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AIPD_nlp_sentence_dataset_v2

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1. A device, comprising: a memory to store instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving video media content, wherein the video media content comprises images, audio content, and closed captioning of text from the audio content; detecting an occurrence of a textual phrase in the closed captioning of the video media content as a detected occurrence; selecting an audio segment from the audio content of the media content as a selected audio segment, wherein the selected audio segment corresponds to the detected occurrence of the textual phrase in the closed captioning; selecting from a speech recognition library an audio pronunciation associated with the textual phrase, wherein the speech recognition library comprises a group of identified audio segments, wherein the group of identified audio segments comprises a baseline audio pronunciation and collected audio pronunciations of the textual phrase; comparing the selected audio segment with the group of identified audio segments from the speech recognition library; determining if an audio pronunciation of the selected audio segment differs from the baseline audio pronunciation from the speech recognition library; responsive to determining that the audio pronunciation of the selected audio segment differs from the baseline audio pronunciation, generating a phonetic transcription of the audio pronunciation of the selected audio segment; and adding the phonetic transcription and the textual phrase to the group of identified audio segments in the speech recognition library to populate the collected audio pronunciations of the selected audio segment.

1. A device, comprising: a memory to store instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving video media content, wherein the video media content comprises images, audio content, and closed captioning of text from the audio content; detecting an occurrence of a textual phrase in the closed captioning of the video media content as a detected occurrence; selecting an audio segment from the audio content of the media content as a selected audio segment, wherein the selected audio segment corresponds to the detected occurrence of the textual phrase in the closed captioning; selecting from a speech recognition library an audio pronunciation associated with the textual phrase, wherein the speech recognition library comprises a group of identified audio segments, wherein the group of identified audio segments comprises a baseline audio pronunciation and collected audio pronunciations of the textual phrase; comparing the selected audio segment with the group of identified audio segments from the speech recognition library; determining if an audio pronunciation of the selected audio segment differs from the baseline audio pronunciation from the speech recognition library; responsive to determining that the audio pronunciation of the selected audio segment differs from the baseline audio pronunciation, generating a phonetic transcription of the audio pronunciation of the selected audio segment; and adding the phonetic transcription and the textual phrase to the group of identified audio segments in the speech recognition library to populate the collected audio pronunciations of the selected audio segment. 3. The device as defined in claim 1 , wherein the operations further comprise: detecting a second occurrence of the textual phrase in the closed captioning as a detected second occurrence; selecting a second audio segment from the audio of the media content as a selected second audio segment, wherein the selected second audio segment corresponds to the detected second occurrence of the textual phrase; comparing the selected second audio segment with the baseline audio pronunciation; generating a group of audio difference metrics by comparing the selected audio segment and the selected second audio segment to the baseline audio pronunciation; identifying by way of the group of audio difference metrics if the selected audio segment and the selected second audio segment have similar audio pronunciations, wherein the similar audio pronunciations differ from the baseline audio pronunciation; and identifying a representative audio segment of the selected audio segment and the selected second audio segment, wherein the phonetic transcription of the audio pronunciation of the selected audio segment and the selected second audio segment are generated from the representative audio segment.

1. An apparatus for dynamic Web page performance scoring, comprising: a tool for accessing Web page structure in connection with the real time loading, display, and operation of a Web page; said tool comprising a module for analyzing a plurality of Web page metrics related to said Web page while said Web page is running; said tool comprising a module for receiving information about said Web page that is generated while analyzing said Web page metrics; said tool comprising a heuristic mechanism for calculating a performance subscore for each of said metrics; and said tool comprising a module for combining said performance subscores for said metrics to produce at least one interpretable Web page performance score.

1. An apparatus for dynamic Web page performance scoring, comprising: a tool for accessing Web page structure in connection with the real time loading, display, and operation of a Web page; said tool comprising a module for analyzing a plurality of Web page metrics related to said Web page while said Web page is running; said tool comprising a module for receiving information about said Web page that is generated while analyzing said Web page metrics; said tool comprising a heuristic mechanism for calculating a performance subscore for each of said metrics; and said tool comprising a module for combining said performance subscores for said metrics to produce at least one interpretable Web page performance score. 5. The apparatus of claim 1 , said tool comprising a module for measuring relative performance of Web pages interactively as they are being developed.

1. A method comprising: receiving, from a user device, a request for content submitted by a particular user, the request for content being associated with a location and including one or more keywords; determining, by one or more processors, one or more entities located proximate to the location associated with the request; determining, by the one or more processors, a prominent entity of the one or more entities located proximate to the location associated with the request; determining, by the one or more processors, one or more categories associated with the prominent entity; evaluating, by the one or more processors, historical search queries submitted by the particular user to determine: one or more interests of the particular user; and one or more additional keywords associated with the particular user; identifying, by the one or more processors, one or more content items responsive to the request based at least in part on the one or more keywords included with the request for content, the one or more categories included with the prominent entity, the one or more interests of the particular user and the one or more additional keywords; and providing, to the user device, the one or more content items responsive to the request for presentation to the particular user, such that the particular user is presented with one or more content items identified based at least in part on one or more keywords included with the request for content, one or more categories associated with a prominent entity of one or more entities determined to be located proximate to a location associated with the request, wherein the one or more interests of the particular user are identified based at least in part on historical search queries submitted by the particular user, and the one or more additional keywords associated with the particular user identified based at least in part on historical search queries submitted by the particular user, wherein the additional keywords are not included in the request for content submitted the particular user.

1. A method comprising: receiving, from a user device, a request for content submitted by a particular user, the request for content being associated with a location and including one or more keywords; determining, by one or more processors, one or more entities located proximate to the location associated with the request; determining, by the one or more processors, a prominent entity of the one or more entities located proximate to the location associated with the request; determining, by the one or more processors, one or more categories associated with the prominent entity; evaluating, by the one or more processors, historical search queries submitted by the particular user to determine: one or more interests of the particular user; and one or more additional keywords associated with the particular user; identifying, by the one or more processors, one or more content items responsive to the request based at least in part on the one or more keywords included with the request for content, the one or more categories included with the prominent entity, the one or more interests of the particular user and the one or more additional keywords; and providing, to the user device, the one or more content items responsive to the request for presentation to the particular user, such that the particular user is presented with one or more content items identified based at least in part on one or more keywords included with the request for content, one or more categories associated with a prominent entity of one or more entities determined to be located proximate to a location associated with the request, wherein the one or more interests of the particular user are identified based at least in part on historical search queries submitted by the particular user, and the one or more additional keywords associated with the particular user identified based at least in part on historical search queries submitted by the particular user, wherein the additional keywords are not included in the request for content submitted the particular user. 5. The method of claim 1 where the location is determined from street addresses in a map-related application.

7. An implantable spine stabilization device comprising: an elongated bone anchor having a distal end and a proximal end and a longitudinal axis; a deflectable post having a distal end and a proximal end and coaxially aligned with the longitudinal axis of the anchor; a joint which secures the distal end of the post to the proximal end of the bone anchor such that the deflectable post may pivot relative to the bone anchor; a tubular extension of the bone anchor which extends over a portion of the deflectable post; and a compliant member disposed between the distal portion of the deflectable post and the tubular extension of the bone anchor whereby the compliant member biases the deflectable post into alignment with the bone anchor with the compliant member being shaped to control deflection of the deflectable post from alignment with the longitudinal axis of the bone anchor.

7. An implantable spine stabilization device comprising: an elongated bone anchor having a distal end and a proximal end and a longitudinal axis; a deflectable post having a distal end and a proximal end and coaxially aligned with the longitudinal axis of the anchor; a joint which secures the distal end of the post to the proximal end of the bone anchor such that the deflectable post may pivot relative to the bone anchor; a tubular extension of the bone anchor which extends over a portion of the deflectable post; and a compliant member disposed between the distal portion of the deflectable post and the tubular extension of the bone anchor whereby the compliant member biases the deflectable post into alignment with the bone anchor with the compliant member being shaped to control deflection of the deflectable post from alignment with the longitudinal axis of the bone anchor. 10. The dynamic pedicle screw of claim 7 , wherein: said tubular extension is associated with a limit surface positioned to contact the deflectable post after a predetermined amount of deflection of the deflectable post away from alignment with the longitudinal axis of the bone anchor; and wherein the compliant member has a cylindrical polymer bushing having an external diameter that mates to the bore of the tubular extension and an internal lumen having a diameter that receives the deflectable post, wherein the cylindrical bushing flares out at an end of the cylindrical polymer bushing furthest from the distal end of the deflectable post.

1. A method, utilizing at least one computing device, comprising: retrieving data definitions defining types of a plurality of business objects stored in enterprise data, the data definitions specify one or more attributes for each of the types of the plurality of business objects; generating, based at least in part on the data definitions, a meta-model of the enterprise data, the meta-model provides semantic information characterizing conceptual meaning to the one or more attributes; using the meta-model of the enterprise data to generate a rule definition that maps the enterprise data to the semantic information; using the rule definition to generate at least one semantic object and at least one semantic relation from the plurality of business objects stored in the enterprise data; and storing the at least one semantic object and the at least one semantic relation in a meta-model semantic network, the meta-model semantic network associating a term to the at least one semantic object.

1. A method, utilizing at least one computing device, comprising: retrieving data definitions defining types of a plurality of business objects stored in enterprise data, the data definitions specify one or more attributes for each of the types of the plurality of business objects; generating, based at least in part on the data definitions, a meta-model of the enterprise data, the meta-model provides semantic information characterizing conceptual meaning to the one or more attributes; using the meta-model of the enterprise data to generate a rule definition that maps the enterprise data to the semantic information; using the rule definition to generate at least one semantic object and at least one semantic relation from the plurality of business objects stored in the enterprise data; and storing the at least one semantic object and the at least one semantic relation in a meta-model semantic network, the meta-model semantic network associating a term to the at least one semantic object. 2. The method of claim 1 , wherein the generating of the meta-model of the enterprise data includes retrieving preexisting data definitions associated with the enterprise data.

9. The keypad of claim 8 , wherein the plurality of alphabetic letters assigned to the one key of the at least one key are displayed on a surface of the one key in an order associated with frequency of use of each of said plurality of alphabetic letters.

9. The keypad of claim 8 , wherein the plurality of alphabetic letters assigned to the one key of the at least one key are displayed on a surface of the one key in an order associated with frequency of use of each of said plurality of alphabetic letters. 10. The keypad of claim 9 , wherein the plurality of alphabetic letters are displayed on the surface of the one key of the at least one key in a descending order with respect to highest frequency of use.

11. A method of traffic sign recognition in a driver assistance system of a motor vehicle driving along a road, wherein the driver assistance system includes a camera, said method comprising the following steps performed in the driver assistance system: a) with the camera, recording image data of at least one image of a vehicle environment outside of the vehicle that includes a main sign and an auxiliary sign associated with the main sign; b) evaluating the image data and thereby recognizing a presence of the main sign and classifying main sign information of the main sign; c) evaluating the image data and thereby recognizing a presence of the auxiliary sign; d) performing pattern recognition on the image data and thereby recognizing and classifying any available pattern information of the auxiliary sign; e) performing text recognition on the image data and thereby reading and interpreting textual information of the auxiliary sign; f) obtaining situational information regarding the motor vehicle, a current operation of the motor vehicle, or a condition of the vehicle environment; g) automatically assessing a relevance of the main sign by comparing the situational information with the interpreted textual information of the auxiliary sign and with any available classified pattern information of the auxiliary sign, and thereby determining whether that the main sign is relevant only when the situational information falls within a scope of the interpreted textual information of the auxiliary sign and the available classified pattern information of the auxiliary sign; and h) in response to the step g) having determined that the main sign is relevant, activating a driver assistance feature of the driver assistance system based on the classified main sign information of the main sign.

11. A method of traffic sign recognition in a driver assistance system of a motor vehicle driving along a road, wherein the driver assistance system includes a camera, said method comprising the following steps performed in the driver assistance system: a) with the camera, recording image data of at least one image of a vehicle environment outside of the vehicle that includes a main sign and an auxiliary sign associated with the main sign; b) evaluating the image data and thereby recognizing a presence of the main sign and classifying main sign information of the main sign; c) evaluating the image data and thereby recognizing a presence of the auxiliary sign; d) performing pattern recognition on the image data and thereby recognizing and classifying any available pattern information of the auxiliary sign; e) performing text recognition on the image data and thereby reading and interpreting textual information of the auxiliary sign; f) obtaining situational information regarding the motor vehicle, a current operation of the motor vehicle, or a condition of the vehicle environment; g) automatically assessing a relevance of the main sign by comparing the situational information with the interpreted textual information of the auxiliary sign and with any available classified pattern information of the auxiliary sign, and thereby determining whether that the main sign is relevant only when the situational information falls within a scope of the interpreted textual information of the auxiliary sign and the available classified pattern information of the auxiliary sign; and h) in response to the step g) having determined that the main sign is relevant, activating a driver assistance feature of the driver assistance system based on the classified main sign information of the main sign. 19. The method according to claim 11 , wherein the situational information comprises at least one of an indication whether a turn signal of the vehicle is activated and a position of a lane of the road in which the vehicle is traveling.

32. The system of claim 30 , wherein adding the new value comprises: identifying a collection of values of a first attribute of a first instance using an identifier of the first instance; and establishing a subset of one or more of the identified values as suitably characterizing the first attribute of the first instance.

32. The system of claim 30 , wherein adding the new value comprises: identifying a collection of values of a first attribute of a first instance using an identifier of the first instance; and establishing a subset of one or more of the identified values as suitably characterizing the first attribute of the first instance. 35. The system of claim 32 , wherein establishing the subset of values as suitable comprises selecting the subset based at least in part on values in the subset meeting a user-specified constraint.

30. A computer-readable medium according to claim 29 further comprising an eighth data field for selecting a vocabulary comprising the plurality of vocabulary words before permitting user selection of the plurality of vocabulary, the plurality of vocabulary words corresponding to the user search topic.

30. A computer-readable medium according to claim 29 further comprising an eighth data field for selecting a vocabulary comprising the plurality of vocabulary words before permitting user selection of the plurality of vocabulary, the plurality of vocabulary words corresponding to the user search topic. 31. A computer-readable medium according to claim 30 wherein the plurality of vocabulary words are based upon words in at least one predetermined document.

15. An apparatus, comprising: a processor of a server; and a computer-readable medium storing a plurality of instructions which, when executed by the processor, cause the processor to perform operations, the operations comprising: generating a training data set comprising a plurality of training flow sets, each training flow set comprising one of a plurality of training feature sets and an associated one of a plurality of class labels, each training feature set and associated class label based on measurements of one of a plurality of training packet flows, the associated class label identifying to which one of a plurality of traffic classes the one of the plurality of training packet flows belongs; training a plurality of binary classifiers using a reduced training data set that is generated from the training data set, each binary classifier associated with one of the plurality of traffic classes, each binary classifier configured to generate an output score based on one the reduced training data set and based on measurements of a packet flow, wherein for each of the plurality of binary classifiers the reduced training data set comprises all training features sets associated with the one of the plurality of traffic classes that are contained in the training data set and training packet flows associated with other traffic classes of the plurality of traffic classes that are uniformly sampled from the training data set; and training a plurality of calibrators using the training data set, wherein each calibrator is associated with one of the plurality of binary classifiers, wherein the training the plurality of calibrators comprises training each of the plurality of calibrators to translate the output score of the associated binary classifier into an estimated class probability value, the estimated class probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator.

15. An apparatus, comprising: a processor of a server; and a computer-readable medium storing a plurality of instructions which, when executed by the processor, cause the processor to perform operations, the operations comprising: generating a training data set comprising a plurality of training flow sets, each training flow set comprising one of a plurality of training feature sets and an associated one of a plurality of class labels, each training feature set and associated class label based on measurements of one of a plurality of training packet flows, the associated class label identifying to which one of a plurality of traffic classes the one of the plurality of training packet flows belongs; training a plurality of binary classifiers using a reduced training data set that is generated from the training data set, each binary classifier associated with one of the plurality of traffic classes, each binary classifier configured to generate an output score based on one the reduced training data set and based on measurements of a packet flow, wherein for each of the plurality of binary classifiers the reduced training data set comprises all training features sets associated with the one of the plurality of traffic classes that are contained in the training data set and training packet flows associated with other traffic classes of the plurality of traffic classes that are uniformly sampled from the training data set; and training a plurality of calibrators using the training data set, wherein each calibrator is associated with one of the plurality of binary classifiers, wherein the training the plurality of calibrators comprises training each of the plurality of calibrators to translate the output score of the associated binary classifier into an estimated class probability value, the estimated class probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator. 19. The apparatus of claim 15 , wherein the training the plurality of binary classifiers further comprises training the plurality of binary classifiers with a maxent algorithm.

1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service.

1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service. 10. The system of claim 1 : wherein the discovery service comprises at least one of a logically centralized discovery service, a private discovery service, and an extension to the security sandbox, and wherein the discovery service is configured to at least one of: provide an application-layer routing between the sandboxed program and the at least one of the networked device and the networked service, and perform a traditional discovery method comprising at least one of a multicast protocol, a unicast protocol, an anycast protocol, a broadcast protocol, a Bonjour® protocol, a Simple Service Discovery Protocol (SSDP), a Local Service Discovery (LSD) uTorrent® protocol, a Service Location Protocol (SLP), a Universal Plug and Play (UPnP) protocol, a Multicast Domain Name System (MDNS) protocol, and a Domain Name System-based Service Discovery (DNS-SD) protocol.

2. A method as in claim 1 , wherein the steps of presenting collectively include operating a simulation engine having a set of state variables, and having a set of rules describing permitted changes in value of those state variables, wherein substantially each collection of possible values for the set of state variables defines a context; and the set of decision models collectively include a set of behavior models, each capable of responding to a query from the simulation engine and capable of generating a response to that query.

2. A method as in claim 1 , wherein the steps of presenting collectively include operating a simulation engine having a set of state variables, and having a set of rules describing permitted changes in value of those state variables, wherein substantially each collection of possible values for the set of state variables defines a context; and the set of decision models collectively include a set of behavior models, each capable of responding to a query from the simulation engine and capable of generating a response to that query. 5. A method as in claim 2 , wherein the simulation engine includes at least one of: a self-learning mode including at least some of those behavior models and software agents having initial values, and reinforcing those behavior models and software agents which are successful according to an evaluator for the simulation engine; a demonstration mode including at least some of those behavior models and software agents demonstrating their learning to an observer; a real-time mode including substantially all of those behavior models and software agents being updated with each change in context; a stochastic mode including introduction of random or pseudorandom values for at least some of those state variables.

