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13. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: starting an automatic speech recognition session for a phone call initiated from a communication device; determining that the communication device is associated with a plurality of users; identifying a group of selected speech recognition models comprising a speaker independent model and a plurality of speaker dependent models; recognizing an utterance received from a particular user in the plurality of users using each model in the group of selected speech recognition models in parallel, to yield a group of recognition results; selecting a dominant speech model from the group of selected speech recognition models using a heuristic search algorithm, to yield a selected dominant speech model, wherein the dominant speech model is an efficient model in the group of selected speech recognition models; and continuously using the selected dominant speech model to recognize speech received from the particular user for a remainder of the automatic speech recognition session.

15. The computer-readable storage device of claim 13 , having additional instructions stored which, when executed by the computing device, result in operations comprising: selecting the plurality of speaker dependent models based on the plurality of users associated with the communication device.

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9. A computer programming product for managing hierarchically related software components, comprising: a memory; two or more software component descriptors, each descriptor, stored on the memory, containing information about a software component of a plurality of software components; one or more aggregate descriptors, stored on the memory, containing information about the two or more software component descriptors and aggregates of the plurality of software components; and logic, stored on the memory for execution on a processor, for: defining hierarchical interrelationships among the plurality of software components and aggregates of the plurality of software components to produce a component hierarchy; managing lifecycles, access controls, interrelationships, versioning and a list of the plurality of software components to maintain the consistency of the component hierarchy; filtering the plurality of software components based upon the hierarchical interrelationships; integrating a particular software component selected from the filtered software components into a software application; and modifying the hierarchical interrelationships based upon associations generated by the selection of the particular software component.

10. The computer programming product of claim 9 , wherein the filtering if based upon classification information associated with the hierarchical interrelationships.

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10. A learning machine for processing data, said learning machine comprising at least one processing unit, a first processing unit including (a) an encoding means for encoding a vector into a code; (b) a means for evaluating a code deviation vector; (c) a memory means for storing at least one first weighted sum of an entry of a code covariance matrix and a component of a code deviation accumulation vector; (d) a memory means for storing at least one masking factor; (e) a multiplying means for evaluating a product of a second weighted sum of an entry of a code covariance matrix and a component of a code deviation accumulation vector, a masking factor, and a component of a code deviation vector; (f) a summing means for evaluating a sum of products obtained by said multiplying means; (g) an evaluation means for using at least a sum obtained by said summing means to evaluate a representation of an empirical probability distribution of a component of a label of a vector input to said first processing unit.

20. The learning machine of claim 10 , said first processing unit further including a supervised learning means for adjusting at least one entry of a code covariance matrix by a supervised covariance rule.

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6. A method of monitoring an electronic communication, the method comprising the steps of: encoding a non-transitory computer-readable storage medium with a dictionary which references information during analysis of the electronic communications in real time, the dictionary comprising a Hash-table store of expressions wherein the Hash-table store for each expression comprises: at least one section, each section corresponding to one of a plurality of grammatical functions; and at least one subject, each subject corresponding to one of a plurality of categories of expressions; a weighted classification score associated with the expression; and an alert level assigned to an expression or plurality of expressions based on the weighted score; determining an array of expressions of the electronic communication to be matched against the Hash-table store of expressions; loading a plurality of the expressions and their respective alert levels in the Hash- table, based on their respective subjects; sampling the electronic communication with the use of electronic filtering means; storing a array of data representing expressions from at least part of the sampled electronic communication; searching, using data processing means for matches between expressions from the array of data and expressions stored in the hash-table; determining an aggregate alert level with regard to context and intent for the sampled communication based on the sum of the respective alert levels of the expressions stored in the Hash-table that match expressions in the array of data; and automatically transmitting an alert message to a remote terminal via a telecommunications network in response to the aggregated alert level reaching or exceeding a threshold, wherein in response to the alert message, taking a plurality of actions that include: displaying an alert message at the user terminal; terminating the electronic communication; and shutting down the user terminal, and wherein said step of shutting down the user terminal comprises responding to no response to the alert message being received from the remote terminal within a predetermined period of time.

12. The method as claimed in claim 6 , wherein the method further comprises the step of: selecting one or more subjects for monitoring.

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19. The system of claim 18 , further comprising: a receiver module for receiving the text message; and an authentication module for determining whether the text message is authentic, wherein one or both of the receiver module and a transmitting module are a component of the text messaging hub.

18. A system comprising: a text messaging hub comprising a processor and a memory that stores instructions that when executed cause the processor to: receive a sign-up request, the sign-up request including a user number for a user, the user number for the user including a phone number for the user; responsive to receiving the sign-up request; assign a first user-specific system number to which a mobile device is to direct future text messages, the mobile device being associated with the phone number for the user, wherein assigning the first user-specific system number comprises storing the first user-specific system number and the phone number for the user to a set of authorized user number and specific number pairs, the first user-specific system number being different from the phone number for the user; and send an initiation message to the mobile device associated with the phone number for the user, the initiation messaging including the first user-specific system number; receive a text message from a device, the text message being directed to a specific number associated with the text messaging hub, wherein the specific number is one of the plurality of possible numbers associated with the text messaging hub, the text message including the phone number for the user; determine whether the text message is authentic based on whether the phone number for the user is associated with the specific number based on the set of authorized user number and specific number pairs, wherein the phone number for the user is not associated with the specific number when the specific number to which the message is directed is not the first user-specific system number, determine that the text message is not authentic in response to determining the phone number for the user is not associated with the specific number; and responsive to determining that the text message is not authentic: assign a second user-specific system number to which the mobile device is to direct future text messages; and send, to the mobile device at the phone number for the user, a notification text message that includes the second user-specific system number.

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14. A method of reproducing transmitted information according to claim 11, wherein prior to the first-mentioned step of decoding, said method includes delaying at least certain ones of the words of said blocks of received digital data by an amount different from any delay imparted to the remaining words, thereby compensating for a corresponding delay imparted prior to transmission.

11. A method of reproducing transmitted information that is received as blocks of digital data words of a predetermined bit length, and which includes a first series of k check words and a second series of k check words, comprising the steps of decoding the received digital data words and the first and second series of check words and correcting the decoded digital data words and the series of first check words by said series of second check words; delaying said corrected digital data words and said series of first check words by respective different amounts so as to arrange the same into a different arrangement order; and decoding the digital data words and the series of first check words so arranged, and correcting the digital data words by said series of first check words; wherein each such decoding is achieved by generating syndromes according to a parity check matrix having n columns and k rows, and in which each element of one predetermined row is selected from digital values from zero to 2.sup.m -1, so that the same value does not appear twice in said predetermined row, and in which the elements in the remaining rows are selected to be a given power, for all the elements in each respective row, of the corresponding elements in said predetermined row, where m is the bit length of said data words and n is the number of words in each block formed of the digital data words and the associated check words.

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7. The information processing apparatus according to claim 5 , wherein the processor identifies second sentences having sentence scores, which lie below the threshold.

5. The information processing apparatus according to claim 4 , wherein the processor displays the sentence by: identifying first sentences having sentence scores, which exceed a threshold; and selecting the sentence from the first sentences.

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10. The social networking website system of claim 1 wherein the at least one social network comprises providers to the current location of one or both of goods and services of professional interest to the user.

1. A social networking website system that supports user interactions in a plurality of social networks, the social networking website system comprising: a server configured to create a new social network automatically, the server enabling communication among a plurality of mobile devices used by a corresponding plurality of users via the new social network, each of the plurality of mobile devices identifies a corresponding current location information based on GPS coordinates; the server automatically, without need of user consent, without any upfront registration requirements or invitations, without employing invitations and explicit user acceptance, automatically registering and including a first user among the plurality of users in the new social network based on the GPS coordinates from the corresponding one of the plurality of mobile devices; and the social networking website system facilitating creation and sharing of new postings, the new postings each comprising audio inputs recorded by the user, a digital photo recorded, a video recorded, and textual inputs provided by the user on a corresponding one the plurality of mobile devices; and wherein a current location to social networks mapping is used to determine appropriate social networks and associated social groups, in the street, city, county, region, state or country in which the user can participate in; wherein the social networking website system also provides each user the ability to create their own social groups to share postings on common interests or affiliations.

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2. The method of claim 1 wherein the learning graph further comprises a plurality of learning collection nodes, wherein the learning collection nodes have a plurality of edges to content nodes.

4. The method of claim 2 wherein the learning graph further comprises a plurality of learning goal nodes, wherein one or more person nodes have one or more edges to one or more learning goal nodes.

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41. A computer system having a touch interface and a graphical user interface, wherein the computer system includes a computer memory encoded with executable instructions for causing the computer system to generate a graphical user interface, the graphical user interface comprising: a main window displayed on a touch sensing touch screen including an indication of a gesture to be performed on the touch screen, the main window configured for detecting a practice gesture; and a touch monitor window graphically distinct from and in an area of the touch screen non-overlapping with the main window, the touch monitor window including an interactive feedback mechanism displayed on the touch screen, the interactive feedback mechanism including an indication of an accuracy of the practice gesture currently being performed.

56. A mobile telephone having a touch interface and a graphical user interface, wherein the mobile telephone includes the computer system of claim 41 .

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9. The method of claim 7 wherein searching for the exact match begins searching the source information located in a designated fact checking database and then goes to a broader set of source information; wherein utilizing pattern matching begins utilizing the source information located in the designated fact checking database, then goes to the broader set of source information; and wherein the natural language search begins searching the source information located in the designated fact checking database, then goes to the broader set of source information.

7. The method of claim 1 further comprising fact checking the target information by comparing the target information with source information to generate the fact check result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold, and the status of the target information is based on the format of the target information and the comparison of the target information with the source information.

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1. A computer-readable storage medium having stored thereon executable instructions for causing a computer to perform a utility program for selecting images for a markup language document comprising: determining a number of images to display in the markup language document; obtaining a set of random numbers, the set of random numbers containing a plurality of random numbers, a number of the plurality of random numbers being equal to the determined number of images; retrieving images from a group of images using the set of random numbers, each retrieved image being associated with an item represented in that retrieved image; determining a location in the markup language document for each of the retrieved images from an instruction embedded in the markup language document; and placing the retrieved images in the markup language document, the retrieved images being, placed in the locations defined in the instruction.

2. The computer-readable storage medium of claim 1 having further executable instructions comprising: validating the retrieved images against validation criteria; and retrieving a replacement image from the group of images if a retrieved image fails the validation.

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14. The system of claim 9 wherein the processors are further configured to perform operations comprising: (a) searching by the second processor, the at least one conversation-specific file according to the first metadata category and a first metadata category value; and (b) transmitting the conversation-specific file from the second processor to the first processor, if the conversation-specific file includes the first metadata category and the first metadata category value.

9. A system for electronic document review comprising: a first processor associated with a reviewer; a second processor associated with a discovery device; and a data storage device including a non-transitory computer-readable medium having computer readable code for instructing the processors, and when executed by the processors, the processors perform operations comprising: (a) parsing by the second processor, a source file into at least one conversation-specific file, the conversation-specific file comprising message content and a first metadata category; (b) transmitting from the second processor to the first processor the message content and the first metadata category for the at least one conversation-specific file; (c) searching by the second processor, the at least one conversation-specific file for message content according to the first metadata category; (d) filtering by the second processor, the message content by selecting or deselecting the message content for display by the first processor according to the first metadata category; and (e) transmitting the filtered message content from the second processor to the first processor.

