telephone user; sending the video and its sound as a first multimedia caller ID sent as part of an outgoing call to another user who is being contacted by the user, in place of a numerical caller ID; using the computer part in the telephone to record a second video of the telephone user speaking using a camera in a telephone associated with the telephone user; sending the second video and its sound as a second multimedia caller ID sent as part of an outgoing text message being sent to another user who is being contacted by a text message by the user.

Generate a child claim based on:

2. The handheld apparatus of claim 1 , wherein the handheld apparatus is further configured to enhance the image captured by lighting the object, automatically adjusting focal length, and using image filters.

3. The handheld apparatus of claim 2 , wherein the handheld apparatus is further configured to enhance the image captured by implementing a feedback loop while lighting the object, automatically adjusting focal length, and using image filters.

Generate a child claim based on:

1. A binary multiplication unit havving a multiplication time substantially higher than the time separating the entering of two successive multiplicand words into the unit, said binary multiplication unit comprising: (a) a multiplicand storage means for successively storing multiplicand words and a multiplier storage means for permanently storing a predetermined multiplier word; (b) means for partitioning each multiplicand word into a plurality of multiplicand subwords following one another in increasing binary weight, each multiplicand subword comprising at least one binary element; (c) means for deriving from each multiplicand subword and the following multiplicand subword a shifted multiplicand subword obtained by omitting the bit of lowest binary weight of the multiplicand subword and adding thereto, as bit of highest binary weight, the bit of lowest binary weight of the following multiplicand subword; (d) means for multiplying said shifted multiplicand subwords by the first bit of said multiplier word and thus obtaining first subproducts; (e) means for respectively multiplying said multiplicand subwords by the successive bits of the multiplier word starting from the second bit of said multiplier word and thus obtaining second, third and following subproducts associated with said multiplicand subwords; (f) means for adding together said first and said second subproducts and thus obtaining subproduct sums following one another in increasing binary weight; (g) means for deriving from each subproduct sum and the following subproduct sum a shifted subproduct sum obtained by omitting the bit of lowest binary weight of the subproduct sum and adding thereto, as bit of highest binary weight, the bit of lowest binary weight of the following subproduct sum; (h) means for respectively adding said third and following subproducts associated with each multiplicand subword respectively to third and following shifted subproduct sums deriving from the subproduct sum associated with the preceeding subproducts of the multiplicand subword and the subproduct sum associated with the preceeding subproducts of the following multiplicand subword; and (i) means for deriving said third and following shifted subproduct sums, each subproduct sum being obtained by omitting the bit of lowest binary weight of the subproduct sum associated to a given miltiplicand subword and adding thereto, as bit of highest binary weight, the bit of lowest binary weight of the subproduct sum associated with the following multiplicand subword.

2. A binary multiplication unit as set forth in claim 1, in which the multiplicand words are n-bit words, the multiplier word is an m-bit word, the n-bit multiplicand words are each partitioned into k subwords of n/k bits, said means for multiplying said shifted multiplicand subwords by the first bit of said multiplier word and thus obtaining first subproducts are k AND gates, said means for adding together said first and second subproducts and thus obtaining subproduct sums are k adders, said means for respectively multiplying said multiplicand subwords by the second to m.sup.th bits of said multiplier word and thus obtaining said second, third and following subproducts are (m- 1) sets of k AND gates and said means for adding together said third and following subproducts and said shifted subproducts sums are (m- 2) sets of k adders.