18. A machine readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations comprising: based on an analysis of conversation data exchanged between a first user equipment and a second user equipment during a communication session via a communication network, determining, during the communication session, goal data indicative of a goal associated with the first user equipment and the second user equipment; based on data received from a network data store of the communication network, determining task data indicative of a task that is to be performed, to accomplish the goal; verifying that first speech data associated with the conversation data is not being transmitted between the first user equipment and the second user equipment during the communication session; and subsequent to the determining the task data and the verifying, generating second speech data that comprises the task data, adding a network device of the communication network as an additional participant in the communication session, transferring, in parallel to the conversation data exchanged between the first user equipment and the second user equipment during the communication session, the second speech data from the network device to the first user equipment and the second user equipment during the communication session, and facilitating transfer of third speech data between the first communication device and the second communication device subsequent to the transferring the second speech data associated with the task data.

18. A machine readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations comprising: based on an analysis of conversation data exchanged between a first user equipment and a second user equipment during a communication session via a communication network, determining, during the communication session, goal data indicative of a goal associated with the first user equipment and the second user equipment; based on data received from a network data store of the communication network, determining task data indicative of a task that is to be performed, to accomplish the goal; verifying that first speech data associated with the conversation data is not being transmitted between the first user equipment and the second user equipment during the communication session; and subsequent to the determining the task data and the verifying, generating second speech data that comprises the task data, adding a network device of the communication network as an additional participant in the communication session, transferring, in parallel to the conversation data exchanged between the first user equipment and the second user equipment during the communication session, the second speech data from the network device to the first user equipment and the second user equipment during the communication session, and facilitating transfer of third speech data between the first communication device and the second communication device subsequent to the transferring the second speech data associated with the task data. 19. The machine readable storage medium of claim 18 , wherein the communication session is a voice call and the transfer of the task data facilitates a playback of a voice message that comprises the second speech data during the voice call.

1. An Integrated Development Environment (IDE), executing computer instructions in a computer-readable storage medium of a computer system, suitable for use in developing a Virtual User Interface (VUI) application, the IDE running on the computer system and comprising: a development window for graphically constructing a visual layout of a User Inteface (UI) to correspond to a virtual layout of a Virtual User Interface (VUI) generated by an ultrasonic sensing unit externally coupled to the computer system and with its own targeted processor and memory for receiving executable program code compiled from the IDE specific to instructions of the targeted processor; and at least one descriptor that identifies a response of a user interface component in the UI to touchless sensory events applied to a corresponding virtual component in the VUI generated by the ultrasonic sensing unit, a compiler for compiling a source code of the VUI application into at least one code object using imported target processor and memory configurations from the ultrasonic sensing unit; a linker for converting said code object into relocatable code based on the targeted processor and memory of the ultrasonic sensing unit; a code builder for building said relocatable code into an executable code object; and a flashing module for managing a down loading of the executable program code object over a connection into a flash memory of the externally coupled ultrasonic sensing unit associated with the target processor and memory, where the computer system is communicatively coupled to the ultrasonic sensing unit by a wired or wireless connection for developing the VUI on the computer and down loading the executable code object into the ultrasonic sensing unit.

1. An Integrated Development Environment (IDE), executing computer instructions in a computer-readable storage medium of a computer system, suitable for use in developing a Virtual User Interface (VUI) application, the IDE running on the computer system and comprising: a development window for graphically constructing a visual layout of a User Inteface (UI) to correspond to a virtual layout of a Virtual User Interface (VUI) generated by an ultrasonic sensing unit externally coupled to the computer system and with its own targeted processor and memory for receiving executable program code compiled from the IDE specific to instructions of the targeted processor; and at least one descriptor that identifies a response of a user interface component in the UI to touchless sensory events applied to a corresponding virtual component in the VUI generated by the ultrasonic sensing unit, a compiler for compiling a source code of the VUI application into at least one code object using imported target processor and memory configurations from the ultrasonic sensing unit; a linker for converting said code object into relocatable code based on the targeted processor and memory of the ultrasonic sensing unit; a code builder for building said relocatable code into an executable code object; and a flashing module for managing a down loading of the executable program code object over a connection into a flash memory of the externally coupled ultrasonic sensing unit associated with the target processor and memory, where the computer system is communicatively coupled to the ultrasonic sensing unit by a wired or wireless connection for developing the VUI on the computer and down loading the executable code object into the ultrasonic sensing unit. 9. The IDE of claim 1 , where the linker for converting said code object into relocatable code identifies regions of memory targeted by the processor of the ultrasonic sensing unit, and links the relocatable code to those regions of memory including the at least one descriptor; and the code builder for building said relocatable code into an executable code object that accesses the targeted memory of the processor in the external ultrasonic sensing unit and at least one descriptor on the ultrasonic sensing device.

22. The apparatus of claim 1 , wherein said association manager is configured to provide controlled access to said electronic mail message and said one or more elements of data based on one or more access rules.

22. The apparatus of claim 1 , wherein said association manager is configured to provide controlled access to said electronic mail message and said one or more elements of data based on one or more access rules. 23. The apparatus of claim 22 , wherein said one or more access rules are based on one or more user-specific roles.

10. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a browser; and in response to said receiving: generating a comment based on or including the input; marking a body section of a data structure for the electronic document with a tag based on the input, wherein the body section includes content for the body of the electronic markup language document; storing the comment in a comment section of the data structure for the electronic document, wherein said storing comprises storing the input using another tag to identify the comment, wherein the comment section of the data structure is separate from the body section of the data structure; and displaying the body of the electronic markup language document and an action user interface element, wherein the action user interface element is useable to cause the browser to parse the tag and the another tag to determine where the input can be applied to the electronic markup language document.

10. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a browser; and in response to said receiving: generating a comment based on or including the input; marking a body section of a data structure for the electronic document with a tag based on the input, wherein the body section includes content for the body of the electronic markup language document; storing the comment in a comment section of the data structure for the electronic document, wherein said storing comprises storing the input using another tag to identify the comment, wherein the comment section of the data structure is separate from the body section of the data structure; and displaying the body of the electronic markup language document and an action user interface element, wherein the action user interface element is useable to cause the browser to parse the tag and the another tag to determine where the input can be applied to the electronic markup language document. 14. The method of claim 10 , wherein the action user interface element is useable to perform an action to submit a request to view the input apart from the document.

1. A system for information clustering, said system comprising; a central processing unit (CPU) for executing parts; a data accumulation part for accumulating and clustering documents in a document repository, said documents including loosely related clusters between said documents being time sliced so as to define chunks of said documents; a vector space generation part for generating document-keyword vectors, said document-keyword vectors consisting of sparse numeral values depending on presence of keywords in said documents; a dimension reduction part for reducing dimensions of said keywords to create a dimension reduction matrix of said document-keyword matrix; a centroid vector determination part for generating a centroid vector of said cluster, said cluster being retrieved from said document-keyword vector using a principal component in a same line of said dimension reduction matrix, said centroid vectors being defined from keywords and weight of documents within said cluster; and an item repository for storing said centroid vectors together with said keywords and said weights of said centroid vector.

1. A system for information clustering, said system comprising; a central processing unit (CPU) for executing parts; a data accumulation part for accumulating and clustering documents in a document repository, said documents including loosely related clusters between said documents being time sliced so as to define chunks of said documents; a vector space generation part for generating document-keyword vectors, said document-keyword vectors consisting of sparse numeral values depending on presence of keywords in said documents; a dimension reduction part for reducing dimensions of said keywords to create a dimension reduction matrix of said document-keyword matrix; a centroid vector determination part for generating a centroid vector of said cluster, said cluster being retrieved from said document-keyword vector using a principal component in a same line of said dimension reduction matrix, said centroid vectors being defined from keywords and weight of documents within said cluster; and an item repository for storing said centroid vectors together with said keywords and said weights of said centroid vector. 2. The system of claim 1 , wherein said centroid vector determination part retrieves a principal document in said document using said principal component as a first query vector and subsequently retrieves documents defining said clusters using said principal document as a second query vector.

1. A portable navigational apparatus for locating one or more locations of interest within a geographical area, comprising: an input device for entering a proprietary search term uniquely associated with an entity within a district of the geographical area and identifying one or more locations of interest within the geographical area; a processor coupled to the input device for receiving the entered proprietary search term, the processor configured for generating a search query comprising the entered proprietary search term and locational information associated with the navigational apparatus; a communications interface coupled to the processor for communicating with a server via a wireless network, the interface configured for sending the search query to the server, and for receiving a search result from the server, the search result comprising one or more locations for the entity uniquely associated with the proprietary search term that have a relationship with the locational information; an output device coupled to the processor for outputting the one or more locations comprising the search result; and an automatic location identification (“ALI”) device that identifies the current location of the navigational apparatus within the geographic area, the processor coupled to the ALI device for obtaining the current location of the navigational apparatus from the ALI device at the time of sending the search query, the locational information in the search query comprising at least one of the current location and a projected location of the navigational apparatus based at least in part on the current location.

1. A portable navigational apparatus for locating one or more locations of interest within a geographical area, comprising: an input device for entering a proprietary search term uniquely associated with an entity within a district of the geographical area and identifying one or more locations of interest within the geographical area; a processor coupled to the input device for receiving the entered proprietary search term, the processor configured for generating a search query comprising the entered proprietary search term and locational information associated with the navigational apparatus; a communications interface coupled to the processor for communicating with a server via a wireless network, the interface configured for sending the search query to the server, and for receiving a search result from the server, the search result comprising one or more locations for the entity uniquely associated with the proprietary search term that have a relationship with the locational information; an output device coupled to the processor for outputting the one or more locations comprising the search result; and an automatic location identification (“ALI”) device that identifies the current location of the navigational apparatus within the geographic area, the processor coupled to the ALI device for obtaining the current location of the navigational apparatus from the ALI device at the time of sending the search query, the locational information in the search query comprising at least one of the current location and a projected location of the navigational apparatus based at least in part on the current location. 7. The navigational apparatus of claim 1 , wherein the proprietary search term consists of less than three alphanumeric characters.

20. A system for enabling a user to provide criterion-specific feedback for an item, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: provide for display a representation of the item and information regarding the item; and provide a user with the ability to provide feedback for the item, including: enable the user to select an existing response to an existing question or statement regarding at least one existing criterion for the item; enable the user to specify a new response to an existing question or statement regarding the at least one existing criterion for the item; enabling the user to select an add feedback element when the at least one existing criterion does not substantially represent the feedback the user wishes to provide for the item; in response to receiving a selection of the add feedback element, enabling the user to input a new criterion that represents the feedback the user wishes to provide for the item and one or more new values for the new criterion, by enabling the user to input a new question corresponding the new criterion and one or more new responses to the new question, the one or more new responses corresponding to the one or more new values; and aggregate feedback provided by the user with existing feedback for the item, the aggregated feedback able to be subsequently provided for display with the representation of the item and information regarding the item.

20. A system for enabling a user to provide criterion-specific feedback for an item, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: provide for display a representation of the item and information regarding the item; and provide a user with the ability to provide feedback for the item, including: enable the user to select an existing response to an existing question or statement regarding at least one existing criterion for the item; enable the user to specify a new response to an existing question or statement regarding the at least one existing criterion for the item; enabling the user to select an add feedback element when the at least one existing criterion does not substantially represent the feedback the user wishes to provide for the item; in response to receiving a selection of the add feedback element, enabling the user to input a new criterion that represents the feedback the user wishes to provide for the item and one or more new values for the new criterion, by enabling the user to input a new question corresponding the new criterion and one or more new responses to the new question, the one or more new responses corresponding to the one or more new values; and aggregate feedback provided by the user with existing feedback for the item, the aggregated feedback able to be subsequently provided for display with the representation of the item and information regarding the item. 21. A system according to claim 20 , wherein the memory device further includes instructions that, when executed by the processor, cause the processor to: when feedback received from the user includes a new question, provide the ability for the user to specify an affirmative feedback statement corresponding to the new question to be displayed with the representation of the item.

1. A method for presenting a search result in response to a current search term, comprising: determining a pre-established first model corresponding to preselected user information and including historical user search data; identifying a selected historical search term in the historical user search data that corresponds with the current search term; identifying a selected historical selection result in the historical user search data that corresponds with the identified historical search term; determining the search result based upon the identified historical selection result, said determining the search result comprising determining an online recommendation result based upon the identified historical selection result; processing the online recommendation result to generate a generated recommendation result; and presenting the generated recommendation result, wherein said processing comprises: calculating a literal association degree between the online recommendation result and the current search term according to a logistic regression process such that the online recommendation result has the literal association degree that is greater than a preselected third threshold value; calculating a semantic association degree between the online recommendation result and the current search term according to a gradient boost decision tree such that the online recommendation result has the semantic association degree that is greater than a preselected fourth threshold value; or a combination thereof.

1. A method for presenting a search result in response to a current search term, comprising: determining a pre-established first model corresponding to preselected user information and including historical user search data; identifying a selected historical search term in the historical user search data that corresponds with the current search term; identifying a selected historical selection result in the historical user search data that corresponds with the identified historical search term; determining the search result based upon the identified historical selection result, said determining the search result comprising determining an online recommendation result based upon the identified historical selection result; processing the online recommendation result to generate a generated recommendation result; and presenting the generated recommendation result, wherein said processing comprises: calculating a literal association degree between the online recommendation result and the current search term according to a logistic regression process such that the online recommendation result has the literal association degree that is greater than a preselected third threshold value; calculating a semantic association degree between the online recommendation result and the current search term according to a gradient boost decision tree such that the online recommendation result has the semantic association degree that is greater than a preselected fourth threshold value; or a combination thereof. 10. The method of claim 1 , wherein said calculating the semantic association degree comprises calculating the literal association degree according to a gradient boost decision tree model trained by a gradient boost decision tree, wherein the gradient boost decision tree trains the gradient boost decision tree model by using the pre-established first model as training data and taking a click-through rate as an optimization objective.

1. One or more computers comprising: a processor; a memory; wherein the one or more computers are configured to perform operations comprising: storing a respective plurality of category-location relevance scores for each location of a plurality of geographic locations, wherein each category-location relevance score for each location estimates a relevance of a respective category to the location, and wherein a category-location relevance score is based on a plurality of category-entity-location relevance scores for a plurality of entities associated with the category at the location, wherein storing a category-location relevance score for a location comprises storing a plurality of Taylor coefficients for a function at the location, wherein an evaluation of the function for a location provides a category-location relevance score for the category, and wherein an evaluation of the function at a location is determined by evaluating a sub-function for each of the plurality of entities, and wherein an evaluation of the sub-function for an entity provides a category-entity-location relevance score for the entity and the location; determining a first category-location relevance score for a first geographic location that is not one of the plurality of geographic locations, including: selecting a second geographic location in the plurality of geographic locations, and calculating the first category-location relevance score based on a second category-location relevance score for the second geographic location and a physical distance between the first geographic location and the second geographic location; and selecting an item from a plurality of candidate items using the first category location relevance score, wherein each candidate item is associated with a respective category, and wherein selecting the item comprises: ranking the plurality of candidate items using the first category location relevance score, and selecting a highest ranked candidate item.

1. One or more computers comprising: a processor; a memory; wherein the one or more computers are configured to perform operations comprising: storing a respective plurality of category-location relevance scores for each location of a plurality of geographic locations, wherein each category-location relevance score for each location estimates a relevance of a respective category to the location, and wherein a category-location relevance score is based on a plurality of category-entity-location relevance scores for a plurality of entities associated with the category at the location, wherein storing a category-location relevance score for a location comprises storing a plurality of Taylor coefficients for a function at the location, wherein an evaluation of the function for a location provides a category-location relevance score for the category, and wherein an evaluation of the function at a location is determined by evaluating a sub-function for each of the plurality of entities, and wherein an evaluation of the sub-function for an entity provides a category-entity-location relevance score for the entity and the location; determining a first category-location relevance score for a first geographic location that is not one of the plurality of geographic locations, including: selecting a second geographic location in the plurality of geographic locations, and calculating the first category-location relevance score based on a second category-location relevance score for the second geographic location and a physical distance between the first geographic location and the second geographic location; and selecting an item from a plurality of candidate items using the first category location relevance score, wherein each candidate item is associated with a respective category, and wherein selecting the item comprises: ranking the plurality of candidate items using the first category location relevance score, and selecting a highest ranked candidate item. 4. The system of claim 1 , wherein the first geographic location is associated with a user, and wherein the second geographic location is a prominent geographic location.

14. A method comprising: converting a multi-way theta join query on MapReduce into a multi-way interval join query on MapReduce, wherein the multi-way theta join query comprises one or more join conditions involving one or more arithmetic operators on one or more items of real-valued data; optimizing the multi-way interval join query to reduce the number of conditions in the multi-way interval join query that include the one or more arithmetic operators; executing the optimized multi-way interval join query via MapReduce to generate an output; and processing the output to generate a solution in response to the optimized multi-way theta join query; wherein said converting, said optimizing, said executing, and said processing are carried out by at least one computing device.

14. A method comprising: converting a multi-way theta join query on MapReduce into a multi-way interval join query on MapReduce, wherein the multi-way theta join query comprises one or more join conditions involving one or more arithmetic operators on one or more items of real-valued data; optimizing the multi-way interval join query to reduce the number of conditions in the multi-way interval join query that include the one or more arithmetic operators; executing the optimized multi-way interval join query via MapReduce to generate an output; and processing the output to generate a solution in response to the optimized multi-way theta join query; wherein said converting, said optimizing, said executing, and said processing are carried out by at least one computing device. 15. The method of claim 14 , wherein said converting further comprises converting one or more items of data associated with the multi-way theta join query to one or more items of interval data.

1. A computer-implemented method for pairing a new document to a document from a plurality of documents in a document repository, comprising: for each of the new document and the plurality of documents in the document repository, generating a vector uniquely associated with a document of the new document and the plurality of documents, wherein: the vector comprises a number of elements equal to a number of terms of interest; and for each term of interest, an associated element value of the vector is assigned as zero if the term of interest does not occur in the document and one if the term does occur in the document; for each document from the plurality of documents, determining a similarity between the vector for the new document and the vector for the document from the plurality of documents comprising calculating a cosine measurement of similarity between the vector for the new document and the vector for the document from the plurality of documents; if it is determined that the similarity between the vector for the new document and the vector for a document from the plurality of documents is greater than or equal to a threshold value then: selecting the document from the plurality of documents; generating a merged document by merging the new document with the document from the plurality of documents in response to the document from the plurality of documents being selected, wherein the merging comprises combining at least a portion of the new document with at least a portion of the selected document into the merged document; removing the selected document from the document repository and adding the merged document to the document repository; and generating a new vector for the merged document; and if it is determined that the similarity is less than the threshold value then adding the new document to the document repository without merging the new document.