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1. A system for analyzing a first request for proposal from among a plurality of requests for proposal, the system comprising: an associative memory including a plurality of data, the plurality of data comprising at least one of the group consisting of data for the plurality of requests for proposal, data related to successful proposal bid activities, and data related to unsuccessful proposal bid activities, the plurality of data having a plurality of associations, and being collected into associated units of data, wherein the associative memory is configured to be queried based on at least one relationship selected from the group consisting of direct relationships and indirect relationships among the plurality of data, and wherein the associative memory further includes a content-addressable structure; an input device in communication with the associative memory, wherein the input device is configured to provide the first request for proposal to the associative memory in a format understandable to the associative memory, and wherein the associative memory is configured to digest the first request for proposal to be included within the plurality of data, wherein a digested request for proposal is formed; and an analyzer in communication with the associative memory, wherein the analyzer is configured to analyze the digested request for proposal by receiving a query comprising one or more terms, creating relationships among the plurality of data in the associative memory based on the query, and returning an output that includes requirements or other attributes presented in the digested request for proposal based on the query; wherein the analyzer is further configured to compare the digested request for proposal to a previously received second request for proposal to form a first comparison, and wherein the analyzer is further configured to modify the output based on the first comparison to form a first modified output; and wherein the analyzer is further configured to compare the digested request for proposal to a previous response to the previously received second request for proposal to form a second comparison, and wherein the analyzer is further configured to modify the output based on the second comparison to form a second modified output.

3. The system of claim 1 further comprising: a document management system configured to receive the second modified output and use the second modified output to produce a draft of a response to the first request for proposal.

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18. The system of claim 17 , wherein as the code modification command set is entered or modified, the display of the customized code snippet dynamically changes to reflect the effects of the command set.

17. The system of claim 12 , wherein use of the code modification command set opens a new window that contains multiple panels, wherein the panels contain a copy of the code snippet, a display of the customized code snippet, and a place to enter or modify the command set.

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1. A universal driving method for peripherals, for driving a peripheral device connected to a host system, and the peripheral device including a connection interface, and the host system including a connection port of the connection interface connected to the peripheral device, comprising: connecting with the host system and the peripheral device; executing an operating system program installed in the host system for recognizing the peripheral device through Universal Resource Locator which is used to resolve the peripheral device's address; accessing the peripheral device for acquiring a scripting language stored in the peripheral device, wherein the scripting language is Markup Language for driving the peripheral device; establishing a channel configured to access the peripheral device; executing the Markup Language; initiating a web-based user interface allowed to control or access the peripheral device by executing the Markup Language; wherein the user interface is an operating interface created by a web browser executing the Markup Language; and driving the peripheral device.

3. The driving method according to claim 1 , wherein the Markup Language is Hypertext Markup Language (HTML), Extensible Markup Language (XML), or Hayes command set.

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14. The electronic device of claim 13 further comprising ranking the likelihood values, wherein the stored content is accessed based on said ranking.

15. The electronic device of claim 14 wherein the ranking is highest likelihood to the lowest likelihood.

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11. The method of claim 5 further comprising: disambiguating, as part of converting, the unstructured text; and forming, from resulting disambiguated text, annotation query language statements.

12. The method of claim 11 wherein parsing comprises parsing the annotation query language statements.

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32. A system according to claim 29 , wherein the taxonomy is displayed in the form of a spreadsheet.

29. A system for managing a collaborative deal closing process that provides a means for tracking and managing signature pages of a closing deal using a taxonomy displayable by a computing device, the system comprising: means for receiving a list of users that are authorized to access the closing deal, the list including an identifier associated with each of the users; means for storing the list of authorized users; means for parsing the identifier associated with each user, wherein the identifier includes one from the group consisting of an email address, a domain name, a name of a company or group, and any combination thereof of the authorized users; means for grouping the users according to parties based on the identifier; means for creating a taxonomy including a listing of documents relevant to the deal and a listing of the parties of the deal; means for receiving at least one document at the server; and means for storing relevant pages of the at least one document, wherein each page is associated with a relevant party in the taxonomy.

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18. The method of claim 13 , wherein displaying the voicemail speech that is not recognized by the transcription application differently than the voicemail speech that is recognized by the transcription application comprises modifying text corresponding to the unrecognized voicemail speech based on one or more of a font, a color, or a size of the text.

13. A method implemented on a computer system for accessing voicemail messages, the method comprising: receiving a voicemail message generated from a missed call; displaying a text transcription of the voicemail message, wherein the text transcription displays voicemail speech that is not recognized by a transcription application differently than voicemail speech that is recognized by the transcription application; receiving an indication to forward the text transcription of the voicemail message to a recipient; and forwarding the text transcription of the voicemail message to the recipient.

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6. A computer-implemented method, said computer including a processor and having a graphical display that includes at least one object that is associated with data, said method comprising: splitting said graphical display into a left area forming a left rectangle, a center area forming a center rectangle, and a right area forming a right rectangle; displaying a star schema in said graphical display by displaying dimension objects including dimension tables that include attribute data in said left area, a facts object including a facts table that includes measurement data in said center area, and additional dimension objects including dimension tables that include attribute data in said right area and by displaying connecting lines across said rectangles in the graphical display to illustrate associations between said facts object and said dimension objects, wherein said objects in each area are manipulated independently of said other objects in said each area and said objects in each other area; accepting input that reduces said at least one object in one area, wherein said at least one object is one of said dimension objects and facts objects; and in response to reducing said at least one object in said one area; reducing said display of said one area that includes said reduced at least one object; realigning vertically and horizontally other objects within said reduced area relative to said reduced at least one object in said reduced area; moving said display of said each other area including at least one object that is not included in said reduced area in response to reduction of the display of said reduced area on the graphical device, thereby enabling efficient analysis of said data associated with said at least one object that is included in said reduced area; and realigning said objects in said each other area with the realigned other objects within said reduced area, wherein positions of said objects in said each other area are adjusted in at least one of a horizontal direction and a vertical direction to accommodate alignment of said other objects within said each other area.

10. The computer-implemented method of claim 6 further comprising including at least one additional object that is associated with said data within said at least one object thereby enabling efficient analysis in a recursive manner of said data associated with said at least one additional object.

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1. A method for voice recognition, the method comprising: obtaining a voice signal; performing two or more voice recognition analyses in parallel on the voice signal, wherein each voice recognition analysis uses a filter bank defined by a different maximum frequency and a different minimum frequency and wherein each voice recognition analysis produces a recognition probability r i of recognition of one or more speech units, whereby there are two or more recognition probabilities r i , wherein each recognition probability r i represents a probability that the voice signal matches a recognized unit of speech, wherein performing the two or more voice recognition analyses in parallel includes performing a first voice recognition analysis on the voice signal based on a first maximum frequency f max and a first minimum frequency f min ; wherein f min and f max are adjusted dynamically during the first voice recognition; and performing one or more additional voice recognition analyses on the voice signal based on a different maximum frequency given by f max ±Δf max and a different minimum frequency given by f min ±Δf min ,where Δf max <f max and Δf min <f min ; and determining a final recognition probability P f based on the two or more recognition probabilities r i ; determining a confidence measure based on the final recognition probability and the two or more recognition probabilities r i ; and using the confidence measure as an acceptance criterion for the final recognition probability P f after determining the final recognition probability P f .

8. The method of claim 1 wherein Δf max is between about 1% and about 5% of f max .

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1. A method implemented by an electronic device, the method comprising: receiving an instruction to scale a region of a displayed structured document, the region including at least one element or a portion thereof; in response to the received instruction: identifying a dominant alignment of the region, the dominant alignment being an alignment of a dominant image in the region or an alignment of text within a dominant text block in the region; scaling the region; and outputting to a display interface a portion of the scaled region intersecting a viewport defined for a display, the viewport being aligned with the scaled region according to the dominant alignment when it is intersected with the scaled region.

6. The method of claim 1 , wherein scaling the region comprises magnifying the region.

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17. A system including memory and one or more processors operable to execute instructions stored in memory, comprising instructions to: identify a plurality of messages from one or more databases; determine a plurality of interrogative sentences from the messages; determine starting n-grams from the interrogative sentences; determine a group of task indications, wherein each of the task indications of the group is based on a set of one or more of the starting n-grams, and wherein determining to include a given task indication of the task indications in the group is based on a count of the starting n-grams that conform to the given task indication; provide the group of the task indications; receive, in response to providing the group of the task indications, one or more task association measures for each of the task indications of the group, wherein a given task association measure for a given task indication is indicative of likelihood that the given task indication is associated with a task request; determine a task association score for each of the task indications of the group, wherein the task association score for the given task indication is based on the one or more task association measures received for the given task indication; and store the task association score for each of a plurality of the task indications of the group.

22. The system of claim 17 , wherein the instructions to identify the plurality of messages includes instructions to identify the messages based on recipients of the messages.

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9. A computer comprising a processor controlling operation of the computer according to computer readable instructions stored in a memory, wherein, upon execution of the computer readable instructions by the processor, the computer performs a method for determining access rights to a range of objects by a range of users through scope information, comprising: receiving, from a first user, request to access a first resource; determining that a scope of a first access control metadata element encompasses the first resource, wherein the first access control metadata element includes: a first set of one or more XML statements that define the scope of the first access control metadata element by selecting a plurality of resources, the scope of the first access control metadata element encompassing the first resource and at least one other resource; a second set of one or more XML statements that define access rights for the plurality of resources within the scope of the first access control metadata element; and a third set of one or more XML statements that define a plurality of users to which the first access control metadata element applies; determining that a scope of a second access control metadata element encompasses the first resource, wherein the second access control metadata element includes: a first set of one or more XML access control-related statements that define the scope of the second access control metadata element by selecting one or more resources, the scope of the second access control metadata element encompassing the first resource; and a second set of one or more XML statements that define access rights for the plurality of resources within the scope of the second access control metadata element; and a third set of one or more XML statements that define a plurality of users to which the second access control metadata element applies; determining that the first user is among the plurality of users to which the first access control metadata element applies as defined by the third set of one or more XML statements of the first access control metadata element; determining that the first user is among the plurality of users to which the second access control metadata element applies as defined by the third set of one or more XML statements of the second access control metadata element; determining that a first access right defined in the first access control metadata element conflicts with a second access right defined in the second access control metadata element; in response to determining that the first access right conflicts with the second access right, determining whether the first access right supersedes the second access right; and in response to determining that the first access right supersedes the second access right, applying the first access right to the access request from the first user.

10. The computer of claim 9 , wherein the first access right comprises granted access to the first resource.

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37. An article of manufacture, comprising: a storage medium; and a plurality of programming instructions stored in the storage medium and configured to cause an apparatus, in response to execution of the instructions by an apparatus, to perform operations associated with inferring at least one meaning of a user's actions with respect to a software component out of a plurality of software components for at least one user involving at least one domain, the operations comprising: representing at least one user goal with respect to the domain, the goal represented independent of tasks which the plurality of software components can perform; representing at least one task which can be accomplished by the software component in the domain independent of stated user goals; establishing an association between at least one at least one linguistic or pragmatic item and a meaning of the user's actions, the at least one linguistic or pragmatic item having an association with the task; establishing an association between the at least one linguistic or pragmatic item and the user goal; inferring, using the associations, that the software component which can accomplish the at least one task is appropriate out of the plurality of software components for achieving the at least one user goal; and performing the at least one task by executing the software component using at least one association to infer the meaning of the user actions with respect to the software component.

38. The article of claim 37 , wherein the software component provides the at least one linguistic or pragmatic item corresponding with the task.

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11. The method of claim 6 , wherein receiving the audio signals comprises concurrently receiving the audio signals.

6. A method, comprising: receiving audio signals corresponding respectively to different regions of an environment; analyzing the audio signals to recognize speech from each of the audio signals, wherein analyzing the audio signals comprises concurrently generating a plurality of different text streams that each correspond to a different one of the audio signals; generating a confidence value for each of the plurality of different text streams corresponding to the audio signals, wherein the confidence value for a particular text stream indicates an estimated accuracy of the recognized speech from said particular text stream, the confidence value generated based at least in part on expected speech input for a predetermined command lexicon; and selecting at least one of the plurality of different text streams associated with the recognized speech from at least one of the audio signals based at least in part on a respective confidence value.