1. A computer-implemented method for pairing a new document to a document from a plurality of documents in a document repository, comprising: for each of the new document and the plurality of documents in the document repository, generating a vector uniquely associated with a document of the new document and the plurality of documents, wherein: the vector comprises a number of elements equal to a number of terms of interest; and for each term of interest, an associated element value of the vector is assigned as zero if the term of interest does not occur in the document and one if the term does occur in the document; for each document from the plurality of documents, determining a similarity between the vector for the new document and the vector for the document from the plurality of documents comprising calculating a cosine measurement of similarity between the vector for the new document and the vector for the document from the plurality of documents; if it is determined that the similarity between the vector for the new document and the vector for a document from the plurality of documents is greater than or equal to a threshold value then: selecting the document from the plurality of documents; generating a merged document by merging the new document with the document from the plurality of documents in response to the document from the plurality of documents being selected, wherein the merging comprises combining at least a portion of the new document with at least a portion of the selected document into the merged document; removing the selected document from the document repository and adding the merged document to the document repository; and generating a new vector for the merged document; and if it is determined that the similarity is less than the threshold value then adding the new document to the document repository without merging the new document. 14. The computer-implemented method of claim 1 , wherein the associated element value for each term of interest is weighted based on a position of the term of interest in the document.

1. A method for placing a call over a communications network, the call being placed through a set of feature modules in the network, each feature module being independent and communicating with other feature modules through featureless internal calls through the communications network, the method comprising the steps of: receiving a request from a customer to place a call over the network; determining which features are associated with the customer's request and routing an internal call to a module representing a first feature; routing subsequent internal calls to additional feature modules representing features associated with the customer's request; and routing an internal call from a last feature module to a destination customer, wherein a path of internal calls from the requesting customer includes all features associated with the requesting customer's request.

1. A method for placing a call over a communications network, the call being placed through a set of feature modules in the network, each feature module being independent and communicating with other feature modules through featureless internal calls through the communications network, the method comprising the steps of: receiving a request from a customer to place a call over the network; determining which features are associated with the customer's request and routing an internal call to a module representing a first feature; routing subsequent internal calls to additional feature modules representing features associated with the customer's request; and routing an internal call from a last feature module to a destination customer, wherein a path of internal calls from the requesting customer includes all features associated with the requesting customer's request. 18. The method of claim 1, wherein at least one of the features allows the requesting customer to provide dialed digits via voice input.

17. The computer-readable storage device of claim 15 , further comprising instructions for modifying the plurality of predetermined indices based on seasonal information.

17. The computer-readable storage device of claim 15 , further comprising instructions for modifying the plurality of predetermined indices based on seasonal information. 18. The computer-readable storage device of claim 17 , wherein the seasonal information modifies at least one of a weighting factor or a term association within the second search index.

25. A system for filtering objectionable words comprising: a closed caption analyzer executable by at least one processor and configured to identify a specified text in a closed caption text stream based on a comparison of each word in the closed caption text stream to at least one filter list; a closed caption audiotizer executable by the at least one processor and configured to generate an audio equivalent of the specified text by converting the specified text to a phonetic representation associated with at least one energy value; and an audio stream analyzer executable by the at least one processor and configured to match a portion of an audio signal with the specified text by comparing the at least one energy value of the audio equivalent with an energy of a comparative form of the audio signal involving a total energy of a speech slice and energy of one or more frequency bands of the speech slice, the audio stream analyzer further configured to filter the portion of the audio signal.

25. A system for filtering objectionable words comprising: a closed caption analyzer executable by at least one processor and configured to identify a specified text in a closed caption text stream based on a comparison of each word in the closed caption text stream to at least one filter list; a closed caption audiotizer executable by the at least one processor and configured to generate an audio equivalent of the specified text by converting the specified text to a phonetic representation associated with at least one energy value; and an audio stream analyzer executable by the at least one processor and configured to match a portion of an audio signal with the specified text by comparing the at least one energy value of the audio equivalent with an energy of a comparative form of the audio signal involving a total energy of a speech slice and energy of one or more frequency bands of the speech slice, the audio stream analyzer further configured to filter the portion of the audio signal. 32. The system of claim 25 , wherein identifying the specified text in the closed caption text stream includes determining whether the specified text is objectionable based on a context of use.

2. A networked computer system comprising: a plurality of nodes coupled to each other via a plurality of networks, each of the plurality of networks comprising a communication path between at least two of the plurality of nodes, each of the plurality of nodes comprising at least one processor and memory, the plurality of nodes comprising a distributed database with a first node including first data in the distributed database and a second node including second data in the distributed database and a third node; a network monitor that monitors characteristics of the plurality of networks and generates a log of the characteristics of the plurality of networks; first and second of the plurality of networks that provide alternative network connections between the third node and the first node; and a query optimizer executing on the at least one processor of the third node, wherein the query optimizer logs historical information for queries that indicates past network selection when executing each of the queries, wherein the query optimizer takes network choice into consideration when executing a database query to the first and second nodes in the distributed database that retrieves the first data and the second data in the distributed database by considering the characteristics of the plurality of networks between the first, second and third nodes logged by the network monitor and by considering the past network selection in selecting at least one of the plurality of networks for executing the query, wherein the query optimizer selects one of the first and second networks for executing the query based on the historical information that includes which of the first and second networks were used during at least one previous execution of the query and based on information in the log of the characteristics of the plurality of networks that indicates characteristics of the first and second networks.

2. A networked computer system comprising: a plurality of nodes coupled to each other via a plurality of networks, each of the plurality of networks comprising a communication path between at least two of the plurality of nodes, each of the plurality of nodes comprising at least one processor and memory, the plurality of nodes comprising a distributed database with a first node including first data in the distributed database and a second node including second data in the distributed database and a third node; a network monitor that monitors characteristics of the plurality of networks and generates a log of the characteristics of the plurality of networks; first and second of the plurality of networks that provide alternative network connections between the third node and the first node; and a query optimizer executing on the at least one processor of the third node, wherein the query optimizer logs historical information for queries that indicates past network selection when executing each of the queries, wherein the query optimizer takes network choice into consideration when executing a database query to the first and second nodes in the distributed database that retrieves the first data and the second data in the distributed database by considering the characteristics of the plurality of networks between the first, second and third nodes logged by the network monitor and by considering the past network selection in selecting at least one of the plurality of networks for executing the query, wherein the query optimizer selects one of the first and second networks for executing the query based on the historical information that includes which of the first and second networks were used during at least one previous execution of the query and based on information in the log of the characteristics of the plurality of networks that indicates characteristics of the first and second networks. 3. The networked computer system of claim 2 wherein the query optimizer selects the at least one of the plurality of networks based on at least one parameter in the query that specifies which network to select when executing the query.

24. A matching service system of a matching service, comprising: a number of communications ports which provide communications with a plurality of end user devices, the end user devices logically associable with a plurality of end user client accounts of the matching service, each end user client account of the plurality of end user client accounts logically associable with a respective end user client of the matching service; at least one nontransitory processor-readable medium that stores at least one of processor executable instructions or data; and at least one processor communicatively coupled to the communications ports and the at least one nontransitory processor-readable medium, and that: monitors communications with the plurality of end user devices; receives indications that respective pairs of the end user clients are no longer participating in the matching service, each end user client identified as one end user client in a pair of end user clients based at least in part on the monitoring of the communications with the plurality of end user devices; designates each of the end user clients in a pair of end user clients for which an indication is received as a successfully paired end user client; for each successfully paired end user client of the matching service, populates a successfully paired end user clients database with information for each successfully paired end user client; monitors communications with the end user devices for a reappearance of any of the successfully paired end user clients; and for each of the successfully paired end user clients in the successfully paired end user clients database that reappear, culls the information for at least the successfully paired end user client that reappears from the successfully paired end user clients database.

24. A matching service system of a matching service, comprising: a number of communications ports which provide communications with a plurality of end user devices, the end user devices logically associable with a plurality of end user client accounts of the matching service, each end user client account of the plurality of end user client accounts logically associable with a respective end user client of the matching service; at least one nontransitory processor-readable medium that stores at least one of processor executable instructions or data; and at least one processor communicatively coupled to the communications ports and the at least one nontransitory processor-readable medium, and that: monitors communications with the plurality of end user devices; receives indications that respective pairs of the end user clients are no longer participating in the matching service, each end user client identified as one end user client in a pair of end user clients based at least in part on the monitoring of the communications with the plurality of end user devices; designates each of the end user clients in a pair of end user clients for which an indication is received as a successfully paired end user client; for each successfully paired end user client of the matching service, populates a successfully paired end user clients database with information for each successfully paired end user client; monitors communications with the end user devices for a reappearance of any of the successfully paired end user clients; and for each of the successfully paired end user clients in the successfully paired end user clients database that reappear, culls the information for at least the successfully paired end user client that reappears from the successfully paired end user clients database. 26. The matching service system of claim 24 wherein the at least one processor monitors communications for a reappearance of any of: a combination of a given name and a surname provided by the successfully paired end user client, a screen name employed by the successfully paired end user client, credit card number, phone number, government issued identification number, and driver's license number.

7. A computer system for implementing a just-in-time compiler, comprising: a virtual machine configured to execute instructions in an intermediate language; an optimizing static compiler adapted for runtime use with the virtual machine; a plurality of high-level code templates in a high-level programming language, wherein the high-level programming language is designed for compilation to the intermediate language, and wherein each high-level code template selected from the plurality of high-level code templates represents an instruction in the intermediate language; and a software development environment configured to: compile the plurality of high-level code templates to native code to obtain a plurality of optimized native code templates prior to runtime; mark a constant in an optimized native code template selected from the plurality of optimized native code templates with an annotation, wherein the annotation indicates that the constant requires modification by the just-in-time compiler at runtime; and implement the just-in-time compiler using the plurality of optimized native code templates, wherein the just-in-time compiler is configured to substitute a copy of an optimized native code template selected from the plurality of optimized native code templates when a corresponding instruction in the intermediate language is encountered at runtime.

7. A computer system for implementing a just-in-time compiler, comprising: a virtual machine configured to execute instructions in an intermediate language; an optimizing static compiler adapted for runtime use with the virtual machine; a plurality of high-level code templates in a high-level programming language, wherein the high-level programming language is designed for compilation to the intermediate language, and wherein each high-level code template selected from the plurality of high-level code templates represents an instruction in the intermediate language; and a software development environment configured to: compile the plurality of high-level code templates to native code to obtain a plurality of optimized native code templates prior to runtime; mark a constant in an optimized native code template selected from the plurality of optimized native code templates with an annotation, wherein the annotation indicates that the constant requires modification by the just-in-time compiler at runtime; and implement the just-in-time compiler using the plurality of optimized native code templates, wherein the just-in-time compiler is configured to substitute a copy of an optimized native code template selected from the plurality of optimized native code templates when a corresponding instruction in the intermediate language is encountered at runtime. 11. The computer system of claim 7 , wherein the plurality of optimized native code templates comprises different versions of templates for resolved classes and unresolved classes.

9. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving unstructured textual data; parsing the unstructured textual data into a plurality of sections including a first section and a second section that is a different section in the unstructured textual data than the first section; for each section in the plurality of sections: identifying one or more keywords in data for the section in the plurality of sections; determining one or more patterns that match the section using the identified one or more keywords; and identifying one or more intelligence types that correspond to the section using the determined one or more patterns; associating, for a first intelligence type from the identified one or more intelligence types for the first section, the data for the first section from the unstructured textual data with the first intelligence type; associating, for a second intelligence type from the identified one or more intelligence types for the second section, the data for the second section from the unstructured textual data with the second intelligence type, wherein the second intelligence type is a different intelligence type than the first intelligence type; determining a rule for a third party that indicates that the third party should receive data associated with a particular intelligence type of the one or more intelligence types; determining that the first intelligence type is the particular intelligence type; and providing the data for the first section to a system of the third party.

9. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving unstructured textual data; parsing the unstructured textual data into a plurality of sections including a first section and a second section that is a different section in the unstructured textual data than the first section; for each section in the plurality of sections: identifying one or more keywords in data for the section in the plurality of sections; determining one or more patterns that match the section using the identified one or more keywords; and identifying one or more intelligence types that correspond to the section using the determined one or more patterns; associating, for a first intelligence type from the identified one or more intelligence types for the first section, the data for the first section from the unstructured textual data with the first intelligence type; associating, for a second intelligence type from the identified one or more intelligence types for the second section, the data for the second section from the unstructured textual data with the second intelligence type, wherein the second intelligence type is a different intelligence type than the first intelligence type; determining a rule for a third party that indicates that the third party should receive data associated with a particular intelligence type of the one or more intelligence types; determining that the first intelligence type is the particular intelligence type; and providing the data for the first section to a system of the third party. 15. The computer storage medium of claim 9 , wherein associating, for the first intelligence type, the data for the first section from the unstructured textual data with the first intelligence type comprises storing, in a database, at least one new record specific to the first intelligence type that comprises the data for the first section.

1. A method for executing database queries, comprising: receiving a database query for execution by a database system, the database system configured to process database queries using a first processing unit including one or more central processing units (CPUs) and a second processing unit including one or more single instruction multiple thread (SIMT) based processing units; generating, by the database system, an intermediate executable representation including code for processing the database query, the processing performed by executing operators representing portions of computations for processing the database query; selecting, by the database system, a target processing unit for executing an operator of the database query based on factors comprising a data type of values stored in a column processed by the query; responsive to selection of the second processing unit for executing the operator of the database query: generating native code from the intermediate executable representation, wherein the native code is optimized for execution on the second processing unit; compiling the native code to executable code; and executing the executable code by the database system using the second processing unit; and sending the result of execution of the query.

1. A method for executing database queries, comprising: receiving a database query for execution by a database system, the database system configured to process database queries using a first processing unit including one or more central processing units (CPUs) and a second processing unit including one or more single instruction multiple thread (SIMT) based processing units; generating, by the database system, an intermediate executable representation including code for processing the database query, the processing performed by executing operators representing portions of computations for processing the database query; selecting, by the database system, a target processing unit for executing an operator of the database query based on factors comprising a data type of values stored in a column processed by the query; responsive to selection of the second processing unit for executing the operator of the database query: generating native code from the intermediate executable representation, wherein the native code is optimized for execution on the second processing unit; compiling the native code to executable code; and executing the executable code by the database system using the second processing unit; and sending the result of execution of the query. 14. The method of claim 1 , further comprising: sending the operator of the database query to both the first processing unit and the second processing unit; and receiving a result of execution of the operator from the processing unit that finishes first.

12. A computer system, relating to creating and maintaining, in at least one database available to a population of users, on a database server computer, information about a plurality of database of subjects, comprising: a) at least one computer processor structured and arranged to associate with each database subject of such plurality of database subjects at least one plurality of natural-language tags potentially descriptive of such each database subject according to an involved subset of such population of database users; said at least one plurality of natural language tags comprising other user chosen and/or other user provided natural language terms potentially descriptive of a subject or subjects of said database; b) at least one computer processor structured and arranged to assess, from input from at least one particular database user, at least one measure of descriptive relevance of each of such at least one plurality of natural-language tags to such each database subject according to each particular database user of such involved subset of such population of database users; c) at least one computer processor structured and arranged to associatively index, in such at least one database, such respective particular database users, such respective natural-language tags, such respective measures of relevance, and such respective database subjects; and d) accumulating and storing such respective measures of relevance.

12. A computer system, relating to creating and maintaining, in at least one database available to a population of users, on a database server computer, information about a plurality of database of subjects, comprising: a) at least one computer processor structured and arranged to associate with each database subject of such plurality of database subjects at least one plurality of natural-language tags potentially descriptive of such each database subject according to an involved subset of such population of database users; said at least one plurality of natural language tags comprising other user chosen and/or other user provided natural language terms potentially descriptive of a subject or subjects of said database; b) at least one computer processor structured and arranged to assess, from input from at least one particular database user, at least one measure of descriptive relevance of each of such at least one plurality of natural-language tags to such each database subject according to each particular database user of such involved subset of such population of database users; c) at least one computer processor structured and arranged to associatively index, in such at least one database, such respective particular database users, such respective natural-language tags, such respective measures of relevance, and such respective database subjects; and d) accumulating and storing such respective measures of relevance. 16. The method according to claim 12 , wherein said other users comprise other member users.

17. The method for correcting errors in an audio transcription of claim 12 , further comprising: providing feedback from the step of editing to the step of generating a transcription.

17. The method for correcting errors in an audio transcription of claim 12 , further comprising: providing feedback from the step of editing to the step of generating a transcription. 18. The method for correcting errors in an audio transcription of claim 17 , further comprising: changing the step of generating a transcription in response to feedback from the step of editing.

2. The method of claim 1 , wherein establishing of the communication service channel comprises at least one of: establishing a chatting service channel between the transmitter-side terminal and the receiver-side terminal; establishing a voice communication service channel between the transmitter-side terminal and the receiver-side terminal; and establishing a video communication service channel between the transmitter-side terminal and the receiver-side terminal.

2. The method of claim 1 , wherein establishing of the communication service channel comprises at least one of: establishing a chatting service channel between the transmitter-side terminal and the receiver-side terminal; establishing a voice communication service channel between the transmitter-side terminal and the receiver-side terminal; and establishing a video communication service channel between the transmitter-side terminal and the receiver-side terminal. 3. The method of claim 2 , further comprising: transmitting a voice signal in the first language collected by the transmitter-side terminal to the receiver-side terminal.

22. A system, comprising: one or more processors; and memory storing instructions, the instructions, when executed by the one or more processors, cause the processors to perform operations comprising: receiving a user request, the user request including at least a speech input and seeks an informational answer or performance of a task, wherein: the user request is associated with a detected failure to provide a satisfactory response to the user request; and one or more crowd sourcing information sources relevant to the user request are queried in response to detecting the failure to provide a satisfactory response to the user request; and generating a response to the user request based on the one or more answers obtained from querying the one or more crowd sourcing information sources.

22. A system, comprising: one or more processors; and memory storing instructions, the instructions, when executed by the one or more processors, cause the processors to perform operations comprising: receiving a user request, the user request including at least a speech input and seeks an informational answer or performance of a task, wherein: the user request is associated with a detected failure to provide a satisfactory response to the user request; and one or more crowd sourcing information sources relevant to the user request are queried in response to detecting the failure to provide a satisfactory response to the user request; and generating a response to the user request based on the one or more answers obtained from querying the one or more crowd sourcing information sources. 27. The system of claim 22 , wherein the operations further comprise: presenting a remedial response to the user request, wherein the remedial response is presented upon failing to obtain any answer from at least one of the one or more crowd sourcing information sources.

24. A program product, comprising: (a) a program configured to perform a method of displaying on a computer display a source code file including an ordered arrangement of a plurality of object definitions that define a plurality of multimedia objects, the method comprising: (1) displaying at least a portion of the plurality of object definitions in first representations on the computer display; and (2) in response to user input, selectively displaying on the computer display, in place of the first representation of a selected object definition, an inlined multimedia representation of the selected object definition disposed at a relative location of the selected object definition in the ordered arrangement; and (b) a signal bearing media bearing the program.

24. A program product, comprising: (a) a program configured to perform a method of displaying on a computer display a source code file including an ordered arrangement of a plurality of object definitions that define a plurality of multimedia objects, the method comprising: (1) displaying at least a portion of the plurality of object definitions in first representations on the computer display; and (2) in response to user input, selectively displaying on the computer display, in place of the first representation of a selected object definition, an inlined multimedia representation of the selected object definition disposed at a relative location of the selected object definition in the ordered arrangement; and (b) a signal bearing media bearing the program. 25. The program product of claim 24, wherein the signal bearing media comprises a recordable type media.

1. A method for generating a biased layout for making an integrated circuit, comprising: (a) identifying a nominal layout defined by one or more cells, each cell having one or more transistors having transistor gate features with a nominal gate length; (b) identifying an annotated layout, the annotated layout itself provides information for identifying gate-length biasing of one or more of the transistor gate features in one or more cells of the nominal layout; and (c) producing a biased layout by modifying the nominal layout using the information provided by the annotated layout, such that the biasing modifies a gate length of those transistor gate features identified by the information of the annotated layout, the method implemented by a processor executing a program.

1. A method for generating a biased layout for making an integrated circuit, comprising: (a) identifying a nominal layout defined by one or more cells, each cell having one or more transistors having transistor gate features with a nominal gate length; (b) identifying an annotated layout, the annotated layout itself provides information for identifying gate-length biasing of one or more of the transistor gate features in one or more cells of the nominal layout; and (c) producing a biased layout by modifying the nominal layout using the information provided by the annotated layout, such that the biasing modifies a gate length of those transistor gate features identified by the information of the annotated layout, the method implemented by a processor executing a program. 3. The method of claim 1 , wherein the annotated layout provides information indicating selection of at least two gate length sizes that are different than the nominal gate length.

1. A phase angle based magnetic ink character recognition (MICR) system, comprising: a segmentation system for segmenting inputted MICR data into sets of temporal data for different inputted characters; a Fourier system for generating a set of phase angle components from the temporal data for each segmented character, wherein the set of phase angle components comprises a plurality of harmonics; a phase angle difference calculation system for calculating a phase angle difference between adjacent harmonics of the plurality of harmonics to generate a set of phase angle differences; and a matching system for comparing the set of phase angle differences with each of a set of reference waveforms to determine an identity of the inputted character.

1. A phase angle based magnetic ink character recognition (MICR) system, comprising: a segmentation system for segmenting inputted MICR data into sets of temporal data for different inputted characters; a Fourier system for generating a set of phase angle components from the temporal data for each segmented character, wherein the set of phase angle components comprises a plurality of harmonics; a phase angle difference calculation system for calculating a phase angle difference between adjacent harmonics of the plurality of harmonics to generate a set of phase angle differences; and a matching system for comparing the set of phase angle differences with each of a set of reference waveforms to determine an identity of the inputted character. 3. The phase angle MICR system of claim 1 , wherein the matching system includes a reference waveform for each character in a character set.

16. An electronic device configured to perform a method comprising: receiving a swipe gesture from an initial touch location on a touch-sensitive display of an electronic device; determining touch attributes for the swipe gesture, the touch attributes comprising a touch location of the swipe gesture; performing a first lock function when the swipe gesture progresses to a first touch location on the touch-sensitive display that is beyond a first threshold from the initial touch location, wherein the first lock function locks a first set of functionalities of the electronic device; and performing a second lock function when the swipe gesture progresses to a second touch location on the touch-sensitive display that is beyond a second threshold from the initial touch location, wherein the second lock function locks a second, different set of functionalities of the electronic device and the second threshold is beyond the first threshold.

16. An electronic device configured to perform a method comprising: receiving a swipe gesture from an initial touch location on a touch-sensitive display of an electronic device; determining touch attributes for the swipe gesture, the touch attributes comprising a touch location of the swipe gesture; performing a first lock function when the swipe gesture progresses to a first touch location on the touch-sensitive display that is beyond a first threshold from the initial touch location, wherein the first lock function locks a first set of functionalities of the electronic device; and performing a second lock function when the swipe gesture progresses to a second touch location on the touch-sensitive display that is beyond a second threshold from the initial touch location, wherein the second lock function locks a second, different set of functionalities of the electronic device and the second threshold is beyond the first threshold. 29. The electronic device of claim 16 , wherein the method further comprises presenting a lock function indicator on the display if at least one stored swipe gesture is detected.

4. The method of claim 1 , wherein at least some of the interactions comprise providing a keyboard input to the target device.

4. The method of claim 1 , wherein at least some of the interactions comprise providing a keyboard input to the target device. 6. The method of claim 4 , wherein the keyboard input comprises a mechanical-pneumatic force exerted on buttons of the target device.

1. A method, comprising: scanning, by a computing apparatus, a set of messages of a user to identify a plurality of addresses, wherein the user is associated with a plurality of messaging accounts including a first messaging account; identifying, by the computing apparatus, names of persons at the addresses to generate a plurality of profiles for the persons, each profile of the plurality of profiles comprising a name of a respective person, and at least one address for the respective person; making a determination that the user is composing a first message using the first messaging account; and computing, by the computing apparatus, scores of the persons using data in the plurality of profiles to determine relevancy of the persons to the user, wherein the scores are based at least in part on the determination that the user is composing the first message using the first messaging account, and wherein the computing the scores comprises applying a time-decay factor to each message of the set of messages.

1. A method, comprising: scanning, by a computing apparatus, a set of messages of a user to identify a plurality of addresses, wherein the user is associated with a plurality of messaging accounts including a first messaging account; identifying, by the computing apparatus, names of persons at the addresses to generate a plurality of profiles for the persons, each profile of the plurality of profiles comprising a name of a respective person, and at least one address for the respective person; making a determination that the user is composing a first message using the first messaging account; and computing, by the computing apparatus, scores of the persons using data in the plurality of profiles to determine relevancy of the persons to the user, wherein the scores are based at least in part on the determination that the user is composing the first message using the first messaging account, and wherein the computing the scores comprises applying a time-decay factor to each message of the set of messages. 4. The method of claim 1 , further comprising: in response to an incomplete input in an address field, identifying a set of persons in the plurality of profiles that matches the incomplete input; presenting to the user, in an order determined by the scores, one or more suggestions to complete the incomplete input based on the set of persons; and in response to the user selecting a suggestion from the one or more suggestions, replacing, by the computing apparatus, the incomplete input with an address corresponding to the suggestion selected by the user.

12. The computer-readable storage device of claim 11 , wherein the video signal includes an audio portion.

12. The computer-readable storage device of claim 11 , wherein the video signal includes an audio portion. 14. The computer-readable storage device of claim 12 , wherein outputting the video signal further comprises: generating translated speech in the target language from the translated information; and embedding the translated speech in the audio portion of the video signal.

1. A method comprising: providing a user device with a first search result including one or more item listings in response to a first query received from the user device, each item listing including a plurality of keywords and being associated with a sale format; tracking a plurality of transactions performed on the one or more item listings via the user device; assigning, using one or more processors, for each transaction, a first numerical value to one or more keywords included in a selected item listing and a second numerical value to one or more keywords included in non-selected item listings, the first numerical value being determined based upon the sale format associated with the selected item listing, the assigning including determining the first numerical value based at least in part on whether the sale format associated with the selected item listing is a fixed price sale or a non-fixed price sale; and building a desirability index using one or more numerical values including the first and second numerical values, the desirability index including a desirability value for each keyword, the desirability value being determined based on one or more first numerical values assigned to the keyword, and the desirability value indicating an accumulative frequency of a corresponding keyword being selected throughout the plurality of transactions; wherein the desirability index is accessed to sort item listings in a second search result identified in response to a second query.

1. A method comprising: providing a user device with a first search result including one or more item listings in response to a first query received from the user device, each item listing including a plurality of keywords and being associated with a sale format; tracking a plurality of transactions performed on the one or more item listings via the user device; assigning, using one or more processors, for each transaction, a first numerical value to one or more keywords included in a selected item listing and a second numerical value to one or more keywords included in non-selected item listings, the first numerical value being determined based upon the sale format associated with the selected item listing, the assigning including determining the first numerical value based at least in part on whether the sale format associated with the selected item listing is a fixed price sale or a non-fixed price sale; and building a desirability index using one or more numerical values including the first and second numerical values, the desirability index including a desirability value for each keyword, the desirability value being determined based on one or more first numerical values assigned to the keyword, and the desirability value indicating an accumulative frequency of a corresponding keyword being selected throughout the plurality of transactions; wherein the desirability index is accessed to sort item listings in a second search result identified in response to a second query. 4. The method of claim 1 , wherein each item listing is further associated with a remaining listing period and wherein the first numerical value is determined based upon the remaining listing period associated with the selected item listing.

23. An apparatus comprising: at a camera of a mobile device, means for capturing an image of a menu listing menu items available for selection at a point of interest that is identifiable by a location context identifier; means for displaying the captured image of said menu in a camera view of said mobile device; means for parsing particular text in the displayed image to identify a particular menu item selected from among said displayed menu items based upon a user-input detected by the mobile device; means for associating a location of said mobile device and said particular parsed text with a previously captured image of said particular menu item as presented to a customer, wherein associating said location and said particular parsed text with said previously captured image includes transmitting said location context identifier and said particular parsed text to a remote server; and means for receiving from said remote server at least one annotation that includes information about the particular menu item, wherein said at least one annotation is superimposed in a portion of said camera view including said captured image of said particular menu item.

23. An apparatus comprising: at a camera of a mobile device, means for capturing an image of a menu listing menu items available for selection at a point of interest that is identifiable by a location context identifier; means for displaying the captured image of said menu in a camera view of said mobile device; means for parsing particular text in the displayed image to identify a particular menu item selected from among said displayed menu items based upon a user-input detected by the mobile device; means for associating a location of said mobile device and said particular parsed text with a previously captured image of said particular menu item as presented to a customer, wherein associating said location and said particular parsed text with said previously captured image includes transmitting said location context identifier and said particular parsed text to a remote server; and means for receiving from said remote server at least one annotation that includes information about the particular menu item, wherein said at least one annotation is superimposed in a portion of said camera view including said captured image of said particular menu item. 24. The apparatus of claim 23 , wherein said means for associating said location of said mobile device and said particular parsed text with said previously captured image further comprises: means for transmitting said particular parsed text and said location context identifier to the remote server; and means for receiving said previously captured image in response to transmitting said particular parsed text and said location context identifier.

1. A computer-implemented method, comprising: obtaining an initial attribute whitelist, the initial attribute whitelist including one or more initial attributes; processing a first collection of documents, wherein each of the documents has content to be displayed and an underlying structure that defines how the content is to be displayed, to identify a plurality of pairings of candidate attributes with candidate values in the documents, wherein each candidate attribute and each candidate value is content found in the content to be displayed; grouping the candidate attributes into a plurality of groups according to both a particular document in the first collection in which each candidate attribute was identified and the underlying structure in the particular document in the first collection in which each candidate attribute was identified; calculating a score for each unique attribute in the candidate attributes, where the score reflects a number of groups containing both the unique attribute and an attribute on the initial attribute whitelist; generating an expanded attribute whitelist, the expanded attribute whitelist including the initial attributes and each unique attribute having a respective score that satisfies a threshold; and using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values.

1. A computer-implemented method, comprising: obtaining an initial attribute whitelist, the initial attribute whitelist including one or more initial attributes; processing a first collection of documents, wherein each of the documents has content to be displayed and an underlying structure that defines how the content is to be displayed, to identify a plurality of pairings of candidate attributes with candidate values in the documents, wherein each candidate attribute and each candidate value is content found in the content to be displayed; grouping the candidate attributes into a plurality of groups according to both a particular document in the first collection in which each candidate attribute was identified and the underlying structure in the particular document in the first collection in which each candidate attribute was identified; calculating a score for each unique attribute in the candidate attributes, where the score reflects a number of groups containing both the unique attribute and an attribute on the initial attribute whitelist; generating an expanded attribute whitelist, the expanded attribute whitelist including the initial attributes and each unique attribute having a respective score that satisfies a threshold; and using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values. 3. The method of claim 1 , where using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values comprises: identifying a plurality of pairings of candidate attributes with candidate values from a second collection of documents, the pairings of candidate attributes with candidate values identified according to a respective structure of one or more of the documents in the second collection; grouping the pairings of candidate attributes with candidate values according to both a particular document in the second collection in which each pairing of candidate attributes with candidate values was identified and the underlying structure in the particular document in the second collection; and determining whether a particular pairing of a candidate attribute with a candidate value identified in the documents of the second collection of documents is in a group with a threshold number of pairings of candidate attributes with candidate values that have an attribute on the expanded attribute whitelist, and if so, including the particular pairing of a candidate attribute with a candidate value in the plurality of valid pairings of candidate attributes with candidate values.

14. A data entry device having at least one output unit and a virtual input unit having a plurality of virtual key regions configured to: associate a group of symbols with each of a single virtual key region from the plurality of virtual key regions; assign to each finger of a user having a group of fingers a single symbol from the group of symbols; an optical sensor positioned remote from the virtual key region to identify a virtual key region about to be actuated by the user to define a candidate key region; identify and detect with the optical sensor a most probable finger that is about to actuate the candidate key region; determine the most probable symbol based on the identity of the most probable finger and the candidate key region; display via the output unit the group of symbols associated with the candidate key region; apply a visually-perceptible emphasis to the most probable symbol to differentiate it from the display of the other symbols in the group of symbols; display via the output unit a visually-perceptible representation of the group of fingers; and apply a visually-perceptible emphasis to the most probable finger to differentiate it from other fingers in the group of fingers.

14. A data entry device having at least one output unit and a virtual input unit having a plurality of virtual key regions configured to: associate a group of symbols with each of a single virtual key region from the plurality of virtual key regions; assign to each finger of a user having a group of fingers a single symbol from the group of symbols; an optical sensor positioned remote from the virtual key region to identify a virtual key region about to be actuated by the user to define a candidate key region; identify and detect with the optical sensor a most probable finger that is about to actuate the candidate key region; determine the most probable symbol based on the identity of the most probable finger and the candidate key region; display via the output unit the group of symbols associated with the candidate key region; apply a visually-perceptible emphasis to the most probable symbol to differentiate it from the display of the other symbols in the group of symbols; display via the output unit a visually-perceptible representation of the group of fingers; and apply a visually-perceptible emphasis to the most probable finger to differentiate it from other fingers in the group of fingers. 18. The device of claim 14 wherein the group of fingers includes fingers of a left hand, fingers or a right hand, fingers of both a left hand and a right hand.

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

13. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions for: receiving, over a network from a computing device, a first request for search suggestions related to a first search query that has been input into a search term entry area displayed by a web browser executing on the computing device; transmitting in response to the first request, over the network to the computing device, instructions for the computing device to display a plurality of search suggestions related to the first search query, each of the plurality of search suggestions representing content from a respective search results web page; setting, by the server computer over the network, a cookie with a time stamp for the displaying of the plurality of the search suggestions related to the first search query; transmitting, by the server computer over the network to the computing device, during the transmission of instructions to initially display the plurality of search suggestions related to the first search query, storage instructions that further cause the computing device to store in a memory of the computing device a web page component that is part of at least one respective search results web page prior to initially displaying the respective search results web page; transmitting, by the server computer over the network to the computing device, instructions further causing the computing device to visibly display the search suggestions related to the first search query transmitted by the server computer without visibly displaying the stored web page component during display of the plurality of search suggestions related to the first search query receiving, by the server computer over the network, a second request for a second search suggestion related to a second search query; determining, by the server computer over the network, that the time period associated with the timestamp of the cookie related to the first search query has not elapsed; and transmitting, by the server computer over the network, upon determination that the time period related to the first search query has not elapsed, instructions to the computing device to display a search suggestion related to the second search query prior to initially displaying the respective search results web page and further causing the computing device to store a web page component associated with a search results web page corresponding to the search suggestion related to the second search query. 17. The non-transitory computer readable storage medium of claim 13 further comprising computer program instructions for: transmitting, over the network to the computing device, the search results web page for display by the computing device, the computing device using the stored web page component when displaying the search results web page.

36. The computer-readable medium of claim 35 , wherein determining the first dynamic value data that describes the first dynamic values stored in the first response file and the second dynamic value data that describes the second dynamic values stored in the second response file comprises: analyzing the first temporary file and the second temporary file to determine the first dynamic data and the second dynamic value data.

36. The computer-readable medium of claim 35 , wherein determining the first dynamic value data that describes the first dynamic values stored in the first response file and the second dynamic value data that describes the second dynamic values stored in the second response file comprises: analyzing the first temporary file and the second temporary file to determine the first dynamic data and the second dynamic value data. 37. The computer-readable medium of claim 36 , wherein generating the correlated script using the identified candidate parameters and the base script comprises: generating the correlated script using the first temporary file and the second temporary file.

1. A method for detecting ruby text in a fixed format document, the method comprising: receiving, at a parser, a fixed format document containing one or more lines of text on one or more pages; detecting, by a line detection engine, one or more lines in the fixed format document containing one or more attributes of a ruby line; retaining the one or more lines in the fixed format document containing one or more attributes of a ruby line as ruby line candidates and a line successive to the one or more lines as ruby base line candidates; analyzing, by a document processor, the ruby line candidate for finding one or more ruby texts contained in the ruby line candidate; matching the one or more ruby texts with a corresponding ruby base text in a successive ruby base line candidate for reconstruction in a flow format document; and reconstructing, by a serializer, the fixed format document to a flow format document containing the matched one or more ruby texts and corresponding ruby base text.