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29. The apparatus of claim 23 , wherein while selecting links to be included in the new model, the training mechanism is configured to: rank the links and prospective links based on the determined link ratings and select the N top-ranked links and prospective links to be included in the new model.

23. An apparatus that selects links while updating a probabilistic generative model for textual documents, comprising: a data store configured to store a current model, which contains terminal nodes representing words and cluster nodes representing clusters of conceptually related words, wherein nodes in the current model are coupled together by weighted links, wherein if a node fires, a link from the node to another node is activated and causes the other node to fire with a probability proportionate to the weight of the link; a training mechanism configured to apply a set of training documents containing words to the current model to produce a new model, wherein the training mechanism is configured to, determine expected counts for activations of links and prospective links, determine link-ratings for the links and the prospective links based on the expected counts, and select links to be included in the new model based on the determined link-ratings; and an updating mechanism configured to make the new model the current model.

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12. A computer-readable storage medium comprising computer-executable code stored on the medium for causing a processor to perform the following steps: acquiring a representation of a portion of a printed document comprising geographical location information by receiving a captured image of the portion of the printed document via a capture device; indexing the acquired representation of the portion of the printed document for identification of a corresponding mixed media reality document, wherein the corresponding mixed media reality document comprising a matching electronic representation of the printed document, wherein indexing the acquired representation includes specifying an x-y location of at least one of a character, a word and an image from the acquired representation within the printed document; parsing the representation of the portion of the printed document to identify a first geographic location from the geographical location information; identifying a second geographic location of the capture device; and performing an action specified by the mixed media reality document based on the first and second geographic locations, wherein specifying the x-y location of the acquired representation includes one selected from the group of: specifying x-y locations of characters of a printed document, specifying x-y locations of words of the printed document, specifying x-y locations of an image or a portion of an image in a printed document, performing an OCR operation and specifying x-y locations of characters or words, and performing feature extraction and specifying x-y locations of characters or words.

14. The computer-readable storage medium of claim 12 , wherein the action is one selected from the group of retrieving information, writing information to a location, performing a search for information, displaying information on a client device, conducting an interactive dialog, deferring the action for later execution, modifying a document, purchase of a product, and input of a command to another system.

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5. The method of claim 4 wherein the first sub-word includes every fourth data bit of the data word beginning with a first data bit of the data word, the second sub-word includes every fourth data bit of the data word beginning with a second data bit of the data word, the third sub-word includes every fourth data bit of the data word beginning with a third data bit of the data word, and the fourth sub-word includes every fourth data bit of the data word beginning with a fourth data bit of the data word.

4. The method of claim 1, further including: determining a third error correction code for a third sub-word of the data word, the third sub-word including a third subset of the data bits of the data word, the third subset comprising non-consecutive data bits of the data word, the third error correction code including a plurality of check bits and being determined based on all of the data bits of the third sub-word; and determining a fourth error correction code for a fourth sub-word of the data word, the fourth sub-word including a fourth subset of the data bits of the data word, the fourth subset comprising non-consecutive data bits of the data word that are intermediate data bits included in the third subset, the fourth error correction code including a plurality of check bits and being determined based on all of the data bits of the fourth sub-word, wherein each data bit of the first sub-word is immediately followed by a data bit of the second sub-word, each data bit of the second sub-word is immediately followed by a data bit of the third sub-word, each data bit of the third sub-word is immediately followed by a data bit of the fourth sub-word, and at least one of the data bits of the fourth sub-word is immediately followed by a data bit of the first sub-word when the data word is received.

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12. The method of claim 1 , wherein the flag is an implicit flag.

14. The method of claim 12 , wherein the implicit flag is set to indicate the temporal MVP candidates are not to be utilized for motion vector prediction if a co-located picture is an Intra picture.

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4. An apparatus for processing documents, comprising: reading means for reading MICR data from said documents; imaging means for generating image data from said documents; printing means for printing a unique document reference number, hereinafter called DRN, on each of said documents; transport means for moving said documents sequentially, in operative relationship with said reading means, said imaging means, and said printing means; recognition means for receiving said image data from said imaging means and also for recognizing predetermined data on said documents; control means including a memory for receiving said MICR data from said reading means and storing it in a first portion of said memory and also for assigning a said DRN to said MICR data, said control means also including means for receiving said image data and for storing it in a second portion of said memory and also for assigning the corresponding said DRN thereto; interface means coupling said control means with said recognition means to transfer a portion of the corresponding said MICR data to said recognition means to assist said recognition means in recognizing said predetermined data; and said recognition means also providing confidence level data for said predetermined data which is transferred to said control means and stored in said first portion of memory by the corresponding said DRN.

5. The apparatus as claimed in claim 4 in which said imaging means produces uncompressed data which is forwarded to said recognition means and also includes compressor means for compressing said uncompressed data prior to its being stored in said second portion of said memory.

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12. The method of claim 1 wherein generating the summarization document for each URL include analyzing each article associated with the URL to extract keywords and/or topics and assigning a score that represents how closely each article relates to a keyword and/or topic.

1. A method of providing a content discovery platform for optimizing a number of social network engagements from an audience of a first user on one or more social networks, the method is implemented in one or more servers programmed to execute the method, the method comprising: retrieving social media data from users on the one or more social networks, wherein the social media data includes one or more URLs associated with one or more articles, respectively; aggregating the social media data for each URL by a number of users, actors and actions with respect to each URL; computing a social importance score for each URL of the one or more URLs as a function of the aggregated data associated with that URL so as to estimate engagement of an article associated with a URL on the one or more social networks; ranking the one or more URLs by social importance score; generating a summarization document for each URL of the one or more URLs, wherein a summarization document for each URL includes information extracted from a web page of the article that is associated with the URL and information derived from the extracted information; indexing the summarization documents relative to social importance score; selecting criteria for optimizing the number of engagements of the audience of the first user based on input data from the first user; fetching a model for optimizing the number of engagements from the audience of the first user on the one or more social networks based on the criteria selected; generating query documents with information relating to the first user; generating features as a function of data in each query document and summarization document; and applying the selected model to the features to calculate scores for each URL summarization document; and selecting one or more summarization documents to present to the first user as a function of the calculated scores for the summarization documents, wherein the presentation of summarization documents thereby enables the first user to subsequently select one or more URLs from the summarization documents for posting on the one or more social networks to receive an optimal number of social network engagements from the audience of the first user.

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6. The method of claim 1 , further comprising: receiving an input from the user device, the input identifying one of the first and second candidates; and performing an action using the identified candidate.

1. A computer-implemented method that is executed using one or more processors, the method comprising: receiving, from a user device, data representing user input to a virtual keyboard on the user device; identifying a character string based on the data representing the user input; performing a spellcheck on the character string to identify a first and a second candidate for the character string, the first and the second candidates being ranked by the spellcheck according to likelihood that a respective candidate is a correct spelling of a word corresponding to the character string, the first candidate ranked higher than the second candidate; for each of the first and second candidates, determining a popularity of the first and second candidates based on a respective frequency at which the first and second candidates are used as search queries input to a search engine, the second candidate having a higher popularity than the first candidate; adjusting the ranking of the candidates based on the popularity of the first and the second candidates such than the second candidate is ranked higher than the first candidate; and outputting, to the user device, a listing of the first and the second candidates based on the adjusted ranking.

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4. The method of claim 1 , further comprising detecting as said entry one of: a number of input member actuations, and a quantity of received text.

1. A method of enabling input into a handheld electronic device comprising an input apparatus and a processor apparatus that comprises a memory, the input apparatus comprising a plurality of input members, at least some of the input members each having a number of linguistic elements assigned thereto, the memory having stored therein a plurality of language objects and a number of word frames, at least some of the language objects each comprising a number of the linguistic elements, the method comprising: detecting an entry on a handheld electronic device of a new language object not already stored in the memory, the new language object comprising a plurality of linguistic elements; determining with the processor apparatus that the at least a portion of the plurality of linguistic elements of the new language object comprises a sequential plurality of linguistic elements that are each assigned to a given input member; associating the new language object with a word frame, wherein the word frame is associated with a language object having a number of linguistic elements that is different from a number of linguistic elements of the new language object, and wherein the word frame comprises at least some of the plurality of linguistic elements of the new language object and a representation of the given input member in place of the sequential plurality of linguistic elements that are each assigned to the given input member.

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21. A computer program product stored in a non-transitory form in a computer-readable device, said program when executed by a computer system causing the computer system to carry out a process comprising: collecting a multiplicity of documents from diverse applications, said documents being in respective different formats unique to the respective applications; automatically generating respective indicators that are associated with said documents and comprise respective items of time information; maintaining in non-transitory form a main collection of the collected documents and the indicators associated therewith; said main collection of documents being unbounded in practical terms consistent with the computer system to thereby accommodate many documents and the respective indicators associated therewith in a form that is selectively searchable and retrievable by the computer system; causing the computer system to respond to search criteria provided to the computer system by generating, from said main collection of documents, a subcollection of a multiplicity of documents that is a subset of the main collection documents; causing the computer system to concurrently display on a computer display representations of plural documents that comprise only a segment rather than all of the documents of one of the main collection or the subcollection of documents; said displaying comprising displaying the representations in an arrangement consistent with the indicators associated with the documents corresponding to the representations that are displayed at the time, wherein at least some of the displayed representations show at least some information indicative of a content of the respective documents, which content-indicative information is in addition to any display of hierarchical data structure or time of creation of modification of documents; said display further including a display of an enhanced representation of at least one of the documents corresponding to the displayed segment while continuing to display other representations of the documents in the segment; maintaining live at least the main collection of documents by automatically responding to subsequent events to include new documents in the main collection in response to said new documents being collected in response to said subsequent events, and automatically generating and storing new indicators associated with said new documents; causing the computer system to respond to said search criteria by automatically including in a subcollection generated in response to said search criteria or new search criteria those of said new documents that meet said criteria; and causing said display facility to display a segment that includes representations of at least some of said new documents.

22. The computer program product of claim 21 in which said program, when executed, causes said display of an enhanced representation of at least one of the documents to appear in response to an interaction of a user with the computer system other than clicking a mouse.

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14. The computer-readable medium of claim 12 , further comprising normalizing the terms within the user queries to forms such that the second location can interpret the user query.

15. The computer-readable medium of claim 14 , wherein normalizing comprises at least one of: correcting spelling errors in the user query; correcting spacing errors in the user query; compensating for the use of synonyms or other variations; and determining a class of the terms within the user query.

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7. The method of claim 1 , wherein obtaining the first data comprises obtaining the associated NLU data from the audio data by using the first speech recognition model.

1. A method, comprising: obtaining first data comprising audio data processed by a natural language understanding (NLU) system at least in part by using a first NLU model, a first N-best list of word sequences generated by using a first speech recognition model to recognize at least a portion of the audio data, and associated NLU data indicating how the audio data was understood by the NLU system; and modifying, using at least one hardware processor, the first speech recognition model and the first NLU model based at least in part on the first data, including using the first N-best list of word sequences, to obtain a second speech recognition model and a second NLU model.

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8. The method of claim 2 , further comprising: identifying characteristics of the plurality of segments and refining the plurality of segments based on the characteristics.

9. The method of claim 8 , wherein identifying characteristics of the plurality of segments of a first video channel is used to generate a description of a monitored scene of a second video channel.

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6. The CAM device of claim 1 , wherein the data encoder circuit comprises a lookup table storing a mapping between the first data word and the encoded data word.