1. A method for detecting ruby text in a fixed format document, the method comprising: receiving, at a parser, a fixed format document containing one or more lines of text on one or more pages; detecting, by a line detection engine, one or more lines in the fixed format document containing one or more attributes of a ruby line; retaining the one or more lines in the fixed format document containing one or more attributes of a ruby line as ruby line candidates and a line successive to the one or more lines as ruby base line candidates; analyzing, by a document processor, the ruby line candidate for finding one or more ruby texts contained in the ruby line candidate; matching the one or more ruby texts with a corresponding ruby base text in a successive ruby base line candidate for reconstruction in a flow format document; and reconstructing, by a serializer, the fixed format document to a flow format document containing the matched one or more ruby texts and corresponding ruby base text. 5. The method of claim 1 , wherein detecting one or more lines in the fixed format document containing one or more attributes of a ruby line comprises: analyzing the one or more lines of text for determining if a font size of characters in a line of text is smaller than a font size of characters in a successive line of text; if the font size of the characters in the line of text is smaller than the font size of the characters in the successive line of text, retaining the line of text as a ruby line candidate and the successive line of text as a ruby base line candidate.

15. A non-transitory computer readable storage medium having stored therein instructions that, when executed by a computer system, cause the computer system to perform a method of generating an Availability Management Framework (AMF) configuration for providing services and protecting the services against resource failure, wherein the AMF configuration is an instance of an AMF sub-profile that defines AMF elements to be used to model resources and the services, and is generated from an instance of an Entity Type Files (ETF) sub-profile, which is called an ETF model, and an instance of a Configuration Requirements (CR) sub-profile, which is call a CR model, each of the AMF sub-profile, the ETF sub-profile and the CR sub-profile being specializations of a pre-defined Unified Modeling Language (UML) meta-model, the method comprising the steps of: receiving the ETF model, which defines a set of ETF prototypes of the ETF model that describe the resources provided by vendors; receiving the CR model, which defines a set of CR elements of the CR model that specify configuration requirements; and applying a set of transformation rules, which are pre-defined for the ETF sub-profile, the CR sub-profile and the AMF sub-profile, to transform the ETF model and the CR model into an AMF model as the AMF configuration, wherein the CR model is organized as a first hierarchy of the CR elements, the ETF model is organized as a second hierarchy of the ETF prototypes, and one or more levels of the first hierarchy are missing levels in the second hierarchy, the step of applying further comprising the steps of: transforming a selected subset of the ETF prototypes of the ETF model that satisfy the configuration requirements into a collection of the AMF elements organized as a hierarchy with the one or more levels missing; and building the one or more missing levels from the collection of the AMF elements based on relationships between the one or more missing levels and existing levels of the first and second hierarchies.

15. A non-transitory computer readable storage medium having stored therein instructions that, when executed by a computer system, cause the computer system to perform a method of generating an Availability Management Framework (AMF) configuration for providing services and protecting the services against resource failure, wherein the AMF configuration is an instance of an AMF sub-profile that defines AMF elements to be used to model resources and the services, and is generated from an instance of an Entity Type Files (ETF) sub-profile, which is called an ETF model, and an instance of a Configuration Requirements (CR) sub-profile, which is call a CR model, each of the AMF sub-profile, the ETF sub-profile and the CR sub-profile being specializations of a pre-defined Unified Modeling Language (UML) meta-model, the method comprising the steps of: receiving the ETF model, which defines a set of ETF prototypes of the ETF model that describe the resources provided by vendors; receiving the CR model, which defines a set of CR elements of the CR model that specify configuration requirements; and applying a set of transformation rules, which are pre-defined for the ETF sub-profile, the CR sub-profile and the AMF sub-profile, to transform the ETF model and the CR model into an AMF model as the AMF configuration, wherein the CR model is organized as a first hierarchy of the CR elements, the ETF model is organized as a second hierarchy of the ETF prototypes, and one or more levels of the first hierarchy are missing levels in the second hierarchy, the step of applying further comprising the steps of: transforming a selected subset of the ETF prototypes of the ETF model that satisfy the configuration requirements into a collection of the AMF elements organized as a hierarchy with the one or more levels missing; and building the one or more missing levels from the collection of the AMF elements based on relationships between the one or more missing levels and existing levels of the first and second hierarchies. 18. The non-transitory computer readable storage medium of claim 15 , wherein the method further comprises the steps of: selecting, along a first direction of moving up the second hierarchy, the set of the ETF prototypes that provide the services required by the CR model; removing, along a second direction of moving down the second hierarchy, the ETF prototypes that do not satisfy the configuration requirements; and removing, by examining all levels of the second hierarchy in parallel, the ETF prototypes that are not required by the configuration requirements to produce the selected subset of the ETF prototypes.

1. A computer-implemented method of identifying at least one key term related to a similar passage, comprising: identifying a plurality of documents stored in a corpus, wherein each identified document contains an instance of the similar passage; for each similar passage instance within the identified documents, extracting each word that appears within a threshold number of words before the similar passage instance within an identified document and each word that appears within a threshold number of words after the similar passage instance within the identified document, the extracted words associated with the similar passage instance; combining the extracted words associated with each similar passage instance to form a context aggregation; determining a plurality of key terms related to the similar passage based on the context aggregation, each key term associated with a subset of the similar passage instances, at least one key term determined by comparing words within the context aggregation to a terms database specifying possible key terms and extracting a word within the context aggregation that matches a term in the terms database; presenting each of one or more key terms as a hyperlink in a user interface; receiving a selection of a key term presented as a hyperlink; and presenting the subset of similar passage instances associated with the selected key term in the user interface.

1. A computer-implemented method of identifying at least one key term related to a similar passage, comprising: identifying a plurality of documents stored in a corpus, wherein each identified document contains an instance of the similar passage; for each similar passage instance within the identified documents, extracting each word that appears within a threshold number of words before the similar passage instance within an identified document and each word that appears within a threshold number of words after the similar passage instance within the identified document, the extracted words associated with the similar passage instance; combining the extracted words associated with each similar passage instance to form a context aggregation; determining a plurality of key terms related to the similar passage based on the context aggregation, each key term associated with a subset of the similar passage instances, at least one key term determined by comparing words within the context aggregation to a terms database specifying possible key terms and extracting a word within the context aggregation that matches a term in the terms database; presenting each of one or more key terms as a hyperlink in a user interface; receiving a selection of a key term presented as a hyperlink; and presenting the subset of similar passage instances associated with the selected key term in the user interface. 9. The method of claim 1 , further comprising: determining a plurality of key terms related to the similar passage based on the context aggregation; assigning scores to the plurality of key terms; selecting a subset of the plurality of key terms responsive to the assigned scores; and presenting for display the selected subset of the plurality of key terms in association with the similar passage.

10. A device, comprising: one or more modules comprising instructions stored in at least one memory and executed by at least one processor in communication with the at least one memory to perform operations comprising: converting a product identification number for a product into a normalized global trade item number (GTIN); generating a first GTIN prefix from the normalized GTIN, the first GTIN prefix associated with the product identification number, respective GTIN prefixes of the plurality of GTIN prefixes being of different textual lengths; calculating a textual similarity score for every pair of brand names of a first set of the brand names, the first set of the brand names being associated with the first GTIN prefix; and identifying each pair of the brand names having the textual similarity score equal to or greater than a pre-defined threshold score, each brand name of the identified pairs of the brand names comprises a brand synonym of each other; classifying the product in the product catalog in accordance with the predicted brand name; receiving input defining a search query; searching the product catalog based on the search query to identify the product based at least in part on the predicted brand name; displaying the identified product in response to the search; receive second input indicating a request to purchase the identified product; and performing a purchase transaction for the identified product based on the received second input.

10. A device, comprising: one or more modules comprising instructions stored in at least one memory and executed by at least one processor in communication with the at least one memory to perform operations comprising: converting a product identification number for a product into a normalized global trade item number (GTIN); generating a first GTIN prefix from the normalized GTIN, the first GTIN prefix associated with the product identification number, respective GTIN prefixes of the plurality of GTIN prefixes being of different textual lengths; calculating a textual similarity score for every pair of brand names of a first set of the brand names, the first set of the brand names being associated with the first GTIN prefix; and identifying each pair of the brand names having the textual similarity score equal to or greater than a pre-defined threshold score, each brand name of the identified pairs of the brand names comprises a brand synonym of each other; classifying the product in the product catalog in accordance with the predicted brand name; receiving input defining a search query; searching the product catalog based on the search query to identify the product based at least in part on the predicted brand name; displaying the identified product in response to the search; receive second input indicating a request to purchase the identified product; and performing a purchase transaction for the identified product based on the received second input. 12. The device of claim 10 , wherein the calculating of the textual similarity score comprises calculating a cosine similarity score.

1. A feature information collecting apparatus, comprising: a first memory; and a controller that: acquires vehicle position information that represents a current position of a vehicle; acquires image information for a vicinity of the vehicle; carries out image recognition processing on recognition target objects that are included in the image information; stores recognition information in the first memory that represents a result of the image recognition of the recognition target objects in association with information for the recognition position of the recognition target objects, the recognition position determined based on the vehicle position information; and extracts, as learned features, recognition target objects that can be repeatedly recognized by image recognition based on a plurality of sets of recognition information related to the same position, the plurality of sets of recognition information being stored due to the image information for the same position being recognized a plurality of times by image recognition; wherein the recognition information is a characteristic amount represented by at least one of a noise amount and an amount of extractions of edge included in the image information.

1. A feature information collecting apparatus, comprising: a first memory; and a controller that: acquires vehicle position information that represents a current position of a vehicle; acquires image information for a vicinity of the vehicle; carries out image recognition processing on recognition target objects that are included in the image information; stores recognition information in the first memory that represents a result of the image recognition of the recognition target objects in association with information for the recognition position of the recognition target objects, the recognition position determined based on the vehicle position information; and extracts, as learned features, recognition target objects that can be repeatedly recognized by image recognition based on a plurality of sets of recognition information related to the same position, the plurality of sets of recognition information being stored due to the image information for the same position being recognized a plurality of times by image recognition; wherein the recognition information is a characteristic amount represented by at least one of a noise amount and an amount of extractions of edge included in the image information. 7. The feature information collecting apparatus according to claim 1 , wherein: the learned features include at least one of road markings provided on a surface of a road, stains on the surface of a road, grime on the surface of a road, cracks in the surface of a road, and shadows on the surface of a road.

488. The system of claim 486 , further comprising: means for receiving a modified copy of the portion of the parsed resume.

488. The system of claim 486 , further comprising: means for receiving a modified copy of the portion of the parsed resume. 489. The system of claim 488 , further comprising: means for creating a replacement resume based on the modified copy of the portion of the parsed resume.

1. A computer-implemented method, comprising: identifying, by a device, a set of documents; expanding, by the device, the set of documents to generate an expanded set of documents, where the expanded set of documents includes all of the documents in the set of documents and one or more additional documents, and where each additional document, of the one or more additional documents, links to a document in the set of documents or is linked to by a document in the set of documents; determining, by the device, a similarity measure for each pair of documents in the expanded set of documents, where, for a pair of documents, in the expanded set of documents, consisting of a first document and a second document, the similarity measure is determined based on: a quantity of documents in the expanded set of documents that contain both a forward link to the first document and a forward link to the second document, whether the first document contains a forward link to the second document, and whether the second document contains a forward link to the first document; and clustering, by the device, the documents in the expanded set of documents into a plurality of clusters based on the similarity measures.

1. A computer-implemented method, comprising: identifying, by a device, a set of documents; expanding, by the device, the set of documents to generate an expanded set of documents, where the expanded set of documents includes all of the documents in the set of documents and one or more additional documents, and where each additional document, of the one or more additional documents, links to a document in the set of documents or is linked to by a document in the set of documents; determining, by the device, a similarity measure for each pair of documents in the expanded set of documents, where, for a pair of documents, in the expanded set of documents, consisting of a first document and a second document, the similarity measure is determined based on: a quantity of documents in the expanded set of documents that contain both a forward link to the first document and a forward link to the second document, whether the first document contains a forward link to the second document, and whether the second document contains a forward link to the first document; and clustering, by the device, the documents in the expanded set of documents into a plurality of clusters based on the similarity measures. 10. The computer-implemented method of claim 1 , where clustering the documents comprises: generating initial groups of documents, in the expanded set of documents, based on the similarity measures; determining a group similarity measure for each pair of groups of documents in the initial groups of documents, where, for a pair of groups of documents, in the initial groups of documents, consisting of a first group of documents and a second group of documents, the group similarity measure is determined based on a quantity of documents, in the expanded set of documents, that contain a forward link to a document in the first group of documents and contain a forward link to a document in the second group of documents; and clustering the initial groups of documents based on the group similarity measures.

8. A computer system for data model optimization using multilevel entity dependency analytics, comprising: a computer processor to execute a set of program code instructions; and a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, accessing a multilevel schema data structure; determining a dependency relationship lineage between schema entities present in the multilevel schema data structure; generating a dependency table using the dependency relationship lineage, the dependency table comprising at least one multilevel dependency relationship between schema entities having a depth of two or more; using the dependency table to perform at least one analysis comprising at least one of, a high impact analysis, a referential integrity analysis, or a conformance analysis; and storing a result from the analysis in a stored metadata format.

8. A computer system for data model optimization using multilevel entity dependency analytics, comprising: a computer processor to execute a set of program code instructions; and a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, accessing a multilevel schema data structure; determining a dependency relationship lineage between schema entities present in the multilevel schema data structure; generating a dependency table using the dependency relationship lineage, the dependency table comprising at least one multilevel dependency relationship between schema entities having a depth of two or more; using the dependency table to perform at least one analysis comprising at least one of, a high impact analysis, a referential integrity analysis, or a conformance analysis; and storing a result from the analysis in a stored metadata format. 13. The computer system of claim 8 , further comprising receiving the stored metadata format into a data model change engine.

8. A non-transitory computing device readable medium storing instructions, the instructions comprising: instructions that, when executed by a processor of a computing device, cause the processor to: receive a graphical specification of a parent class of graphical objects in a graphical modeling environment; receive a graphical specification of a first child class of graphical objects and a second child class of graphical objects in the graphical modeling environment, wherein: the first child class of graphical objects is a first subclass of the parent class of graphical objects in a hierarchy of classes of graphical objects, the second child class of graphical objects is a second subclass of the parent class of graphical objects in the hierarchy of classes of graphical objects, and the first child class of graphical objects and the second child class of graphical objects depend respectively on the parent class of graphical objects for common features that are shared by the first child class of graphical objects and the second child class of graphical objects; receive an instruction to incorporate an instance of the parent class of graphical objects into an executable graphical model in the graphical modeling environment; instantiate an instance of the first child class of graphical objects and an instance of the second child class of graphical objects in the executable graphical model; execute the executable graphical model; and dynamically switch between the instance of the first child class of graphical objects and the instance of the second child class of graphical objects during the execution of the executable graphical model.

8. A non-transitory computing device readable medium storing instructions, the instructions comprising: instructions that, when executed by a processor of a computing device, cause the processor to: receive a graphical specification of a parent class of graphical objects in a graphical modeling environment; receive a graphical specification of a first child class of graphical objects and a second child class of graphical objects in the graphical modeling environment, wherein: the first child class of graphical objects is a first subclass of the parent class of graphical objects in a hierarchy of classes of graphical objects, the second child class of graphical objects is a second subclass of the parent class of graphical objects in the hierarchy of classes of graphical objects, and the first child class of graphical objects and the second child class of graphical objects depend respectively on the parent class of graphical objects for common features that are shared by the first child class of graphical objects and the second child class of graphical objects; receive an instruction to incorporate an instance of the parent class of graphical objects into an executable graphical model in the graphical modeling environment; instantiate an instance of the first child class of graphical objects and an instance of the second child class of graphical objects in the executable graphical model; execute the executable graphical model; and dynamically switch between the instance of the first child class of graphical objects and the instance of the second child class of graphical objects during the execution of the executable graphical model. 13. The medium of claim 8 , wherein the first child class of graphical objects is operable to modify at least one aspect that is inherited from the parent class of graphical objects.

32. A computer program product embodied in a non-transitory computer readable medium for verification analysis comprising: code for obtaining a design description including set of constraints wherein the set of constraints includes a multiplication constraint; code for analyzing the set of constraints to identify the multiplication constraint; code for performing factorization to produce factoring values that solve the multiplication constraint, wherein the factorization is performed on an overflow representation of the number; and code for solving a design problem within the design description based on the factoring values.

32. A computer program product embodied in a non-transitory computer readable medium for verification analysis comprising: code for obtaining a design description including set of constraints wherein the set of constraints includes a multiplication constraint; code for analyzing the set of constraints to identify the multiplication constraint; code for performing factorization to produce factoring values that solve the multiplication constraint, wherein the factorization is performed on an overflow representation of the number; and code for solving a design problem within the design description based on the factoring values. 35. The computer program product of claim 32 further comprising code for randomly selecting from the factoring values to solve a design problem within the design description.

31. A system for refining a content recommendation made by a user, the system comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to: receive, through a user interface of a social network application installed on a user device, an indication that a user recommended content displayed in a web browser on the user device, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the web browser, retrieve candidate annotations that describe characteristics of each of the plurality of different content components; update the user interface presented at the user device with a request for the user to select at least one of the candidate annotations for at least one of the plurality of content components; receive, through the social network application, a user selection of at least one of the candidate annotations as an annotation for at least one of the plurality of content components; and distribute through a social network the user recommended content with the selected at least one candidate annotation at a presentation location corresponding to the at least one content component of the recommended content.

31. A system for refining a content recommendation made by a user, the system comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to: receive, through a user interface of a social network application installed on a user device, an indication that a user recommended content displayed in a web browser on the user device, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the web browser, retrieve candidate annotations that describe characteristics of each of the plurality of different content components; update the user interface presented at the user device with a request for the user to select at least one of the candidate annotations for at least one of the plurality of content components; receive, through the social network application, a user selection of at least one of the candidate annotations as an annotation for at least one of the plurality of content components; and distribute through a social network the user recommended content with the selected at least one candidate annotation at a presentation location corresponding to the at least one content component of the recommended content. 35. The system of claim 31 , wherein the content includes one or both of a web page and a promotional content item.

1. A method for determining a local intent of a query comprising: receiving a query; identifying a presence of a location term in the query; separating the query into a root term and the location term when the location term is present; analyzing historical searches that record which location terms are most often associated with the root term; and computing a local intent probability (LIP) for the root term with a probability model using the historical searches wherein computing the LIP comprises a probability model using the historical searches, wherein the probability model is an exponential function between the LIP and a local intent value (LIV).