7. The CAM device of claim 6 , wherein the mapping is constructed to minimize power consumption of the CAM device.

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16. The computer-readable medium of claim 15 , wherein the operations further comprise receiving the phrase, wherein the phrase includes one or more terms that correspond to the voice action.

15. A non-transitory computer-readable medium storing instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: classifying a received phrase as an incomplete phrase for performing a voice action based at least on determining that (i) the voice action requires a parameter, and (ii) that no term of the phrase corresponds to the parameter; in response to classifying the phrase as an incomplete phrase, generating a prompt for entry of the parameter; in response to the prompt, receiving data indicating an entered parameter; and providing, for output, a suggested complete phrase for performing the voice action using the entered parameter, the suggested complete phrase comprising a phrase that when subsequently received causes the voice action to be performed without prompting for the entry of the parameter after determining that the suggested complete phrase includes one or more terms that correspond to the voice action.

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11. The method of claim 9 , wherein determining a searching cost corresponding to the first navigation hierarchical structure diagram of the plurality of navigation hierarchical structure diagrams includes: determining a plurality of confidence levels corresponding to respective ones of the plurality of nodes based at least in part on the historical user operation data associated with the user; calculating a viewing cost of the first navigation hierarchical structure diagram based at least in part on confidence levels of nodes associated with the first navigation hierarchical structure diagram and branch positions corresponding to the nodes; calculating a clicking cost of the first navigation hierarchical structure diagram based at least in part on confidence levels of the nodes and hierarchical positions corresponding to the nodes; and calculating the searching cost associated with the first navigation hierarchical structure diagram based at least in part on the clicking cost and the viewing cost.

9. A method, comprising: receiving a search query input at a search box from a user; and in response to the search query: obtaining historical user operation data associated with the user; generating a plurality of navigation hierarchical structure diagrams based on a website navigation category diagram and the historical user operation data associated with the user, wherein: the website navigation category diagram comprises a plurality of nodes; the plurality of navigation hierarchical structure diagrams comprises a first navigation hierarchical structure diagram and a second navigation hierarchical structure diagram, wherein the first navigation hierarchical structure diagram of the plurality of navigation hierarchical structure diagrams is generated based at least in part on one or more of the following binding conditions: nodes associated with the first navigation hierarchical structure diagram with a corresponding confidence level greater than a preset threshold value are included in a predetermined level of the first navigation hierarchical structure diagram; a total number of nodes in a level of the first navigation hierarchical structure diagram is no greater than a number of nodes for which associated information is permitted to be displayed at a web page; and for a particular node that appears more frequently in the first navigation hierarchical structure diagram more than a substantially similar node appears at the website navigation category diagram, at least one copy of that particular node is eliminated; the first navigation hierarchical structure diagram comprises a first at least subset of the plurality of nodes and the second navigation hierarchical structure diagram comprises a second at least subset of the plurality of nodes; and each of the first at least subset of the plurality of nodes and the second at least subset of the plurality of nodes is different from the website navigation category diagram; determining a plurality of searching costs corresponding to respective ones of the plurality of navigation hierarchical structure diagrams based at least in part on the historical user operation data associated with the user; selecting a selected navigation hierarchical structure diagram of the plurality of navigation hierarchical structure diagrams based on the plurality of searching costs corresponding to respective ones of the plurality of navigation hierarchical structure diagrams; and implementing, using one or more processors, at least in part a website navigation process using the selected navigation hierarchical structure diagram.

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10. A computer-readable storage device storing instructions that, when executed by a processor, cause performance of operations that comprise: receiving, by a computing device, a first orally-provided input that includes a first carrier phrase; and performing, by the computing device and in response to having received the first orally-provided input, an action by a first application program due to the first orally-provided input including the first carrier phrase, wherein the first carrier phrase is registered with the operating system of the computing device as being associated with the first application program for causing a command to be performed by the first application; wherein the computing device is configured to perform an action by a second application program due to orally-provided input including a second carrier phrase, wherein the second carrier phrase is registered with the operating system of the computing device as being associated with the second application program for causing a command to be performed by the second application.

11. The computer-readable storage device of claim 10 , further comprising: receiving, by the computing device, a second orally-provided input that includes the second carrier phrase; and performing, by the computing device, the action by the second application program due to the second orally-provided input including the second carrier phrase.

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13. A non-transitory computer-readable medium storing a computer program that when executed on a computer, performs a method comprising: acquiring a representation of actions of a user performing multiple iterations of a task with a web service; analyzing the acquired actions to determine semantics and a plurality of variables describing the user actions, each variable being an input to the web service that the web service ordinarily requests the user to enter during the multiple iterations of the task, the variables comprising free variables and bound variables, where which of the variables are the free variables and which of the variables are the bound variables is determined automatically without prompting the user, by analyzing differences in the actions of the user across the multiple iterations of the task; representing the semantics and the variables in at least one script file, the at least one script file supporting performance of user interaction with the web service based on the semantics and values provided for the variables, where each bound variable has a constant value over multiple executions of the at least one script file, and each free variable has a value that is changeable over the multiple executions of the at least one script file; and associating the at least one script file with a unique uniform resource locator (URL) address that is selectable to initiate performance of user interaction with the web service, wherein the unique URL address is selectable by different user devices to invoke and execute the user interaction.

14. The non-transitory computer-readable medium of claim 13 , wherein analyzing comprises parsing the recorded actions and analyzing the web service on which the actions were performed.

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9. The method of claim 8 , wherein parsing the application to locate the plurality of audio tags includes extracting the segments of the text string associated with a portion of the plurality of audio tags from the application.

10. The method of claim 9 further comprising extracting a voice property associated with the plurality of audio tags from the application.

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20. The receiver-side terminal of claim 19 , further comprising: a speaker configured to output the translation voice signal in the second language.

19. The receiver-side terminal of claim 17 , wherein the storage unit comprises a voice-for-TTS database for conversion of the translation text in the second language to the translation voice signal in the second language, and the controller is configured to control to use the voice-for-TTS database to generate the translation voice signal in the second language corresponding to the translation text in the second language.

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8. The method of claim 7 , wherein the display is disposed on a mobile communication device.

9. The method of claim 8 , wherein the step of discerning the set of suspected geographical origins includes obtaining Global Positioning System (GPS) coordinates from the communication device.

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16. The method of claim 9 , where each pair comprises (1) a first directed relationship having a first strength value connecting a first entity in the pair to a second entity in the pair, or (2) a first directed relationship having a first strength value connecting the first entity to the second entity and a second directed relationship having a second strength value connecting the second entity to the first entity.

9. A method comprising: obtaining data representing entities, each entity being a query, a document, a session of queries, a time, or a domain of a document; identifying a plurality of pairs of entities from a subset of the entities from search history data, where each pair is either: (1) (i) a query paired with (ii) another query, a document, a session of queries, or a time, or (2) (i) a document paired with (ii) a session of queries, or (3) two documents paired with each other, and where the plurality of pairs of entities comprise a first pair of entities that is a first document paired with a first session of queries and a second pair of entities that is a second session of queries paired with a second document; generating, for each pair of entities, using the search history data, a respective directed relationship having a respective strength value and connecting a first entity of the pair to a second entity of the pair; and determining, for any two entities that are directly or indirectly connected through directed relationships, a relevance score from strength values of the directed relationships connecting the two.

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1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes each corresponding to a plurality of objects, respectively, associated with the online social network, each object being of a particular object-type; receiving, from a client device of the first user, a first search query comprising a selection of a first query-domain, the first query-domain corresponding to a first object-type; identifying, responsive to the first search query, a first set of objects of the plurality of objects matching the first object-type, each of the identified objects corresponding to a second node within a threshold degree of separation of the first node; sending, to the client device of the first user, a first search-results page responsive to the first search query, the first search-results page comprising references to one or more of the identified objects from the first set of objects and one or more query-filter elements, each query-filter element corresponding to a query-filter associated with the first query-domain, wherein each query-filter element is activatable to apply the associated query-filter to the identified objects; and receiving, from the client device of the first user, a second search query comprising a selection of one or more of the query-filters in response to the first user activating the corresponding query-filter elements.

8. The method of claim 1 , wherein the first object-type is selected from a group consisting of: users, photos, posts, pages, applications, events, locations, or user groups.

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8. A system comprising: at least one programmable processor; and a machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising: determining, at a language layer of a query language architecture, a query syntax of a received query and a definition of a result set for the query; checking, at a compiler layer of the query language architecture, semantics of the received query, the compiler layer supporting a single data model usable on multiple application layers of a multi-layer business software architecture; reading, from a data dictionary in a persistent layer of a database from which query results are to be returned, a field expression corresponding to the result set; building, by the compiler layer, the field expression into a query statement; executing, at a runtime layer of the query language architecture, the query including the query statement; and returning results to the query per the result set based on execution of the query on the database.

11. A system as in claim 8 , wherein the query syntax comprises use of logical associations to represent connections between entities.

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1. A method performed by data processing apparatus, the method comprising: receiving a search query, the search query including one or more terms that include a name corresponding to one or more individuals; identifying a plurality of search results responsive to the query, wherein the plurality of search results includes a first search result, the first search result corresponding to a cluster of social media resources associated with a particular individual of the one or more individuals, and wherein each resource in the cluster of resources is associated with a corresponding cluster identifier that identifies the cluster of resources; providing for presentation the first search result and one or more other search results of the plurality of search results; receiving user feedback for the first search result that identifies the cluster of resources associated with the particular individual, wherein the feedback provides an indication of the accuracy of the cluster of resources; and processing the received feedback to determine whether to modify the cluster of resources associated with the particular individual, where the processing includes assigning a weight to the user feedback, where the weight of the user feedback is determined based at least on one or more factors associated with the user, and where the one or more factors include a level of a social connection between the user and the one or more individuals.

11. The method of claim 1 , where modifying a cluster includes generating an additional feature to be used in the clustering.

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1. A machine-implemented method of albuming graphic elements, comprising: identifying candidate relative layouts of graphic elements on a page, wherein each of the candidate relative layouts describes a respective set of layout relationships among the graphic elements; generating for each of the candidate relative layouts a respective set of constraints describing the corresponding set of layout relationships among the graphic elements; determining a respective determinate layout of the graphic elements on the page from each set of constraints; and selecting one of the determinate layouts as a final layout of the graphic elements on the page.

26. The method of claim 1 , further comprising initiating the determining of the determinate layouts by transmitting a message from a client to a server.

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2. The method of claim 1 , further comprising: sending, to the client device of the first user, a query-initiation page responsive to a selection of a query field by the first user, the query-initiation page comprising one or more query-domain elements corresponding to one or more query-domains, respectively, wherein each query-domain element is activatable to generate a search query comprising a selection of the associated query-domain.

3. The method of claim 2 , wherein receiving the first search query comprises receiving an indication the first user has activated a first query-domain element corresponding to the first query-domain.

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1. A control system for communication robot for supporting input of interactive actions to be performed by a communication robot, comprising: a first storage storing in advance information on a plurality of behaviors associated with a plurality of behavior programs including a spontaneous behavior program for performing a spontaneous behavior and a reflex behavior program prepared with inclusion of determination of a precondition and for performing a reflex behavior in response to behavior of a person when the precondition is satisfied; a displayer displaying on a display a list of said plurality of behaviors in a user-selectable manner based on said information stored in said first storage; a detector detecting a user's operation to an input device to select a behavior to be performed by said communication robot from said list of behaviors displayed by said displayer; a behavior decider deciding the behavior to be performed by said communication robot on the basis of a detection result by said detector; a second storage storing the behavior decided by said behavior decider as input history information; an accumulator accumulating a plurality of input history information stored by said second storage; and a generator generating reproductive motion information for interactive actions to be performed by said communication robot on the basis of the plurality of input history information accumulated by said accumulator.

6. A control system for communication robot as set forth in claim 1 , further comprising a transmitter, when said behavior decider has decided the behavior to be performed by said communication robot, transmitting an execution instruction for said behavior to said communication robot.

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16. A computer implemented method comprising: enabling, via a security module, secure information transfer between a web content scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine.

30. The method of claim 16 , wherein the web content scripting engine comprises a web browser scripting engine.

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32. The non-transitory computer readable medium of claim 28 , wherein the computer executable instructions defining the step of detecting electrode position candidates in a second frame of the fluoroscopic image sequence using at least one trained electrode detector comprise computer executable instructions defining the steps of: detecting a first set of electrode position candidates in the second frame using a first trained electrode detector; detecting a second set of electrode position candidates by pruning the first set of electrode position candidates using a second trained electrode detector; and clustering the second set of electrode position candidates using non-maximal suppression.

28. A non-transitory computer readable medium encoded with computer executable instructions for detecting and tracking coronary sinus (CS) catheter electrodes in a fluoroscopic image sequence, the computer executable instructions defining steps comprising: initializing a catheter electrode model in a first frame of a fluoroscopic image sequence based on input locations of a plurality of CS catheter electrodes in the first frame, wherein the catheter electrode model in the first frame comprises a plurality of template points corresponding to locations of the CS catheter electrodes in the first frame; and tracking the catheter electrode model in a second frame of the fluoroscopic image sequence by: detecting electrode position candidates in a second frame of the fluoroscopic image sequence using at least one trained electrode detector; generating catheter electrode model candidates in the second frame based on the detected electrode position candidates and the catheter electrode model initialized in the first frame by translating each of the plurality of template points of the catheter electrode model initialized in the first frame to each of the detected electrode position candidates in the second frame; calculating a probability score for each of the catheter electrode model candidates in the second frame; and selecting one of the catheter electrode model candidates in the second frame based on the probability score, wherein the selected catheter electrode model candidate provides locations of the plurality of CS catheter electrodes in the second frame.

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2. The panel as claimed in claim 1 , wherein the area of said J mark section is approximately the same area as said R mark section area, the area of said S mark section is approximately the same area as said R mark section area, the area of said period mark section is approximately the same area as R mark section area, the area of said semi-colon mark section is approximately the same area as R mark section area, the area of said colon mark section is approximately the same area as R mark section area, the area of said L mark section is approximately the same area as said R mark section area, the area of said M mark section is approximately the same area as said R mark section area, the area of said N mark section is approximately the same area as said R mark section area, the area of said P mark section is approximately the same area as said R mark section area, the area of said I mark section is approximately the same area as said R mark section area, the area of said B mark section is approximately the same area as said R mark section area, the area of said H mark section is approximately the same area as said R mark section area, the area of said Z mark section is approximately the same area as said R mark section area, the area of said X mark section is approximately the same area as said R mark section area, the area of said G mark section is approximately the same area as said R mark section area, the area of said V mark section is approximately the same area as said R mark section area, the area of said F mark section is approximately the same area as said R mark section area, the area of said question mark mark section is approximately the same area as said R mark section area, the area of said C mark section is approximately one and one half times the same area as said R mark section area, the area of said Y mark section is approximately one and one half times the same area as said R mark section area, the area of said K mark section is approximately one and one half times the same area as said R mark section area, the area of said U mark section is approximately one and one half times the same area as said R mark section area, the area of said D mark section is approximately two times the same area as said R mark section area, the area of said O mark section is approximately two times the same area as said R mark section area, the area of said A mark section is approximately two times the same area as said R mark section area, the area of said T mark section is approximately four time times the same area as said R mark section area, the area of said E mark section is approximately four time times the same area as said R mark section area, the area of said Caps mark section is approximately three time times the same area as said R mark section area, the area of said 123 mark section is approximately three time times the same area as said R mark section area, and the area of each of the other marked sections are approximately one half times the same area as said R mark section area.

1. A touch sensitive rectangular panel including a processor comprising: a top surface divided into thirty nine sections; each said sections is uniquely positioned relative to the planar position of each other said sections; each said sections uniquely identified by a mark; wherein the upper left corner section of said panel is identified by a R mark, a section identified by a S mark located such that it shares a common border with the right side of said R mark section, and is contiguous with a section of the top side of said panel, a section identified by a Y mark located such that it shares a common border with the right side of said S mark section, and is contiguous with a section of the top side of said panel, a section identified by a K mark located such that it shares a common border with the right side of said Y mark section, and is contiguous with a section of the top side of said panel, a section identified by a I mark located such that it shares a common border with the right side of said K mark section, and is contiguous with a section of the top side of said panel, a section identified by a L mark located such that it shares a common border with the lowest side of said R mark section, and is contiguous with a section of the left side of said panel, a section identified by a N mark located such that it shares a common border with the lowest side of said L mark section, and is contiguous with a section of the left side of said panel, a section identified by a T mark located such that it shares a common border with the lowest side of said N mark section, and is contiguous with a section of the left side of said panel, said T section further bounding by a bottom section perpendicular to the left side of said panel and a right side composed of a straight line upper section and a curved lower section, said straight line upper section and said curved line lower section approximately equal in length; wherein the upper right corner section of said panel is identified by a J mark, a section identified by a M mark located such that it shares a common border with the lowest side of said J mark section, and is contiguous with a section of the right side of said panel, a section identified by a P mark located such that it shares a common border with the lowest side of said M mark section, and is contiguous with a section of the right side of said panel, a section identified by a E mark located such that it shares a common border with the lowest side of said P mark section, and is contiguous with a section of the right side of said panel, said E section further bounding by a bottom section perpendicular to the right side of said panel, and a left side composed of a straight line upper section and a curved line lower section, said straight line upper section and said curved line lower section approximately equal in length; wherein the lower left corner section of said panel is identified by a Caps mark, a section identified by a O mark located such that it shares a common border with the right side of said Caps mark section, and is contiguous with a section of the bottom side of said panel, a section identified by a U mark located such that it shares a common border with the right side of said O mark section, and is contiguous with a section of the bottom side of said panel, a section identified by a A mark located such that it shares a common border with the right side of said U mark section, and is contiguous with a section of the bottom side of said panel; wherein the lower right corner section of said panel is identified by a 123 mark, a section identified by a B mark located such that it shares a common border with the right side of said L mark section, and shares a common border with the bottom side of said S mark section, a section identified by a Z mark located such that it shares a common border with the right side of said N mark section, and shares a common border with the bottom side of said B mark section, a section identified by a H mark located such that it shares a common border with the left side of said M mark section, and shares a common border with the bottom side of said I mark section, a section identified by a X mark located such that it shares a common border with the left side of said P mark section, and shares a common border with the bottom side of said H mark section, a section identified by a period mark located such that it shares a common border with said straight line section of said left side of said E mark section, and shares a common border with the bottom side of said X mark section, a section identified by a G mark located such that it shares a common border with the left side of said B mark section, and shares a common border with approximately two thirds the left side of the bottom boarder of said Y mark section, a section identified by a C mark located such that it shares a common border with the left side of said G mark section, and shares a common border with approximately one third the right side of the bottom boarder of said Y mark section and with approximately one third the left side of the bottom boarder of said K mark section, a section identified by a W mark located such that it shares a common border with the left side of said C mark section, and shares a common border with approximately two thirds the right side of the bottom boarder of said K mark section, a section identified by a V mark located such that it shares a common border with the left side of said Z mark section, shares a common border with the bottom boarder of said G mark section and shares a common border with approximately one third of the left side of the bottom boarder of said C mark section, a section identified by a F mark located such that it shares a common border with the left side of said V mark section, shares a common border with approximately one third of the right side of the bottom Lowder of said C mark section, and shares a common border with the bottom boarder of said W mark section, a section identified by a D mark located such that it shares a common border with the left side of said period mark section, shares a common border with the bottom boarder of said V mark section and shares a common border with the bottom boarder of said F mark section, a section identified by an apostrophe mark located such that it shares a common border with the bottom boarder of said Z mark section and shares a common border with the top of the right side of the straight line upper section of said T mark section, a section identified by a comma mark located such that it shares a common border with the right side of said apostrophe mark section, and shares a common border with the left side of said D mark section; wherein an oval section located such that said oval's circumference shares a common board with the bottom border of said comma mark section, the bottom border of said D mark section, the bottom border of said D period section, said curved line lower section of the left side of said E mark section, the upper left point of said 123 mark section, the upper border of said A mark section, the upper border of said U mark section, the upper border of said O mark section, the upper right point of said Caps mark section, and said curved line lower section of the right side of said T mark section, a section identified by a quotation mark located such that it shares a common border with the lowest side of said D mark section, and resides within said oval, a section identified by an exclamation mark located such that it shares a common border with the lowest side of said period mark section, and resides within said oval, a section identified by colon mark located such that it shares a common border with said curved line lower section of the left side of said E mark section, and resides within said oval, a section identified by an enya accent mark located such that it shares a common border with the top side of said A mark section, and resides within said oval, a section identified by a Q mark located such that it shares a common border with the top side of said U mark section, and resides within said oval, a section identified by a dash mark located such that it shares a common border with the top side of said O mark section, and resides within said oval, a section identified by semi-colon mark located such that it shares a common border with said curved line lower section of the right side of said T mark section, and resides within said oval, a section identified by a hyphen mark located such that it shares a common border with the lowest side of said comma mark section, and resides within said oval, a section identified by a question mark located such that it shares a common border with the lower side of said quotation mark section, the lower left side of said exclamation mark section, the left side of said colon mark section, the upper left side of said enya accent mark section, the upper side of said Q mark section, the upper right point of said dash section, the right side of said semi-colon section, and the lower right side of said hyphen section.

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46. The information processing apparatus according to claim 43 , further comprising a reference history memory unit that stores a reference history of the keywords in the external display device, wherein the external display device connection control unit notifies the search engine of a keyword selected by the external display device.

43. An information processing apparatus, comprising: a broadcast audio information receiving unit that receives broadcast audio information transmitted from a broadcasting station; a parameter extraction unit that extracts a parameter from voice data contained in the broadcast audio information, the parameter characterizing the voice data; a keyword extraction unit that recognizes the voice data and extracts keywords from the voice data based on the parameter and a keyword extraction database; an information search unit that searches for the extracted keywords using a search engine and acquires a search result for the keywords and articles related to the keywords, the information search unit acquiring from the search engine a search keyword list containing search keywords searched by the search engine and rank information associated with the search keyword list; and an external display device connection control unit that performs connection control with an external display device and outputs the keywords, the search result for the keywords, and the articles related to the keywords to the external display device, wherein the search engine represents a website that provides a keyword search service and a directory search service so that a user uses the search engine to search for information available through Internet.

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7. The method of claim 2 wherein the plurality of instances belonging to the entity class is no more than ten.

2. The method of claim 1 wherein a bag of words model for an entity class is created by: supplying an entity class name and a plurality of instances belonging to the entity class; submitting each instance to a search engine; extracting and storing a plurality of html documents from the search results for each instance; converting each html document to a text document; extracting well formed sentences from the text documents; stemming non stop words in the well formed sentences; constructing an entity network for the entity class comprised of the entity class name, the plurality of instances and stemmed non stop words obtained from well formed sentences containing words in the entity network; assigning a likelihood score to each word in the entity network based on the frequency with which that word appeared in the well formed sentences; creating the bag of words model for the entity class using the words in the entity network along with their respective likelihood scores; and refining the bag of words models for the entity classes by (i) reducing likelihood scores of words shared by bag of words models of various entity classes and (ii) removing proper nouns from the models.