1. A method for determining a local intent of a query comprising: receiving a query; identifying a presence of a location term in the query; separating the query into a root term and the location term when the location term is present; analyzing historical searches that record which location terms are most often associated with the root term; and computing a local intent probability (LIP) for the root term with a probability model using the historical searches wherein computing the LIP comprises a probability model using the historical searches, wherein the probability model is an exponential function between the LIP and a local intent value (LIV). 2. The method of claim 1 wherein historical searches are broken into root terms that are associated with location bands, wherein the location bands cover different geographic ranges.

1. A method for implementing a future payment transaction for payments owed, comprising: presenting information to a user, the information comprising information related to payments owed, including a number of payments owed and scheduled due dates for the payments owed; providing the user with an ability to submit a future payment request to a server, wherein the future payment request comprises a request to pay money to a third party in escrow for the benefit of a separate entity ahead of schedule for at least a portion of any scheduled payment selectable by the user representing money owed to the separate entity at a future date, wherein the user is provided with an ability to submit the future payment request for an out-of-sequence scheduled payment without submitting a corresponding a payment request in-sequence scheduled payment; processing said future payment request at the server using a rules based engine configured to evaluate the future payment request by the user and, when acceptable based on rules established on behalf of the separate entity applicable to the acceptability of future payment requests, provide a decision comprising approval of the future payment request based on established rules, and when unacceptable based on rules established on behalf of the separate entity applicable to the acceptability of future payment requests, provide the decision comprising denial of the future payment request based on established rules; presenting the decision to the user; offering the user an ability to submit an alternate future payment request when the future payment request is unacceptable based on the rules established and processing that alternate future payment request at the server using the rules based engine; wherein the rules established on behalf of the separate entity comprise the acceptability of receiving a future payment from any user.

1. A method for implementing a future payment transaction for payments owed, comprising: presenting information to a user, the information comprising information related to payments owed, including a number of payments owed and scheduled due dates for the payments owed; providing the user with an ability to submit a future payment request to a server, wherein the future payment request comprises a request to pay money to a third party in escrow for the benefit of a separate entity ahead of schedule for at least a portion of any scheduled payment selectable by the user representing money owed to the separate entity at a future date, wherein the user is provided with an ability to submit the future payment request for an out-of-sequence scheduled payment without submitting a corresponding a payment request in-sequence scheduled payment; processing said future payment request at the server using a rules based engine configured to evaluate the future payment request by the user and, when acceptable based on rules established on behalf of the separate entity applicable to the acceptability of future payment requests, provide a decision comprising approval of the future payment request based on established rules, and when unacceptable based on rules established on behalf of the separate entity applicable to the acceptability of future payment requests, provide the decision comprising denial of the future payment request based on established rules; presenting the decision to the user; offering the user an ability to submit an alternate future payment request when the future payment request is unacceptable based on the rules established and processing that alternate future payment request at the server using the rules based engine; wherein the rules established on behalf of the separate entity comprise the acceptability of receiving a future payment from any user. 8. The method of claim 1 , wherein the rules engine comprises rules that consider the user's ability to satisfy the future payment request.

19. The method of claim 15 , wherein the object embedding program includes links to a plurality of different pages of network-based information and each of the different pages of network-based information includes a link to a different script program.

19. The method of claim 15 , wherein the object embedding program includes links to a plurality of different pages of network-based information and each of the different pages of network-based information includes a link to a different script program. 21. The method of claim 19 , wherein at least one of the different script programs is specific to mortgage rate information.

27. The non-transitory computer-readable medium of claim 19 , wherein the third party server includes a database associated with the notification server.

27. The non-transitory computer-readable medium of claim 19 , wherein the third party server includes a database associated with the notification server. 28. The non-transitory computer-readable medium of claim 27 , wherein the trigger message includes information associated with the user's purchase history or purchase habits.

79. The method of claim 74 wherein the generating of the second word score includes the steps of: forming simplified phone machines which includes the step of replacing by a single specific value the actual label probabilities for a given label at all transitions at which the given label may be generated in a particular phone machine; performing an approximate acoustic match for the subject word based on the simplified phone machines and the generated labels; and evaluating a fast match word score for the subject word from the performed approximate acoustic match; the fast match word score corresponding to the second word score.

79. The method of claim 74 wherein the generating of the second word score includes the steps of: forming simplified phone machines which includes the step of replacing by a single specific value the actual label probabilities for a given label at all transitions at which the given label may be generated in a particular phone machine; performing an approximate acoustic match for the subject word based on the simplified phone machines and the generated labels; and evaluating a fast match word score for the subject word from the performed approximate acoustic match; the fast match word score corresponding to the second word score. 80. The method of claim 79 including the further step of: selecting the phone machines used in performing the detailed match from a first set of phone machines; selecting the phone machines used in performing the approximate match from a second set of phone machines; the second set of phone machines differing from the first set of phone machines.

20. A method in accordance with claim 2 comprising: processing the categories of information with a plurality of analyses.

20. A method in accordance with claim 2 comprising: processing the categories of information with a plurality of analyses. 21. A method in accordance with claim 20 wherein; the plurality of analyses comprise a psychological profiling algorithm which provides an indication of a psychological state of the person, at least one key word algorithm which processes any phrases and/or threatening acts to identify a psychological state of the person and how the author may react to the identified psychological state and at least one message characteristic algorithm which analyzes characteristics of the at least one communication to identify a psychological state and/or at least one possible action of the author.

9. The system of claim 8 , wherein the call detail record comprises a prompt issued to a user and a response from the user.

9. The system of claim 8 , wherein the call detail record comprises a prompt issued to a user and a response from the user. 10. The system of claim 9 , wherein the call detail record further comprises an interpretation of the response.

6. A system for detecting and managing duplicate documents, comprising: one or more processing units for executing programs; a network interface for receiving documents; and memory storing one or more programs to be executed by the one or more processing units, the one or more programs comprising instructions that when executed by the one or more processing units cause the system to: receive a first document, the received document characterized by a document content identifier; select, from a plurality of previously received documents, a set of documents sharing the same document content identifier, the first document and the selected set having associated score information; wherein documents having the same document content identifier have the same content and documents having different document content identifiers have different content; update the selected set of documents with the first document, in accordance with the score information associated with the first document and the selected set of documents, to produce an updated set of documents; determine a representative document for the updated set of documents in accordance with the score information; index the received document when the received document is the representative document for the updated set of documents; and repeat the receiving, selecting, updating, determining and indexing operations with respect to a plurality of received documents, each of which shares a respective document content identifier with a respective set of documents, such that at least some of the received documents are determined to be representative documents and are indexed.

6. A system for detecting and managing duplicate documents, comprising: one or more processing units for executing programs; a network interface for receiving documents; and memory storing one or more programs to be executed by the one or more processing units, the one or more programs comprising instructions that when executed by the one or more processing units cause the system to: receive a first document, the received document characterized by a document content identifier; select, from a plurality of previously received documents, a set of documents sharing the same document content identifier, the first document and the selected set having associated score information; wherein documents having the same document content identifier have the same content and documents having different document content identifiers have different content; update the selected set of documents with the first document, in accordance with the score information associated with the first document and the selected set of documents, to produce an updated set of documents; determine a representative document for the updated set of documents in accordance with the score information; index the received document when the received document is the representative document for the updated set of documents; and repeat the receiving, selecting, updating, determining and indexing operations with respect to a plurality of received documents, each of which shares a respective document content identifier with a respective set of documents, such that at least some of the received documents are determined to be representative documents and are indexed. 8. The system of claim 6 , wherein the score information includes a document ranking value indicative of document importance.

13. A computer program product comprising: a computer-usable storage medium having computer-usable program code stored thereon that, when executed by a system comprising a processor and a memory, causes the system to perform a method of processing an Extensible Markup Language (XML) document, the method comprising: loading, via the processor, an execution plan into a virtual machine, wherein the execution plan represents an XML schema and specifies a hierarchy of XML components, and wherein the virtual machine comprises a plurality of dedicated XML processing functions specifically corresponding to the XML components specified by the XML schema; selectively invoking, via the processor, the XML processing functions available within the virtual machine according to the execution plan, wherein the XML processing functions operate upon an XML document; and outputting, via the processor, an indication of whether the XML document is valid according to the XML processing functions.

13. A computer program product comprising: a computer-usable storage medium having computer-usable program code stored thereon that, when executed by a system comprising a processor and a memory, causes the system to perform a method of processing an Extensible Markup Language (XML) document, the method comprising: loading, via the processor, an execution plan into a virtual machine, wherein the execution plan represents an XML schema and specifies a hierarchy of XML components, and wherein the virtual machine comprises a plurality of dedicated XML processing functions specifically corresponding to the XML components specified by the XML schema; selectively invoking, via the processor, the XML processing functions available within the virtual machine according to the execution plan, wherein the XML processing functions operate upon an XML document; and outputting, via the processor, an indication of whether the XML document is valid according to the XML processing functions. 19. The computer program product of claim 13 , wherein selectively invoking XML processing functions further comprises selecting an XML processing function that performs flow control within the virtual machine.

1. A method comprising: creating a recording of a name of a particular user in a network, the recording of the name comprising an audio representation of an accurate pronunciation of the name; storing the recording of the name in a storage location within the network; providing a list of a plurality of user names and respective presence information regarding each of the plurality of users; receiving a request from an endpoint for the recording of the name of the particular user, the request for the recording being generated by the endpoint selecting the name of the particular user from the list of the plurality of user names; accessing the storage location in response to the request; providing the recording of the name of the particular user in response to the request from the endpoint; wherein creating the recording of the name comprises creating a first version and a second version of the audio representation; and wherein providing the recording of the name comprises providing the first version or the second version of the audio representation based on presence based call routing rules, caller identification information, or phone number association.

1. A method comprising: creating a recording of a name of a particular user in a network, the recording of the name comprising an audio representation of an accurate pronunciation of the name; storing the recording of the name in a storage location within the network; providing a list of a plurality of user names and respective presence information regarding each of the plurality of users; receiving a request from an endpoint for the recording of the name of the particular user, the request for the recording being generated by the endpoint selecting the name of the particular user from the list of the plurality of user names; accessing the storage location in response to the request; providing the recording of the name of the particular user in response to the request from the endpoint; wherein creating the recording of the name comprises creating a first version and a second version of the audio representation; and wherein providing the recording of the name comprises providing the first version or the second version of the audio representation based on presence based call routing rules, caller identification information, or phone number association. 6. The method of claim 1 , further comprising associating the particular user with a plurality of possible endpoints.

10. The method of claim 9 wherein the object option includes at least one of, an operation and attribute.

10. The method of claim 9 wherein the object option includes at least one of, an operation and attribute. 15. The method of claim 10 wherein defining a component step further includes, allowing the user to define a default value and a description.

1. A fuzzy logic method for reasoning about data, comprising the steps of: (i) accessing the data; (ii) determining a type of the data from a group consisting of numeric, linguistic and a hybrid combination thereof; (iii) selecting a rule for firing based on the determined type of the data; (iv) obtaining fuzzy membership grades; (v) aggregating the fuzzy membership grades by invoking a parametric formulation; (vi) applying a compositional rule of inference parametrically to extract a consequent to obtain a fuzzy output; and (vii) defuzifying the fuzzy output.

1. A fuzzy logic method for reasoning about data, comprising the steps of: (i) accessing the data; (ii) determining a type of the data from a group consisting of numeric, linguistic and a hybrid combination thereof; (iii) selecting a rule for firing based on the determined type of the data; (iv) obtaining fuzzy membership grades; (v) aggregating the fuzzy membership grades by invoking a parametric formulation; (vi) applying a compositional rule of inference parametrically to extract a consequent to obtain a fuzzy output; and (vii) defuzifying the fuzzy output. 5. The method according to claim 1 , wherein the type of the data is linguistic, and wherein the rule has a singleton consequent.

1. A system for performing an ad hoc query comprising: a query service operating on a processor and configured to receive an ad hoc query in a domain-specific language; a query parsing service operating on the processor and configured to receive a validate request and a parse request from the query service and to return a query object to the query service; and a queryable interface operating on the processor and configured to receive the query object and to transmit the query object to one or more framework services for execution, wherein the ad hoc query contains one or more new key words and the query parsing service and the queryable interface are configured to add the one or more new key words if they are located in an associated model in the framework services.

1. A system for performing an ad hoc query comprising: a query service operating on a processor and configured to receive an ad hoc query in a domain-specific language; a query parsing service operating on the processor and configured to receive a validate request and a parse request from the query service and to return a query object to the query service; and a queryable interface operating on the processor and configured to receive the query object and to transmit the query object to one or more framework services for execution, wherein the ad hoc query contains one or more new key words and the query parsing service and the queryable interface are configured to add the one or more new key words if they are located in an associated model in the framework services. 10. The system of claim 1 wherein the query service is configured to expand a set of domain-specific query terms without a change in a query language.

14. One or more non-transitory computer-readable storage media storing instructions, which when executed by one or more processors, cause the one or more processors to perform: determining that a first query is associated with a first query category; detecting a first entity text in the first query; mapping the first entity text to a first entity category at least partially in response to: (a) determining that the first entity text is among a plurality of entity texts that are mapped to an entity of a plurality of entities, wherein a plurality of other entity texts are mapped to a plurality of other entities of the plurality of entities, and (b) determining that the entity is mapped to the first entity category; determining a first keyword text that occurs in the first query in addition to the first entity text; determining that a second query comprises said first keyword text and a second entity text in said first entity category; based at least in part on said determining that the second query comprises said first keyword text and the second entity text in said first entity category, storing information that indicates that the second query is associated with said first query category; storing a plurality of annotated queries in association with a plurality of query categories, wherein each annotated query of the plurality of annotated queries comprises a pair of at least a keyword text and an entity category, and wherein each annotated query represents one or more queries of a set of queries; for each annotated query of the plurality of annotated queries, determining an accuracy value for the annotated query based at least in part on a frequency by which the annotated query refers to a query category associated with the annotated query relative to a total number of times the annotated query occurs in the set of queries; selecting one or more annotated queries of the plurality of annotated queries based at least in part on the accuracy value determined for the one or more annotated queries.

14. One or more non-transitory computer-readable storage media storing instructions, which when executed by one or more processors, cause the one or more processors to perform: determining that a first query is associated with a first query category; detecting a first entity text in the first query; mapping the first entity text to a first entity category at least partially in response to: (a) determining that the first entity text is among a plurality of entity texts that are mapped to an entity of a plurality of entities, wherein a plurality of other entity texts are mapped to a plurality of other entities of the plurality of entities, and (b) determining that the entity is mapped to the first entity category; determining a first keyword text that occurs in the first query in addition to the first entity text; determining that a second query comprises said first keyword text and a second entity text in said first entity category; based at least in part on said determining that the second query comprises said first keyword text and the second entity text in said first entity category, storing information that indicates that the second query is associated with said first query category; storing a plurality of annotated queries in association with a plurality of query categories, wherein each annotated query of the plurality of annotated queries comprises a pair of at least a keyword text and an entity category, and wherein each annotated query represents one or more queries of a set of queries; for each annotated query of the plurality of annotated queries, determining an accuracy value for the annotated query based at least in part on a frequency by which the annotated query refers to a query category associated with the annotated query relative to a total number of times the annotated query occurs in the set of queries; selecting one or more annotated queries of the plurality of annotated queries based at least in part on the accuracy value determined for the one or more annotated queries. 15. The one or more non-transitory computer-readable storage media of claim 14 , wherein the first query is one of a first set of queries, wherein the first query category is one of a set of query categories, wherein each particular query of the first set of queries is associated with a particular query category of the set of query categories; the instructions further causing the one or more processors to perform: for each particular query in the first set of queries: detecting a particular entity text in the particular query; mapping the particular entity text to a particular entity category by: determining that the particular entity text is among a plurality of entity texts mapped to a particular entity of the plurality of entities, and mapping the particular entity to the particular entity category; determining a particular keyword text that occurs in the particular query in addition to the particular entity text; storing information that indicates that a particular annotated query comprising the particular keyword text and the particular entity category is associated with the particular query category.

1. Method, in particular computer-implemented method or method implemented by digital electronic components, for retrieving results in response to a query, in particular a user-defined natural language query, from semantically structured resources stored in at least one database, comprising the steps of: i. tokenizing the query by segmenting the query into terms, in particular one or multiple words, and mapping them into semantic tokens using at least one lexicon, wherein such lexicon contains at least the token type of a semantic token, in particular class, role, instance and/or constraint, ii. generating a representation, in particular a representation Incorporating a mathematical graph, of the semantic tokens associated with the segmentation performed in step (i), and determining the representation's focus, by employing a set of rules or patterns for such focus based on the token type, in particular class, role, instance and/or constraint, of the semantic tokens, wherein the rules or patterns define one or more nodes, and/or one or more relationships between nodes, associated with the token type of the semantic tokens, and the rules or patterns distinguish between terminal and non-terminal nodes and relationships, and characterize one of the non-terminal nodes or relationships as the query's focus, iii. generating a database query, in particular an SQL, SPARQL or XQuery query, from the graph-based intermediate representation determined in steps i) and ii) and sending it to the at least one database, iv. retrieving a response from the at least one database.

1. Method, in particular computer-implemented method or method implemented by digital electronic components, for retrieving results in response to a query, in particular a user-defined natural language query, from semantically structured resources stored in at least one database, comprising the steps of: i. tokenizing the query by segmenting the query into terms, in particular one or multiple words, and mapping them into semantic tokens using at least one lexicon, wherein such lexicon contains at least the token type of a semantic token, in particular class, role, instance and/or constraint, ii. generating a representation, in particular a representation Incorporating a mathematical graph, of the semantic tokens associated with the segmentation performed in step (i), and determining the representation's focus, by employing a set of rules or patterns for such focus based on the token type, in particular class, role, instance and/or constraint, of the semantic tokens, wherein the rules or patterns define one or more nodes, and/or one or more relationships between nodes, associated with the token type of the semantic tokens, and the rules or patterns distinguish between terminal and non-terminal nodes and relationships, and characterize one of the non-terminal nodes or relationships as the query's focus, iii. generating a database query, in particular an SQL, SPARQL or XQuery query, from the graph-based intermediate representation determined in steps i) and ii) and sending it to the at least one database, iv. retrieving a response from the at least one database. 4. Method according to claim 1 , wherein step ii) includes: a) employing a set of rules or patterns with a specific token type, in particular a class, instance, role or constraint for each semantic token, wherein each said rule or pattern defines one or more said nodes, and/or one or more said relationships, associated with the token type of such semantic token, b) computing further relationships between the nodes and/or relationships to complete the mathematical graph, c) selecting one of the non-terminal nodes or non-terminal relations as a focus, in particular based on a comparison between the similarity of the mathematical graph and the semantic tokens in the segmentation and/or a truth value associated with the further relationship between the node and/or the relationship.