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12. The method in claim 9 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize a message as belonging to the first class.

13. The method in claim 12 wherein the formatting attributes comprises whether a predefined word in the text of the incoming message is capitalized, or whether the text of the incoming message contains a series of predefined punctuation marks.

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11. The system of claim 9 , wherein the executable and operational data are further effective to cause the one or more processors to identify the plurality of first phrases in the ecommerce query by: identifying the plurality of first phrases as longest phrases in the ecommerce query that are also found in a reference dictionary.

9. A system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive a plurality of past computer network queries; identify among the plurality of past computer network queries a plurality sub-queries each including one or more contiguous words from a past query of the plurality of past computer network queries, the plurality of sub-queries including start sub-queries including a starting word of the past query and end sub-queries including an ending word of the past query; for each sub-query of the plurality of sub-queries: generate a start sub-query count equal to a number of occurrences of the each sub query of the plurality of sub-queries as a start sub-query; generate an end sub-query count equal to a number of occurrences of the each sub query of the plurality of sub-queries as an end sub-query; generate a score that: is a function of the start sub-query count and the end sub-query count; decreases with increasing start sub-query count; and increases with increasing end sub-query count; receive an ecommerce query including a plurality of terms; for a plurality of first phrases including contiguous terms of the plurality of terms, determine weights for the plurality of first phrases according to scores of a sub-query of the plurality of sub-queries corresponding to the plurality of first phrases; submit the ecommerce query to a search engine with the weights for the plurality of first phrases; receive results from the search engine; and return the results.

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2. The storage media of claim 1 , wherein obtaining the set of conditional expressions for the conditional expression comprises setting a positive condition and a negative condition for the conditional expression, and identifying, the conditional expressions with corresponding results determinable based on the result of the conditional expression.

1. A non-transitory computer readable storage media having instructions stored thereon that, when executed by a computer, implement a method for optimizing if statements in a program, the method comprising: obtaining for the program, a set of conditional expressions having an inclusion relation; computing a first provisional cost corresponding to the set of conditional expressions being positive, and a second provisional cost corresponding to the set of conditional expressions being negative; determining, for each conditional expression from the set of conditional expressions, a position in the program as a move destination for the conditional expression, using information of the set in which the conditional expression is included; and moving the conditional expression to the movie destination of the conditional expression, wherein moving the conditional expression comprises: in the case where a result of the conditional expression is not cached in a variable, generating an if statement for the conditional expression and caching a result of the conditional expression in a new variable, wherein the if statement is generated in increasing order of a total cost of the first provisional cost and the second provisional cost; and in the case where the result of the conditional expression is cached in the variable, replacing a conditional operator of the conditional expression with a logical operator, prior to caching the result in the new variable.

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15. A system comprising: a microphone to receive an audible speech signal and audible background noise; a signal processor to determine a noise level of the audible background noise; an automatic speech recognition system implemented at least partially in hardware to convert the audible speech signal to a text format; and a dialog system implemented at least partially in hardware to: attempt to interpret the text format of the audible speech signal; determine that the noise level of the audible background noise causes the text format of the audible speech to be uninterpretable; and provide a message that indicates that the audible speech cannot be interpreted because the audible background noise too high; wherein the dialog system is configured to: store noise signals received over time; correlate noise signals received over time and failed attempts to interpret received speech signals; and determine a threshold noise level based on the correlation between noise signals received over time and the failed attempts to interpret received speech signals; and use the threhsold noise level to determine that the speech signal is uninterpretable.

17. The system of claim 15 , wherein the automatic speech recognition module comprises the sound signal processor and the automatic speech recognition module is further configured to receive a noise signal from the microphone and determine a noise level of the audible background noise.

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1. One or more computer-storage media excluding a signal having computer-executable instructions embodied thereon, that when executed, cause a computing device to perform a method of generating a search results page having one or more search results and relevant information associated with a target search result that is based on a user-inputted query, the method comprising: receiving a query in a search box on a search page; based on the query, identifying from a database the target search result that best corresponds to the query and a functional tool corresponding to the target search result that allows a user to directly interact with a webpage associated with the target search result by way of the search results page without the user selecting the target search result, wherein the functional tool and the search box are simultaneously displayed on the search results page, wherein the functional tool includes one or more input boxes that allow for the user to provide input, and wherein once the input that has been provided into the one or more input boxes has been submitted, the user is directed to one or more of, (1) the search results page that has been modified to include responses associated with the input provided into the one or more input boxes, or (2) a response page that is associated with the target search result; and generating the search results page that includes the target search result and the functional tool.

10. The media of claim 1 , wherein the database includes a plurality of queries and associated search results, and wherein the search results are tagged according to whether each of the search results is an official webpage.

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1. A method comprising: communicating a first user interface to a seller; receiving unstructured text from the seller via the first user interface, the unstructured text including item information describing an item for sale on a network-based marketplace; analyzing the item information to generate structured text, the structured text signifying at least one semantic of the unstructured text, the structured text including application information, the application information describing a plurality of applications including a first application, the first application including a vehicle including the item as a first component, the application information including a first application information describing the first application, the analyzing being performed by the use of at least one processor; storing the application information describing the plurality of applications and the item information in a listing in a database; publishing the listing on the network-based marketplace to sell the item via the network-based marketplace; receiving a query from a buyer including keywords that describe the item and a second application including the item; generating second application information describing the second application responsive to identifying the keywords in the query that describe the second application; retrieving the listing from the database based on matching the keywords in the query that describe the item with the item information included in the listing and based on matching the second application information that was generated from the keywords in the query with the first application information that was stored in the listing; and communicating the listing in a second user interface to the buyer, the second user interface including visually perceptible user interface elements signifying the item and visually perceptible user interface elements signifying the vehicle as compatible with the item.

9. The method of claim 1 , wherein the first application information includes a first set of name-value pairs.

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17. The computer-readable volatile or non-volatile storage medium of claim 14 , wherein the cost of computing the path expression is the weighted sum of the estimated CPU cost and the estimated I/O cost.

18. The computer-readable volatile or non-volatile storage medium of claim 17 , wherein said estimated CPU cost is computed with an input size of data to be queried, a size of the output from the query and a plurality of factors specific to an implementation of the database system.

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17. The method of claim 1 , further comprising generating key phrases in the voice-synthesized responses and sending the key phrases to a thought navigation process that retrieves information on the key phrases.

1. A computer implemented method of conducting commerce, using one or more computers, the method comprising: receiving by one or more computer systems text inputs corresponding to transactions; analyzing by the one or more computer systems the text inputs by executing natural language processing programs; producing by the one or more computers, based on results of analyzing the transactions by the natural language processing programs, added information, searching a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response triggering a facility to present additional information about the key concept; building by a conversational engine running on the one or more computer systems, a conversation based on the transaction requests and key concept, statistically analyzing by the one or more computers the information stored in the database based on the added information; tracking by the one or more computers interactions with the user; storing information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generating in the one or more computers voice-synthesized responses based on the received transaction requests through an avatar; generating additional, voice-synthesized, follow-up responses through the avatar in response to the transactions based on information stored in the database, including the added information regarding the transactions; receiving by the one or more computer systems subsequent text inputs from the user; analyzing in the one or more computers the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take; and causing execution of the determined action.

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42. The method of claim 24 , wherein the network layer comprises a Transport Control Protocol over Internet Protocol (TCP/IP) interface or an Interprocess Communication (IPC) interface.

24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer.

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1. A method for differential dynamic content delivery, the method comprising: providing to a multiplicity of users a presentation including content from a session document; streaming presentation speech to the user including individual speech from at least one user participating in the presentation; converting the presentation speech to text; detecting whether the presentation speech contains simultaneous individual speech from two or more users; and displaying the text if the presentation speech contains simultaneous individual speech from two or more users.

2. The method of claim 1 wherein the presentation speech contains simultaneous individual speech from two or more users, the method includes identifying a period of simultaneous speech, and displaying the text includes displaying presentation text for a presentation period longer than the period of simultaneous speech.

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8. A computer implemented method comprising: accessing a digital document, wherein the digital document relates to one or more topics; generating a list of expert students, wherein the expert students have authored one or more annotations relating to a topic similar to the one or more topics in the digital document; computing a confidence score for each annotation imported by a user accessing the digital document, wherein the confidence score is based on a test score of one or more users who imported the annotation, the test score being an indication of a quality of the annotation; computing a rank based on the confidence score for each annotation by the one or more users relating to the similar topic; and ordering the list of expert students according to the rank, wherein the rank identifies a level of expertise of the expert students; and presenting the ordered list of expert students, where the ordered list comprises a pre-defined number of expert students with a level of expertise meeting a predefined threshold.

9. The method of claim 8 , further comprising regenerating the ordered list of expert students as a new topic in the digital document is viewed, wherein the ordered list is based on an identified context of the new topic.

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1. A method for managing information comprising: generating a first database in a first memory device; storing, by an administrator via a server system, a plurality of predefined questions in the first database, wherein the plurality of predefined questions relate to project information and include at least a first predefined question and a second predefined question; storing, by the administrator, a plurality of predefined answer options related to the project information, wherein each predefined answer option corresponds to one of the plurality of predefined questions; associating, by the administrator, each of the plurality of predefined answer options with a task by pre-defining, within the first database, a task to be performed based on each of the plurality of predefined answer options; associating, by the administrator, a plurality of tools used to complete a task with each task, wherein said plurality of tools includes at least one expert on a task; providing, via a computer, to a user, the plurality of predefined questions and the plurality of predefined answer options; receiving a plurality of answers from the user, wherein the plurality of answers are chosen by the user from the provided plurality of predefined answer options, and wherein at least one answer option associated with the second predefined question is modified based on an answer from the first predefined question from the user, wherein modifying at least one answer option comprises at least one of adding at least one answer option associated with the second predefined question and removing at least one answer option associated with the second predefined question; determining, by the computer, a task and tools based on the plurality of answers provided by the user; creating at least one additional database in a second memory device based on the plurality of predefined answer options; associating the first database with the at least one additional database based on the plurality of answers provided by the user without making a change to at least one source code; populating the at least one additional database with the determined task; and prompting the user to customize the determined task within the at least one additional database, without changing the at least one source code, after the at least one additional database has been populated.

5. The method in accordance with claim 1 further comprising: migrating a plurality of tasks comprising the determined task into the first database; populating the at least one additional database by downloading the plurality of tasks from the first database into the at least one additional database, wherein said populating is performed when the plurality of tasks are migrated into the first database; adding an additional task into the first database; and communicating the additional task to the at least one additional database without additional input from any users and when the additional task is added to the first database.

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17. The method of claim 15 wherein operating the server comprises operating the server to send data reflective of new versions of T&Cs to respective wireless communications devices to present the new versions of T&Cs on the respective wireless devices for acceptance thereof.

15. A wireless communications method for a plurality of mobile wireless communications devices, each mobile wireless communications device including non-transitory memory storing program instructions that when executed by a processor enable receipt of data reflective of terms and conditions (T&Cs) for use of the mobile wireless communications device and enable communication based upon acceptance of the T&Cs in a corresponding version at a time of acceptance for use of the mobile wireless communications device, the method comprising: operating a server comprising non-transitory memory storing program instructions that when executed by a processor cause the server to: store data reflective of the corresponding version of the accepted T&Cs for each of the mobile wireless communications devices; enable review of the corresponding version of the accepted T&Cs for each of the mobile wireless communications devices; and deploy the T&Cs in respective resource deployment packages (RDP) for different languages over at least one wireless network over which the wireless communications devices communicate with the server, wherein each RDP further comprises deployment instructions for the at least one wireless network.

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10. A method for automatically extracting contract data from electronic contracts, comprising: providing templates for inputting document patterns and a list of contract data tags for each of a plurality of contract document types, said document patterns being based on at least one predetermined region of a document, one of said regions including the first line of the document; parsing an electronic contract document, using a processor, to convert the electronic contract document into a contract text document; determining a list of contract document types in the electronic contract by comparing and matching patterns of all known contract document types with the pattern of the contract text document; and extracting contract data for each contract document type on the list.

15. The method as recited in claim 10 , further comprising retrieving a list of contract data tags and extracting contract data accordingly for each contract document type on the list.

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1. A computer-based method of scoring recommendations for potential purchase by a customer, comprising: receiving a recommendation context from a customer; using the recommendation context to identify a plurality of candidate recommendations that match the recommendation context, where each candidate recommendation recommends at least one recommended item; with a computer system, determining a score for each candidate recommendation by subtracting a first expected margin value factor for the recommended item that is based on the candidate recommendation not being displayed from a second expected margin value factor for the recommended item that is based on the candidate recommendation being displayed; and ranking the plurality of candidate recommendations using the score for each candidate recommendation to identify at least a highest ranking candidate recommendation.

5. The method of claim 1 , where the second expected margin value is calculated based at least in part on a relevance measure, a post-recommendation exposure measure and a post-recommendation clarity measure for the candidate recommendation.

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2. The method of claim 1 wherein the user is identified by a session cookie.

1. A method for performing a search operation in a multitenant database environment, the method comprising: providing a graphical user interface on a display of an electronic computing device, wherein the graphical user interface includes a search functionality for searching a database within a multitenant database environment, wherein the multitenant environment includes data for multiple client entities, each identified by a tenant identifier (ID) having one of one or more users associated with the tenant ID, users of each of multiple client identities can only access data identified by a tenant ID associated with the respective client entity, and the multitenant environment is at least a hosted database provided by an entity separate from the client entities, and provides on-demand database service to the client entities; maintaining, for a plurality of users corresponding to one or more tenants of the multitenant environment, a list of most recently used records for a plurality of database object types; providing suggested search results via the graphical user interface in response to a user-generated partial search query input by performing one or more anticipated searches based on the user-generated partial search query, wherein the suggested search results are derived from database objects that match the user-generated partial search query input and include database records of multiple object types that have been recently edited by a user generating the user-generated partial search query input by utilizing the list of most recently used records corresponding to the user, the suggested search results being grouped by database object type, and further wherein the suggested search results also include content from one or more real-time feeds comprising at least one social media feed within the multitenant environment of at least one other user from the same client entity as the user; refining the suggested search results in response to subsequent user-generated search query input by performing one or more subsequent anticipated searches based on the subsequent user-generated search query input, the refined suggested search results also based on multiple object types that have been recently edited by a user generating the subsequent user-generated search query input by utilizing the list of most recently used records corresponding to the user, the suggested search results being grouped by database object type, and further wherein the suggested search results also include content from one or more real-time feeds comprising at least one social media feed within the multitenant environment of at least one other user from the same client entity as the user; and providing search results in the graphical user interface based on the user-generated search query input and/or a user selection from the suggested search results.

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3. The method according to claim 1 , further comprising using at least the optimized mixed membership model to determine a clustering of data objects.

4. The method according to claim 3 , further comprising clustering the plurality of data objects based on at least relational data of one heterogeneous relation matrix.

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9. The computerized text classifier system of claim 7 , wherein the statistical engine is further configured to receive real-time feedback to adapt the statistical information provided to one or more learning nodes of the set of learning nodes.

11. The computerized text classifier system of claim 9 , wherein the real-time feedback comprises a reply to the suggested action, the suggested action comprising the response or a link to a web-resource.

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3. The method of claim 1 , wherein building the classifier comprises generating a plurality of clusters, each of the plurality of clusters comprising at least one partial set of words, each of the at least one partial set of words including a set of words from the beginning of the speech recognition result to the end of question part of the speech recognition result.

4. The method of claim 3 , wherein in response to receiving the recognition-stage speech recognition result incrementally in a word by word manner as an input, the classifier calculates a similarity between the input and the plurality of clusters and returns the corresponding end of question part for the recognition-stage speech recognition result based the similarity between the input and any of the plurality of clusters being less than a predetermined threshold.

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1. An information processing device comprising: an input unit to which voice data is input; a text data generating unit generating text data, based on the voice data input to the input unit; an analyzing unit analyzing voiceprint data of the voice data input to the input unit; and an erasing unit erasing the voice data from which the text data has been generated by the text data generating unit, in accordance with a result of the analysis carried out by the analyzing unit.

4. The information processing system of claim 1 , wherein the erasing unit varies the period of time from the analysis carried out by the analyzing unit to the erasing, between a voice data of the registered user and a voice data of a person other than the registered user.

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24. A system that is connected to a network, where a first web page is available on the network so that the first web page can be viewed over the network using a web browser program executing on a client computer connected to the network, where the first web page is widely available to client computers having access to the network, where the first web page includes content created by a first author, and where the system is configured to carry out operations comprising: (a) determining that a second web page includes a reference to the content created by the first author, where the second web page is available to client computers having access to the network and is an independent web page that is not part of the first web page, and where the second web page includes content created by a second author; (b) determining that a third web page includes a reference to the content created by the first author, where the third web page is available to client computers having access to the network and is an independent web page that is not part of the first web page, and where the third web page includes content created by a third author; (c) after determining that the second web page includes a reference to the content created by the first author, and after determining that the third web page includes a reference to the content created by the first author, receiving a communication over the network when a client computer has requested the first web page, where the client computer is operated by a user; and (d) responding to the communication by transferring at least a portion of the first web page over the network to the client computer, where the first web page includes a representation of the second and third web pages, and the content created by the first author, and where the representation of the second and third web pages is automatically included in the first web page, meaning that the representation is included without requiring the user operating the client computer to be previously aware that the second web page includes the reference to the content created by the first author, and without requiring the user operating the client computer to be previously aware that the third web page includes the reference to the content created by the first author.

25. The system of claim 24 , where the representation appears in the first web page at the client computer as a display object that serves as a representation for both the second web page and the third web page, the display object having an appearance that signifies multiple references to the content created by the first author.

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14. One or more tangible computer-readable storage media comprising instructions that are executable by a computer to: designate a linguistic service having a particular functional property available through a platform responsive to an application program interface (API) call specifying the particular functional property of the linguistic service, without the API call specifying the linguistic service; and broker communication between the application and the linguistic service without the application directly communicating with the linguistic service.

19. One or more tangible computer-readable storage media as described in claim 14 , wherein the linguistic service is independent from the application.

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18. A mediation computer according to claim 6 wherein the processing circuitry is configured to determine the candidate tag by determining the candidate tag based upon a semantic meaning of utterances within the conversation.

6. A mediation computer configured to generate maintenance reports, the mediation computer comprising: an interface configured to receive user input, in relation to a computer-mediated conversation between users of at least two computers, relating to maintenance of a system; and processing circuitry configured to determine a candidate tag representative of a semantic context of the user input, wherein the processing circuitry is configured to determine the candidate tag by: (i) determining the candidate tag in an instance in which the user input relates to an initial message of the conversation based upon a domain within which the user input is provided, wherein the domain is selected from the group consisting of design, manufacturing and maintenance operations of the system within which the user input is provided; and (ii) determining the candidate tag in an instance in which the user input relates to an ongoing conversation based upon the semantic context of the conversation including a mapping of words in the conversation to concepts in the respective semantic context or matching of elements in the conversation to elements within a corpus of other conversations, wherein the interface is further configured to provide an indication of the candidate tag to the user and to receive a response from the user regarding validity of the candidate tag with respect to the semantic context of the user input, and wherein the processing circuitry is further configured to cause the maintenance report to be generated and stored with the maintenance report modified to include the computer-mediated conversation and the candidate tag associated therewith.

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12. A system for collecting metadata for a first multimedia data element, comprising: a plurality of computational cores configured to receive the first multimedia data element, each core having properties to be independent of each other core, each said core generates responsive to the first multimedia data element a first signature element and a second signature element, said first signature element is a robust signature; a storage unit for storing at least one second multimedia data element, metadata associated with said second multimedia data element, and at least one of a first signature and a second signature associated with said second multimedia data element, said first signature is a robust signature; and a comparison unit coupled to said plurality of computational cores and to said storage unit, wherein the comparison unit is configured to compare signatures of multimedia data elements for the purpose of determining matches between multimedia data elements; wherein responsive to receiving the first multimedia data element said plurality of computational cores generate a respective first signature of said first multimedia element and a second signature of said first multimedia data element, for the purpose of determining a match with said at least one second multimedia data element stored in said storage and associating at least a subset of metadata associated with said at least one second multimedia data element with said first multimedia data element.

13. The system of claim 12 , wherein said multimedia data element is selected from the group consisting of an image, graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, images of signals, a combinations thereof, and portions thereof.

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1. A method comprising, by one or more computer systems of a social-networking system: receiving, from a client device of a first user of the social-networking system, a search query comprising one or more characters inputted by the first user, the one or more characters being received as the first user inputs the one or more characters at the client device into a user interface of the social-networking system; identifying one or more entities associated with the social-networking system matching the one or more characters of the search query; ranking each of the identified entities matching the search query based on a calculated likelihood that the user will interact with a search result corresponding to the identified entity, wherein the calculated likelihood that the user will interact with the search result corresponding to the identified entity is based at least in part on a historical behavior of the user in selecting one or more prior search results related to the identified entity; boosting one or more ranks of one or more of the identified entities matching the search query based on: one or more business objectives of the social-networking system, wherein at least one of the business objectives comprises encouraging the first user to interact with the identified entity based on a level of social relevance of the identified entity with respect to the first user; and a level of the user's interaction with one or more features of the social-networking system associated with the identified entity, wherein the boosting is designed to increase the level of the user's interaction with the one or more features of the social-networking system associated with the identified entity; and sending, to the client device of the first user and in response to the received search query, one or more search results for presentation to the user as the user inputs the one or more characters at the client device into the user interface, each search result corresponding to one of the identified entities, the search results being presented according to the ranking and boosting of the corresponding identified entities, the presentation of the search results to the user enabling the user to select one or more of the search results to interact with.

12. The method of claim 1 , wherein boosting one or more ranks of one or more of the identified entities comprises boosting the ranking of the one or more of the identified entities to bring one or more features associated with the identified entities to the user's attention.

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4. The system of claim 1 , wherein the system functions as an accessory user interface or projection device for the standard game states of an electronic game.

1. A system for gaming comprising: a video display; player sensors including a directional microphone for detecting input from players proximate to the system; a natural language processor configured to identify words detected from players via a player sensor; a circumstances inventory (CI) engine that includes a game states queue and a player attributes queue, and wherein the CI engine is programmed with instructions to collect current game states and player states for the game states queue and the player attributes queue, respectively; a social intelligence engine including an emotional state interpreter configured to process information from the player sensors and natural language processor about respective players and pass processed information to the player attributes queue based on information corresponding to each identified player; an artificial intelligence engine suitable for receiving data from and configured to be in communication with the CI engine, the data representing standard game states from an electronic game table, wherein the artificial intelligence engine is configured with instructions to: associate the standard game states with possible virtual assistant reactions, and save the associations as knowledge; and create virtual assistant interactions in real time by selecting a virtual assistant reaction; and a virtual assistant projector configured with instructions to display an automated virtual assistant on the video display based on at least one of the virtual assistant interactions, and wherein the virtual assistant is projected based on the selected virtual assistant reaction, and wherein the virtual assistant projector is further configured with possible virtual assistant emotions for the virtual assistant reaction, and wherein the artificial intelligence engine is configured with instructions to: create associations between game states and virtual assistant emotions, select an emotion for the virtual assistant projector to display for the virtual assistant interactions, and provide conversational dialogue using the selected emotion.