1. A method of disambiguating an input into a handheld electronic device, the method comprising: detecting an ambiguous input including one or more selections of one or more input keys; generating one or more prefix objects corresponding with the ambiguous input; generating an output set including at least some of the one or more prefix objects, wherein each of the at least some of the one or more prefix objects is associated with an identified corresponding word object; determining, using a processor, a quantity of prefix objects in the output set is fewer than a predetermined quantity, and, based on the determination, adding as an orphan prefix object to the output set an additional prefix object of the one or more of prefix objects for which a corresponding word object was not identified; outputting the output set; detecting an additional selection of one or more input keys; determining that a selection input was not detected between the detection of the ambiguous input and the detection of the additional selection; and generating one or more additional prefix objects corresponding with the ambiguous input plus the additional selection without generating an additional prefix object corresponding with the orphan prefix object.

1. A method of disambiguating an input into a handheld electronic device, the method comprising: detecting an ambiguous input including one or more selections of one or more input keys; generating one or more prefix objects corresponding with the ambiguous input; generating an output set including at least some of the one or more prefix objects, wherein each of the at least some of the one or more prefix objects is associated with an identified corresponding word object; determining, using a processor, a quantity of prefix objects in the output set is fewer than a predetermined quantity, and, based on the determination, adding as an orphan prefix object to the output set an additional prefix object of the one or more of prefix objects for which a corresponding word object was not identified; outputting the output set; detecting an additional selection of one or more input keys; determining that a selection input was not detected between the detection of the ambiguous input and the detection of the additional selection; and generating one or more additional prefix objects corresponding with the ambiguous input plus the additional selection without generating an additional prefix object corresponding with the orphan prefix object. 4. The method of claim 1 , wherein each of the at least some of the one or more prefix objects is positioned in the output set at a position corresponding to a frequency object associated with the identified corresponding word object.

11. A system for clustering content according to similarity, the system comprising: a processor configured to: receive a set of features for a plurality of content items; calculate a distance matrix for the plurality of content based on user navigation of at least some of the content items; label content items as a pairwise constraint based on the distance matrix; and create a boosted cluster by incorporating the pairwise constraint into a clustering algorithm; a tangible computer readable media configured store the boosted cluste; apply a pattern analysis to data points representing the boosted cluster; and modify the boosted cluster based on relations identified by the pattern analysis.

11. A system for clustering content according to similarity, the system comprising: a processor configured to: receive a set of features for a plurality of content items; calculate a distance matrix for the plurality of content based on user navigation of at least some of the content items; label content items as a pairwise constraint based on the distance matrix; and create a boosted cluster by incorporating the pairwise constraint into a clustering algorithm; a tangible computer readable media configured store the boosted cluste; apply a pattern analysis to data points representing the boosted cluster; and modify the boosted cluster based on relations identified by the pattern analysis. 19. The system of claim 11 , wherein the boosted cluster is stored as a data structure in a computer readable memory and wherein the modifying step includes modifying the data structure.

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

2. The computer program product in accordance with claim 1 , wherein when the language service provider port component holds a plurality of language service providers, the management component is further configured to select one of the plurality of language service providers to provide the set of available symbols. 8. The computer program product in accordance with claim 2 , wherein the management component is further configured to register new language service components as they are added to the language service provider port component.

11. A computer-readable storage medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to: receive an original query from a user to search a plurality of images, each of which is associated with metadata; generate a first results set based on executing the original query relative to metadata associated with each image in said plurality of images; select, from the first results set, a specified number of results ranked highest in the first results set; generate a list comprising terms from metadata associated with each result of the specified number of results; for each term in the list, calculate a weight for that term based on a frequency of occurrence of that term in the list; generate a single updated query comprising terms that are in the list and that are weighted based on said weights; generate a second results set by executing only the updated query relative to metadata associated with each image in said plurality of images; store the second results set on a non-volatile or volatile computer readable storage medium; and display, as a result of the original query, only images that are associated with metadata containing terms in the second results set, without executing any query other than the updated query to generate the second results set.

11. A computer-readable storage medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to: receive an original query from a user to search a plurality of images, each of which is associated with metadata; generate a first results set based on executing the original query relative to metadata associated with each image in said plurality of images; select, from the first results set, a specified number of results ranked highest in the first results set; generate a list comprising terms from metadata associated with each result of the specified number of results; for each term in the list, calculate a weight for that term based on a frequency of occurrence of that term in the list; generate a single updated query comprising terms that are in the list and that are weighted based on said weights; generate a second results set by executing only the updated query relative to metadata associated with each image in said plurality of images; store the second results set on a non-volatile or volatile computer readable storage medium; and display, as a result of the original query, only images that are associated with metadata containing terms in the second results set, without executing any query other than the updated query to generate the second results set. 15. The computer-readable storage medium of claim 11 , wherein metadata comprises title, description, and tags.

1. A computer-implemented system comprising: at least one processor to run a detecting module configured to detect a listing for an item, the listing including a title, and a category of the item for transaction; a determining module to determine a recommended category set for the item using categories of existing listings that match one or more keywords in the title; a verifying module to verify whether the category of the item complies with the recommended category set; and a generating module to generate a tune-up report for the listing upon completion of the verification, the tune-up report including the recommended category set and a recommendation comprising at least one tip regarding highlighting one or more keywords of the listing, the generating module configured to determine an attribute value indicative of an experience level of a user who listed the listing based on a number of previous transactions by the user and to optimize the tune-up report according to the attribute value, wherein the generating module is configured to calculate a fee for the tune-up report based on a number of categories of the recommended category set accepted by the user.

1. A computer-implemented system comprising: at least one processor to run a detecting module configured to detect a listing for an item, the listing including a title, and a category of the item for transaction; a determining module to determine a recommended category set for the item using categories of existing listings that match one or more keywords in the title; a verifying module to verify whether the category of the item complies with the recommended category set; and a generating module to generate a tune-up report for the listing upon completion of the verification, the tune-up report including the recommended category set and a recommendation comprising at least one tip regarding highlighting one or more keywords of the listing, the generating module configured to determine an attribute value indicative of an experience level of a user who listed the listing based on a number of previous transactions by the user and to optimize the tune-up report according to the attribute value, wherein the generating module is configured to calculate a fee for the tune-up report based on a number of categories of the recommended category set accepted by the user. 18. The computer-implemented system of claim 1 , wherein the generating module is configured to add a recommendation associated with the listing in the tune-up report based on a determination that the number of previous transactions does not exceed a threshold value and wherein the generation module is configured to refrain from adding the recommendation in the tune-up report based on a determination that the number of previous transactions exceeds the threshold value.

1. A method for performing context inference in a mobile device, the method comprising: receiving, at a classifier implemented in one or more integrated circuits of the mobile device, sensor data from at least one data source associated with the mobile device, wherein the at least one data source comprises one or more sensors of the mobile device; determining, by the classifier implemented in the one or more integrated circuits, a first context class for the received sensor data, the first context class corresponding to a context state indicated by the received sensor data; determining, by the classifier implemented in the one or more integrated circuits, that a confidence value associated with the determination of the first context class is below a threshold value; creating, by the classifier implemented in the one or more integrated circuits, a fusion class for the received sensor data at least in part by fusing the first context class for the received sensor data and at least a second context class for the received sensor data, the at least the second context class being different from the first context class, wherein the fusion class semantically encompasses the first context class and the at least the second context class and further wherein the fusion class is broader than each of the first context class and the at least the second context class; substituting, by the classifier implemented in the one or more integrated circuits, the fusion class for the first context class; and outputting, by the classifier implemented in the one or more integrated circuits, the fusion class as the inferred context of the mobile device.

1. A method for performing context inference in a mobile device, the method comprising: receiving, at a classifier implemented in one or more integrated circuits of the mobile device, sensor data from at least one data source associated with the mobile device, wherein the at least one data source comprises one or more sensors of the mobile device; determining, by the classifier implemented in the one or more integrated circuits, a first context class for the received sensor data, the first context class corresponding to a context state indicated by the received sensor data; determining, by the classifier implemented in the one or more integrated circuits, that a confidence value associated with the determination of the first context class is below a threshold value; creating, by the classifier implemented in the one or more integrated circuits, a fusion class for the received sensor data at least in part by fusing the first context class for the received sensor data and at least a second context class for the received sensor data, the at least the second context class being different from the first context class, wherein the fusion class semantically encompasses the first context class and the at least the second context class and further wherein the fusion class is broader than each of the first context class and the at least the second context class; substituting, by the classifier implemented in the one or more integrated circuits, the fusion class for the first context class; and outputting, by the classifier implemented in the one or more integrated circuits, the fusion class as the inferred context of the mobile device. 5. The method of claim 1 wherein the substituting the fusion class is performed in response to the confidence value associated with the determination of the first context class being below the threshold value.

9. A handheld electronic device, comprising: a housing; an input apparatus including a keyboard with a plurality of character keys; an output apparatus including a display; a processor apparatus having a processor and a memory, the processor apparatus is structured to receive input from the keyboard, to provide output signals to the display, and to execute a number of routines; the memory having a number of routines stored therein; the number of routines including at least one keyboard routine structured to associate an individual character key input with a specific character, the characters being provided in a database having sets of associated characters, the sets of associated characters including at least one non-Latin character set and the Latin character set; the number of routines including at least one e-mail routine structured to present an e-mail address field and to detect and present input from the keyboard character keys; wherein the processor apparatus is structured to execute the at least one keyboard routine and the at least one e-mail routine to cause the handheld electronic device to perform operations comprising: a) having the plurality of character keys associated with a non-Latin character set; b) detecting input of a first at least one non-Latin character; c) determining if any non-Latin character names within the address book corresponds to the detected input; d) determining a first at least one Latin character associated with each character of the input; e) determining if any Latin character names within the address book corresponds to the first at least one Latin character; f) if any non-Latin character names or Latin character names within the address book correspond to the first at least one Latin character, presenting at least one name that corresponds to the detected first at least one non-Latin character; g) receiving a trigger input; h) detecting input of a second at least one non-Latin character; i) associated with the second at least one non-Latin character associated with the second at least one non-Latin character; and j) presenting at least a second Latin character name corresponds to the first at least one Latin character and the second at least one Latin character.

9. A handheld electronic device, comprising: a housing; an input apparatus including a keyboard with a plurality of character keys; an output apparatus including a display; a processor apparatus having a processor and a memory, the processor apparatus is structured to receive input from the keyboard, to provide output signals to the display, and to execute a number of routines; the memory having a number of routines stored therein; the number of routines including at least one keyboard routine structured to associate an individual character key input with a specific character, the characters being provided in a database having sets of associated characters, the sets of associated characters including at least one non-Latin character set and the Latin character set; the number of routines including at least one e-mail routine structured to present an e-mail address field and to detect and present input from the keyboard character keys; wherein the processor apparatus is structured to execute the at least one keyboard routine and the at least one e-mail routine to cause the handheld electronic device to perform operations comprising: a) having the plurality of character keys associated with a non-Latin character set; b) detecting input of a first at least one non-Latin character; c) determining if any non-Latin character names within the address book corresponds to the detected input; d) determining a first at least one Latin character associated with each character of the input; e) determining if any Latin character names within the address book corresponds to the first at least one Latin character; f) if any non-Latin character names or Latin character names within the address book correspond to the first at least one Latin character, presenting at least one name that corresponds to the detected first at least one non-Latin character; g) receiving a trigger input; h) detecting input of a second at least one non-Latin character; i) associated with the second at least one non-Latin character associated with the second at least one non-Latin character; and j) presenting at least a second Latin character name corresponds to the first at least one Latin character and the second at least one Latin character. 13. The method of claim 9 further comprising the steps of: reiterating steps (b)-(f) wherein the input becomes longer with each iteration.

1. A method comprising: placing an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoking a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtaining information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; using the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identifying items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and ranking the relevant items.

1. A method comprising: placing an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoking a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtaining information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; using the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identifying items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and ranking the relevant items. 6. The method as claimed in claim 1 including determining which of a plurality of extraction processes is most efficient for the content of the web page.

16. A computer program product comprising computer readable media having computer readable program code embodied therein, the computer readable program code adapted to be executed as: a compiled rating model corresponding to a calculation base including variables, factor tables and calculation sequences thereof, wherein one or more axes of the factor tables are bound to respective ones of the variables, and wherein the calculation sequences are defined in terms of steps operative on values of the variables and cells of the factor tables; a lookup facility to identify runtime identifiers corresponding to runtime instances of the variables; an input interface including access methods for setting values for the runtime instances of the variables using the corresponding runtime identifiers; and a calculate method of the compiled rating model executable to generate result of the calculation sequences based on the set values.

16. A computer program product comprising computer readable media having computer readable program code embodied therein, the computer readable program code adapted to be executed as: a compiled rating model corresponding to a calculation base including variables, factor tables and calculation sequences thereof, wherein one or more axes of the factor tables are bound to respective ones of the variables, and wherein the calculation sequences are defined in terms of steps operative on values of the variables and cells of the factor tables; a lookup facility to identify runtime identifiers corresponding to runtime instances of the variables; an input interface including access methods for setting values for the runtime instances of the variables using the corresponding runtime identifiers; and a calculate method of the compiled rating model executable to generate result of the calculation sequences based on the set values. 17. The computer program product of claim 16 , wherein the runtime identifiers allow client code to employ the compiled rating model without knowledge of internals thereof.

39. The search system of claim 35 , wherein at least some of said semantic representations are delicensed based upon a lack of semantic coherence between them.

39. The search system of claim 35 , wherein at least some of said semantic representations are delicensed based upon a lack of semantic coherence between them. 40. The search system of claim 39 , wherein said licensing is based at least in part upon a statistical distributions of concepts associated with said semantic representations.

2. The method of claim 1 , wherein the classifying the plurality of questions comprises: identifying the plurality of common questions; calculating the semantic relatedness value between each of the remaining questions, of the plurality of questions, and each of the plurality of common questions; determining whether any of the semantic relatedness values reaches a particular threshold value; in response to determining that one or more of the semantic relatedness values are equal to or greater than the particular threshold value, disregarding one or more questions, of the remaining questions, wherein the one or more questions correspond to the one or more semantic relatedness values; and in response to determining that one or more other semantic relatedness values, of the semantic relatedness values between each of the remaining questions and each of the plurality of common questions, are not equal to or are less than the particular threshold value, identifying one or more other questions, of the remaining questions, as one or more new common questions, wherein the one or more other questions correspond to the one or more other semantic relatedness values.

2. The method of claim 1 , wherein the classifying the plurality of questions comprises: identifying the plurality of common questions; calculating the semantic relatedness value between each of the remaining questions, of the plurality of questions, and each of the plurality of common questions; determining whether any of the semantic relatedness values reaches a particular threshold value; in response to determining that one or more of the semantic relatedness values are equal to or greater than the particular threshold value, disregarding one or more questions, of the remaining questions, wherein the one or more questions correspond to the one or more semantic relatedness values; and in response to determining that one or more other semantic relatedness values, of the semantic relatedness values between each of the remaining questions and each of the plurality of common questions, are not equal to or are less than the particular threshold value, identifying one or more other questions, of the remaining questions, as one or more new common questions, wherein the one or more other questions correspond to the one or more other semantic relatedness values. 3. The method of claim 2 , wherein the calculating the semantic relatedness value between one of the remaining questions and one of the plurality of common questions comprises: pretreating the one of the remaining questions; extracting a set of new terms from the pretreated one of the remaining questions; extracting a set of common terms from the one of the plurality of common questions; and calculating the semantic relatedness value between the set of new terms and the set of common terms.

2. The system as defined by claim 1 wherein said second selection criterion is more restrictive than said first selection criterion.

2. The system as defined by claim 1 wherein said second selection criterion is more restrictive than said first selection criterion. 3. The system as defined by claim 2 wherein said first feature signal is provided with a predetermined delay in its turn-off characteristic.

39. A system, comprising: a radiation source configured to direct incident radiation to a sample; a detector configured to measure radiation from the sample; and an electronic processor configured to: determine spectral information for the sample from the measured radiation; determine, based on the spectral information, probabilities that the sample corresponds to each of a plurality of candidates in a library of reference information; determine, based on the probabilities, whether sample identity information can be obtained by comparing the measured spectral information to the reference information; when the sample identity information cannot be obtained, adjust a characteristic of the system to increase a magnitude of one of the probabilities relative to the other probabilities, and repeat the steps of measuring radiation, determining spectral information, determining the probabilities, and determining whether sample identity information can be obtained, until the sample identity information can be obtained; and compare the spectral information to the reference information to determine the sample identity information.

39. A system, comprising: a radiation source configured to direct incident radiation to a sample; a detector configured to measure radiation from the sample; and an electronic processor configured to: determine spectral information for the sample from the measured radiation; determine, based on the spectral information, probabilities that the sample corresponds to each of a plurality of candidates in a library of reference information; determine, based on the probabilities, whether sample identity information can be obtained by comparing the measured spectral information to the reference information; when the sample identity information cannot be obtained, adjust a characteristic of the system to increase a magnitude of one of the probabilities relative to the other probabilities, and repeat the steps of measuring radiation, determining spectral information, determining the probabilities, and determining whether sample identity information can be obtained, until the sample identity information can be obtained; and compare the spectral information to the reference information to determine the sample identity information. 40. The system of claim 39 , wherein the electronic processor is further configured to determine, for each of the plurality of candidates, an overlap between a range of expected values of the spectral information based on the reference information, and a range of measurement values based on the spectral information and an estimate of a variability of the spectral information.

4. The method of claim 1 , in which the information resource is among one or more information resources, the method further comprising: extracting a set of surface forms and entity indicators associated with a plurality of named entities from the one or more information resources; storing the surface forms and named entities in a surface form reference, comprising a data collection indexed by the surface forms and indicating the named entities associated with each of the surface forms; and storing the named entities and entity indicators in a named entity reference, comprising a data collection indexed by the named entities and containing the entity indicators associated with each of the named entities; in which the surface form of a named entity in a text is identified from among the surface forms stored in the surface form reference, and the one or more measures of correlation are evaluated between the text and the extracted entity indicators stored in the named entity reference.