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5. The method of claim 4 , wherein evaluating the at least one EL expression comprises: analyzing the set of tag library usage information; identifying, based on the analyzing, one or more program points in the set of program points associated with the at least one EL expression; identifying, based on the map, at least one variable name in set of variable names accessed by the at least one EL expression at the one or more program points; and generating, based on identifying the at least one variable name, the Java expression based on the at least one variable and the set of values of the at least one variable name, the Java expression comprising at least a Java method call for obtaining the set of values of the at least one variable name.

4. The method of claim 1 , wherein evaluating the at least one EL expression comprises generating the at least one Java expression based on the set of tag library usage information and the map.

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1. A method of managing network usage, the method comprising: defining a set of linguistic patterns, where each linguistic pattern is associated with a condition that is to be monitored; capturing network packets containing content during transmission; decapsulating the captured network packets; identifying linguistic patterns in the content of the captured network packets; scoring captured network packets based on similarity of at least one of the identified linguistic patterns to one or more of the defined set of linguistic patterns; and when a packet that is scored above a specified threshold value is identified, implementing at least one responsive action.

4. The method of claim 1 wherein the capturing comprises actively capturing.

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6. A computer program product stored in a computer readable storage medium, comprising computer program code that, when executed by an information handling system, causes the information handling system to perform actions comprising: creating a structured resource from a corpus of documents, wherein the structured resource comprises a plurality of first member entities and a plurality of second member entities; identifying a plurality of sentences in the corpus of documents that each comprises one of the plurality of first member entities and one of the plurality of second member entities; constructing a natural language context, for each of the plurality of sentences, based on a sentence context of the first member entity included in the sentence relative to the second member entity included in the sentence, wherein the constructing produces a plurality of natural language contexts that are different from each other; generating a plurality of database queries based on the plurality of natural language contexts, wherein each of the plurality of database queries are different from each other; creating a plurality of pattern maps that each comprise one of the plurality of natural language contexts and one of the plurality of database queries corresponding to the natural language context; in response to matching a question to each of the plurality of natural language contexts, assigning a priority score to each of the plurality of pattern maps based upon a relative amount at which their corresponding one of the plurality of natural language contexts have been matched against one or more previous questions; and invoking each of the plurality of database queries corresponding to the each of the plurality of the patterns maps in an order based on the corresponding priority score assigned to each of the plurality of the pattern maps, until a data resource match is reached.

9. The computer program product of claim 6 wherein the information handling system performs additional actions comprising: determining that the structured resource comprises a plurality of entity-cluster centroids; generating a synthetic event for each one of the plurality of entity-cluster centroids, resulting in a plurality of synthetic events; selecting one of the plurality of synthetic events; and linking a plurality of synthetic event relations to the selected synthetic event.

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10. A system, comprising: (a) an input operable to receive a behavior-descriptive input stream; determining, by a meta-parser that performs a preliminary parse on one or more portions of the input stream, a structure of the input stream for either subsequent selection of a parser or subsequent creation of a parser, the meta-parser outputting the input stream and an indication of whether the meta-parser was able to successfully parse the input stream, the input stream output from the meta-parser being passed to the parser; (b) a lexical analyzer operable to analyze the behavior-descriptive input stream to provide a tokenized equivalent; (c) the parser operable to syntactically parse the tokenized equivalent to provide a parser output; (d) a semantic encoder and processor operable to semantically analyze the parser output to provide an indication of at least one of a behavior and type of behavior described by the input stream; and (e) a semantic evaluator operable, based on the indication, to select an appropriate response.

13. The system of claim 10 , wherein the input stream is potentially defined by a plurality of grammars and further comprising: (f) a rules engine operable to determine that at least a portion of the input stream does not correspond to a known grammar and, in response, create a grammar defining the at least a portion of the input stream; and (g) a parser generator operable to create a parser operable to apply syntactical rules associated with the grammar; and (h) a semantic encoder generator operable to create a semantic encoder operable to apply semantical rules associated with the grammar.

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29. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: processor executable instructions embodied on a computer readable media, memory, or processor readable device, or a combination thereof, said instructions comprising: instructions to receive user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; instructions for accomplishing at least one of an interactive workspace or a user suggestion or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; instructions to display or output, or both, an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project.

40. The system of claim 29 further comprising that at least one workspace comprises at least a subset of related system capabilities and a representation of at least a subset of at least one user specification, stage of understanding, or model, or a combination thereof.

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1. A system for categorizing items, the system comprising: a data store that stores item information for items; a computing device operating a network-based service and in communication with the data store, wherein the network-based service is operative to: receive a request for at least one category recommendation for an item of interest, the request including item information regarding the item of interest, wherein the item of interest is an item offered for sale using the network-based service; and submit the received item information to a categorization service; and the categorization service in communication with the network-based service, wherein the categorization service is operative to: generate an item vector from the item information according to a vector space model; compare the item vector to at least one category vector representing a description of an item category according to the vector space model, wherein the item category is maintained by the network-based service and associated with a plurality of items; determine the item category to be the at least one category recommendation if a similarity between the item vector and the at least one category vector is greater than a threshold value; and distribute the identified at least one category recommendation so as to enable a human reviewer to electronically select an item category from the at least one category recommendation for assignment to the item of interest.

4. The system of claim 1 , wherein the item information comprises at least one of a flat file, an XML file, and item information directly input from a user.

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3. The method of claim 1 , further including performing one of: calculating an average size of the calculated sets of similarity element matches, and using the average size to determine the resolution level for storing the input similarity elements.

4. The method of claim 3 , further including defining a set of similarity element matches to include similarity element matches with a similar angle, where an angle of a similarity element match is the difference between a position of the similarity element match in the repository data and a position of the similarity element match in the input data, and where two angles are considered as similar if a difference of the two angles does not exceed a predefined threshold.

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3. The method of claim 1 , further comprising: receiving a further user input specifying a scope of invocation of checkpoints, the scope specifying that checkpoints are to be invoked only for a particular user of multiple users using the computer program; and invoking checkpoints according to the specified scope.

1. A method, comprising: receiving a computer program having a plurality of checkpoints, each checkpoint being assigned to at least one of a plurality of checkpoint groups, each checkpoint and each checkpoint group being identified by a group identifier, each checkpoint in the plurality of checkpoints including an assertion statement that tests whether a specified condition is true, and a breakpoint that halts execution of the computer program, the assertion statement including an argument to activate logging with programmer-controlled granularity, the argument being used to determine whether to update a log entry when the assertion statement fails, the assignment of each checkpoint to a checkpoint group being specified in a statement defining the respective checkpoint, the statement including the group identifier identifying the checkpoint group, and each checkpoint group including a respective identification; associating each checkpoint group with one of a plurality of activation variants that indicates a behavior based on a result of the assertion statement, wherein checkpoint groups associated with an activation variant behave in accordance with the activation variant; selectively activating at least one checkpoint group based on the respective identification; indicating the activation variant of the plurality of activation variants, in accordance with the at least one checkpoint group is to behave; and executing the computer program based on selectively activating the at least one checkpoint group and indicating the activation variant, wherein only the at least one checkpoint group of the computer program is executed, and a remainder of the plurality of checkpoint groups, if any, is not executed.

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33. The computer program product of claim 30 , wherein the one or more profiles are arranged hierarchically.

30. A computer program product having a non-transitory computer-readable medium having computer program instructions recorded thereon for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the computer program instruction comprising instructions for: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user based on the feedback received, where for each of the search results that receive feedback, a plurality of feedback values are determined and are used to construct a model that includes profile weights computed from the feedback values; modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made by combining the internal weights with the profile weights in the constructed model, wherein the internal weights are modified according to a function of the internal weights used for scoring search criteria and of the profile weights; generating implicit search criteria for the user based on the one or more profiles; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user.

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15. A method for making an integrated circuit (IC), comprising: forming a material layer on a substrate; patterning a first photoresist layer on the material layer using a first photomask; etching the material layer through openings of the first photoresist layer; removing the first photoresist layer; patterning a second photoresist layer on the material layer using a second photomask and a third photomask; etching the material layer through openings of the second photoresist layer; and removing the second photoresist layer.

19. The method of claim 15 , wherein the material layer is a hard mask layer and the method further includes etching the substrate through openings of the hard mask layer after the etching the material layer through openings of the first photoresist layer and the etching the material layer through openings of the second photoresist layer.

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13. The system of claim 12 , wherein determining a significance of the link based on a child and parent associated with the link comprises: determining a first probability that a child associated with the link arises in a context of a parent associated with the link; determining a second probability that the child associated with the link arises independently of the parent associated with the link; and determining the link rating by dividing the first probability by the second count probability.

12. The system of claim 8 , wherein determining a link rating for the link based on the expected count for the link and the significance comprises: determining a significance of the link based on a child and parent associated with the link; and determining the link rating by multiplying the significance of the link by the expected count for the link.

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10. A non-transitory computer readable storage medium as in claim 9 wherein the further information is selected from an additional filter condition.

11. A non-transitory computer readable storage medium as in claim 10 wherein the structured association type in combination with the further information, amount to a join condition.

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12. The method of claim 1 , wherein the search results are displayed on the client system of the user in an order based on relative proximities of the embeddings for the respective visual-media items to the embeddings for one or more of the n-grams of the search query.

1. A method comprising, by one or more computing systems: identifying a shared visual concept in two or more visual-media items, wherein each visual-media item comprises one or more images, each image comprising one or more visual features, and wherein each visual-media item comprises one or more visual concepts, the shared visual concept being identified based on one or more shared visual features in the respective images of the visual-media items; extracting, for each of the visual-media items, one or more n-grams from one or more communications associated with the visual-media item; generating, in a d-dimensional space, an embedding for each of the visual-media items, wherein a location of the embedding for the visual-media item is based on the one or more visual concepts included in the visual-media item; generating, in the d-dimensional space, an embedding for each of the extracted n-grams, wherein a location of the embedding for the n-gram is based on a frequency of occurrence of the n-gram in the communications associated with the visual-media items; associating with the shared visual concept, one or more of the extracted n-grams that have embeddings within a threshold area of the embeddings for the identified visual-media items; populating a visual-concept index that indexes visual concepts with their respective associated n-grams; receiving, from a client system of a user, a search query comprising one or more n-grams; determining, based on the visual-concept index, one or more visual concepts associated with the n-grams of the search query; and sending, to the client system of the user, one or more search results comprising visual-media items in which the determined visual concepts are identified.

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2. An automated data entry and display system as claimed in claim 1, wherein display control keys are mounted on the wand and is electrically connected to the display means, each such key being adapted to generate and transmit to the display means electrical control signals and wherein said display means are adapted to receive said wand key signals and be responsive thereto.

1. An automated data entry and display system comprising: a. a wand having means for photo-electrically reading printed and typed alpha-numeric characters on a surface and for outputting electrical signals corresponding to the photo-electrically read characters; b. optical character recognition means electrically connected to the wand for receiving and recognizing electrical signals from the wand corresponding to any printed and typed alpha-numeric characters and for generating and transmitting electrical signals corresponding to the received recognized electrical signals; c. alpha-numeric keyboard electrical input means for transmitting electrical signals corresponding to designated alpha-numeric characters; and d. display means electrically connected to the alpha-numeric keyboard electrical input means and to the optical character recognition means for receiving electrical signals transmitted from said keyboard means and said optical character recognition means and for displaying for viewing designated symbols in response thereto.

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22. The client system of claim 21 , further including geographical information associated with the user, and the ranking function includes a geographical component.

21. The client system of claim 17 , further including a ranking function, and the instructions for presenting are configured to display a plurality of field suggestions in accordance with the ranking function.