4. The method of claim 1 , in which the information resource is among one or more information resources, the method further comprising: extracting a set of surface forms and entity indicators associated with a plurality of named entities from the one or more information resources; storing the surface forms and named entities in a surface form reference, comprising a data collection indexed by the surface forms and indicating the named entities associated with each of the surface forms; and storing the named entities and entity indicators in a named entity reference, comprising a data collection indexed by the named entities and containing the entity indicators associated with each of the named entities; in which the surface form of a named entity in a text is identified from among the surface forms stored in the surface form reference, and the one or more measures of correlation are evaluated between the text and the extracted entity indicators stored in the named entity reference. 5. The method of claim 4 , wherein the one or more information resources are selected from among a group consisting of: an encyclopedia; a directory; an atlas; and a citation index.

13. The computer storage medium of claim 1 , wherein the metadata corresponding to the second input is associated with the first photo as well as the circumscribed portion such that in response to the search request, a thumbnail representation of the entire first photo and a thumbnail representation of only the circumscribed portion of the first photo is displayed.

13. The computer storage medium of claim 1 , wherein the metadata corresponding to the second input is associated with the first photo as well as the circumscribed portion such that in response to the search request, a thumbnail representation of the entire first photo and a thumbnail representation of only the circumscribed portion of the first photo is displayed. 15. The computer storage medium of claim 13 , wherein the slideshow is initiated after the thumbnail representations of the photos are displayed and in response to user input that selects a slideshow mode for display of the second plurality of photos returned by the search.

1. A method comprising: receiving, at a network entity, a multimedia message from a sending entity and addressed to one or more recipients, wherein the multimedia message includes media content; determining, by the network entity, whether a recipient rule specified by at least one recipient of the one or more recipients exists; and responsive to a determination that the recipient rule exists, delivering the media content to the at least one recipient of the one or more recipients based upon the recipient rule.

1. A method comprising: receiving, at a network entity, a multimedia message from a sending entity and addressed to one or more recipients, wherein the multimedia message includes media content; determining, by the network entity, whether a recipient rule specified by at least one recipient of the one or more recipients exists; and responsive to a determination that the recipient rule exists, delivering the media content to the at least one recipient of the one or more recipients based upon the recipient rule. 2. The method according to claim 1 , wherein the recipient rule is independent of the sending entity.

18. A method comprising: providing program code to launch a translation window associated with a primary window; providing a link to the program code, wherein when the primary window is displayed on a screen the program code causes the translation window to open on the screen with the primary window, and the translation window will be positioned so that the translation window does not overlap the primary window; receiving input information in a first language in a text box of the translation window; translating the input information from the first language to information in a second language, wherein the information in the second language is received from a first source; and displaying the information in the second language in the translation window, wherein the translation window has a length longer than its width.

18. A method comprising: providing program code to launch a translation window associated with a primary window; providing a link to the program code, wherein when the primary window is displayed on a screen the program code causes the translation window to open on the screen with the primary window, and the translation window will be positioned so that the translation window does not overlap the primary window; receiving input information in a first language in a text box of the translation window; translating the input information from the first language to information in a second language, wherein the information in the second language is received from a first source; and displaying the information in the second language in the translation window, wherein the translation window has a length longer than its width. 23. The method of claim 18 wherein the input information comprises a word or a sentence.

4. The system as set forth in claim 3 , wherein the text classifier module further comprises a user type identification classifier to determine whether a user identification is related to an individual or an organization, and wherein the one or more processors further perform an operation of increasing the probability of the civil unrest event occurring if the user identification is related to an organization.

4. The system as set forth in claim 3 , wherein the text classifier module further comprises a user type identification classifier to determine whether a user identification is related to an individual or an organization, and wherein the one or more processors further perform an operation of increasing the probability of the civil unrest event occurring if the user identification is related to an organization. 5. The system as set forth in claim 4 , wherein the one or more processors further perform an operation of searching the set of textual social media data for mentions of cities or monuments to assign a location to the civil unrest event.

15. The system of claim 10 , wherein the inference input module is further configured to: infer an interest level of the user among the hierarchy of categories based on a first adjusted category score vector.

15. The system of claim 10 , wherein the inference input module is further configured to: infer an interest level of the user among the hierarchy of categories based on a first adjusted category score vector. 18. The system of claim 15 , wherein the second network resource is separate from the plurality of network resources and has not been used by the user, and wherein the plurality of edges further represents the measure of cross-references between the second resource description data record and the plurality of resource description data collections.

1. A method, implemented by a media server, for distributing media content with overlay graphical information from the media server to a media client, the method comprising: retrieving, from a media source, one or more frames carrying media content, wherein at least one of the one or more frames encodes overlay graphical information that is integrated into viewable non-overlay media content; extracting, from the at least one frame, the overlay graphical information so as to exclude the viewable non-overlay media content also encoded by the at least one frame; transmitting the extracted overlay graphical information of the at least one frame to the media client, separately from the viewable non-overlay media content of the at least one frame; processing, in separate blocks, each of the one or more frames that comprise an area of overlay graphical information, the processing comprising masking an area of a block that comprises overlay graphical information and lowpass filtering the block, thereby avoiding introduction of visual artifacts in the vicinity of the overlay graphical information; encoding each processed frame; and transmitting each encoded frame to the media client, thereby enabling the media client to reproduce the media content without encoding-originated artifacts by adding the extracted overlay graphical information as an overlay on top of media content decoded from the encoded frames.

1. A method, implemented by a media server, for distributing media content with overlay graphical information from the media server to a media client, the method comprising: retrieving, from a media source, one or more frames carrying media content, wherein at least one of the one or more frames encodes overlay graphical information that is integrated into viewable non-overlay media content; extracting, from the at least one frame, the overlay graphical information so as to exclude the viewable non-overlay media content also encoded by the at least one frame; transmitting the extracted overlay graphical information of the at least one frame to the media client, separately from the viewable non-overlay media content of the at least one frame; processing, in separate blocks, each of the one or more frames that comprise an area of overlay graphical information, the processing comprising masking an area of a block that comprises overlay graphical information and lowpass filtering the block, thereby avoiding introduction of visual artifacts in the vicinity of the overlay graphical information; encoding each processed frame; and transmitting each encoded frame to the media client, thereby enabling the media client to reproduce the media content without encoding-originated artifacts by adding the extracted overlay graphical information as an overlay on top of media content decoded from the encoded frames. 7. The method according to claim 1 , wherein said overlay graphical information comprises text.

15. A graphical user interface (GUI) system for tuning access middleware that provides an application with one or more connections to a database, the GUI system comprising: a processor; a module for providing a driver/provider selection screen for receiving a first response from a user specifying a type of a driver/provider for the database to be tuned; a module for providing a plurality of navigable application question screens for querying the user based on the first response received from the user and receiving a second response from the user specifying whether the application connected via the access middleware to the database supports a functionality specified in a query; a module for providing one or more preference question screens based on the first and second responses and receiving a third response from the user specifying one or more user preferences, each preference question screen querying the user regarding one or more user preferences associated with application performance; a module for generating, based on the first response received from the user, the second response received from the user specifying whether the application supports the functionality and the third response from the user specifying one or more user preferences associated with performance, a set of connection options and values configured to achieve optimal performance of the driver/provider; and a module for providing a results screen for providing the set of connection options and values to the user.

15. A graphical user interface (GUI) system for tuning access middleware that provides an application with one or more connections to a database, the GUI system comprising: a processor; a module for providing a driver/provider selection screen for receiving a first response from a user specifying a type of a driver/provider for the database to be tuned; a module for providing a plurality of navigable application question screens for querying the user based on the first response received from the user and receiving a second response from the user specifying whether the application connected via the access middleware to the database supports a functionality specified in a query; a module for providing one or more preference question screens based on the first and second responses and receiving a third response from the user specifying one or more user preferences, each preference question screen querying the user regarding one or more user preferences associated with application performance; a module for generating, based on the first response received from the user, the second response received from the user specifying whether the application supports the functionality and the third response from the user specifying one or more user preferences associated with performance, a set of connection options and values configured to achieve optimal performance of the driver/provider; and a module for providing a results screen for providing the set of connection options and values to the user. 16. The system of claim 15 , further comprising: a module for providing one or more user preference question screens and receiving a personal knowledge response regarding personal knowledge of the user, each user preference question screen querying the user regarding personal knowledge of database systems; and wherein the module for generating the set of connection options and values is configured to generate the set of connection options and values based on the personal knowledge response.

24. A network computer for generating a computer visualization of data, comprising: a transceiver that communicates over the network; a non-transitory memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: selecting a visualization model based on at least an allocation model, wherein the visualization model includes one or more visualization model items; mapping one or more allocation model items included in the allocation model to the one or more visualization model items; providing a resource value for each of the one or more visualization model items by at least aggregating an amount of resources corresponding to each of their one or more mapped allocation model items; storing the visualization model in the non-transitory memory of the computer, wherein the visualization model includes one or more resource values for the one or more visualization model items; displaying one or more portions of the visualization model that overlays the allocation model in a user interface of the network computer, wherein the allocation model underlies the visualization model; and when a visualization model item is selected using the user interface of the network computer perform further actions, including: traversing the underlying allocation model to identify one or more source allocation model items and one or more target allocation model items that are associated with the selected visualization model item; providing one or more source visualization model items that provide resources to the selected visualization model item based on the one or more identified source allocation model items; providing one or more target visualization model items that receive resources from the selected visualization model item based on the one or more identified target allocation model items; displaying on the user interface one or more input flow lines that start from the one or more source visualization model items and end at the selected visualization model item; and displaying on the user interface one or more output flow lines that start from the selected visualization model item and end at the one or more target visualization model items.

24. A network computer for generating a computer visualization of data, comprising: a transceiver that communicates over the network; a non-transitory memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: selecting a visualization model based on at least an allocation model, wherein the visualization model includes one or more visualization model items; mapping one or more allocation model items included in the allocation model to the one or more visualization model items; providing a resource value for each of the one or more visualization model items by at least aggregating an amount of resources corresponding to each of their one or more mapped allocation model items; storing the visualization model in the non-transitory memory of the computer, wherein the visualization model includes one or more resource values for the one or more visualization model items; displaying one or more portions of the visualization model that overlays the allocation model in a user interface of the network computer, wherein the allocation model underlies the visualization model; and when a visualization model item is selected using the user interface of the network computer perform further actions, including: traversing the underlying allocation model to identify one or more source allocation model items and one or more target allocation model items that are associated with the selected visualization model item; providing one or more source visualization model items that provide resources to the selected visualization model item based on the one or more identified source allocation model items; providing one or more target visualization model items that receive resources from the selected visualization model item based on the one or more identified target allocation model items; displaying on the user interface one or more input flow lines that start from the one or more source visualization model items and end at the selected visualization model item; and displaying on the user interface one or more output flow lines that start from the selected visualization model item and end at the one or more target visualization model items. 28. The network computer claim 24 , wherein the one or more processor devices execute instructions that perform actions, further comprising, displaying on the user interface each resource value for the one or more visualization model items.

5. The word processing system of claim 1, wherein said detection element comprises a second list of properly-spelled words together with marker means therein, said marker means identifying discrete words of said second list as being duplicates of words in said list of commonly-confused words; and individual memory means comprising said conditioning means and being present in one-to-one correspondence with said discrete words, each said individual memory means normally being in said first state enabling generation of said warning signal and wherein said third control comprises address means associated with each of said discrete words of the second list, said address means locating the individual memory means for selective setting by said operator to said second state disabling generation of said warning signal.

5. The word processing system of claim 1, wherein said detection element comprises a second list of properly-spelled words together with marker means therein, said marker means identifying discrete words of said second list as being duplicates of words in said list of commonly-confused words; and individual memory means comprising said conditioning means and being present in one-to-one correspondence with said discrete words, each said individual memory means normally being in said first state enabling generation of said warning signal and wherein said third control comprises address means associated with each of said discrete words of the second list, said address means locating the individual memory means for selective setting by said operator to said second state disabling generation of said warning signal. 8. The word processing system of claim 5, wherein said second list comprises a spelling dictionary and said marker means is a discrete code following the last character of each word in said spelling dictionary duplicating a word in said list of commonly-confused words.

15. One or more non-transitory computer storage media encoded with a computer program, the computer program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: building an event model by identifying, from user data of one or more applications associated with a user, events related to the user; receiving a voice input from the user that includes a command to perform a specific action, the action having a plurality of parameters, and each parameter specifying information necessary to perform the action; determining whether the voice input includes sufficient information to perform the action; in response to determining that the voice input does not include sufficient information to perform the action, identifying one or more missing parameters from the voice input required to perform the action; identifying, using the event model, one or more current or future events related to the user that are relevant to the action, wherein each current or future event either is (i) currently occurring relative to a time when the voice input was received or (ii) will occur in the future relative to the time when the voice input was received; customizing the action based on the one or more current or future events, comprising assigning values to one or more of the identified missing parameters of the action based on data associated with the one or more current or future events; and performing the customized action in response to the voice input.

15. One or more non-transitory computer storage media encoded with a computer program, the computer program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: building an event model by identifying, from user data of one or more applications associated with a user, events related to the user; receiving a voice input from the user that includes a command to perform a specific action, the action having a plurality of parameters, and each parameter specifying information necessary to perform the action; determining whether the voice input includes sufficient information to perform the action; in response to determining that the voice input does not include sufficient information to perform the action, identifying one or more missing parameters from the voice input required to perform the action; identifying, using the event model, one or more current or future events related to the user that are relevant to the action, wherein each current or future event either is (i) currently occurring relative to a time when the voice input was received or (ii) will occur in the future relative to the time when the voice input was received; customizing the action based on the one or more current or future events, comprising assigning values to one or more of the identified missing parameters of the action based on data associated with the one or more current or future events; and performing the customized action in response to the voice input. 18. The non-transitory computer storage media of claim 15 , wherein: identifying, using the event model, one or more current or future events related to the user that are relevant to the action comprises: identifying user data from the event model that is potentially relevant to the action; determining a level of confidence for an association of the one or more potentially relevant current or future events from the identified user data and the context of the voice input; and identifying one or more current or future events related to the user that are relevant to the action from the potentially relevant events based on the determined level of confidence.

10. A system comprising: one or more server computers comprising a main memory storing an in-memory database, wherein the one or more server computers having one or more processors coupled to the main memory and executing computer readable instructions for a plurality of computer modules including: an entity extraction module configured to receive a user input of partial search query parameters from a user interface, wherein the partial search query parameters having at least one incomplete search query parameter, wherein the user interface is presented on a user computer, wherein the entity extraction module being further configured to: extract one or more first entities, in real-time, as search query data is requested by the user computer, from the partial search query parameters by comparing the partial search query parameters with an entity co-occurrence database having instances of co-occurrence of the one or more first entities in an electronic data corpus and identifying at least one entity type corresponding to the one or more first entities in the partial search query parameters, wherein the in-memory database comprises the entity co-occurrence database, wherein a score is assigned to each extracted feature, wherein the score indicates a level of certainty of the each extracted feature being correctly extracted with a correct attribute; and a fuzzy-score matching module configured to select in real-time, as the search query data is requested by the user computer, a fuzzy matching algorithm for searching the entity co-occurrence database to identify one or more records associated with the partial search query parameters, wherein the fuzzy matching algorithm corresponds to the at least one identified entity type, the fuzzy-score matching module being further configured to: search, in real-time, as the search query data is requested by the user computer, the entity co-occurrence database using the selected fuzzy matching algorithm and form one or more first suggested search query parameters from the one or more records based on the search, and present the one or more first suggested search query parameters to the user interface; wherein the entity extraction module is further configured to: receive a user selection of the one or more first suggested search query parameters from the user interface so as to form completed search query parameters, extract one or more second entities from the completed search query parameters, search the entity co-occurrence database to identify one or more entities related to the one or more second entities so as to form one or more second suggested search query parameters, and present the one or more second suggested search query parameters to the user interface.

10. A system comprising: one or more server computers comprising a main memory storing an in-memory database, wherein the one or more server computers having one or more processors coupled to the main memory and executing computer readable instructions for a plurality of computer modules including: an entity extraction module configured to receive a user input of partial search query parameters from a user interface, wherein the partial search query parameters having at least one incomplete search query parameter, wherein the user interface is presented on a user computer, wherein the entity extraction module being further configured to: extract one or more first entities, in real-time, as search query data is requested by the user computer, from the partial search query parameters by comparing the partial search query parameters with an entity co-occurrence database having instances of co-occurrence of the one or more first entities in an electronic data corpus and identifying at least one entity type corresponding to the one or more first entities in the partial search query parameters, wherein the in-memory database comprises the entity co-occurrence database, wherein a score is assigned to each extracted feature, wherein the score indicates a level of certainty of the each extracted feature being correctly extracted with a correct attribute; and a fuzzy-score matching module configured to select in real-time, as the search query data is requested by the user computer, a fuzzy matching algorithm for searching the entity co-occurrence database to identify one or more records associated with the partial search query parameters, wherein the fuzzy matching algorithm corresponds to the at least one identified entity type, the fuzzy-score matching module being further configured to: search, in real-time, as the search query data is requested by the user computer, the entity co-occurrence database using the selected fuzzy matching algorithm and form one or more first suggested search query parameters from the one or more records based on the search, and present the one or more first suggested search query parameters to the user interface; wherein the entity extraction module is further configured to: receive a user selection of the one or more first suggested search query parameters from the user interface so as to form completed search query parameters, extract one or more second entities from the completed search query parameters, search the entity co-occurrence database to identify one or more entities related to the one or more second entities so as to form one or more second suggested search query parameters, and present the one or more second suggested search query parameters to the user interface. 11. The system of claim 10 wherein the fuzzy-score matching module is further configured to search the entity co-occurrence database using the selected fuzzy matching algorithm before the user input is finalized.

5. A computer-implemented process for graphing social connections among entities' names extracted from general Web pages by creating a 2-D graph with a set of vertices representing names, and a set of edges representing social connections, comprising: using a computing device to perform: receiving a ranked list of social connections between a social graph owner and additional entities obtained from information blocks extracted from the general Web pages, wherein the ranked list was obtained by using a context measure of a relationship and a distance measure of relationship, wherein the context measure of relationship is based on a keyword of a keyword set being found between the name of the social graph owner and a name of an entity in an information block, and wherein the distance measure of relationship is determined by measuring the distance between the name of the social graph owner and a name of an entity; on a display placing the social graph owner in the center of the 2D graph as a center vertex; for each of the additional entities, placing a vertex representing a name of an entity in the ranked list in a difference orbit around the center vertex where the shorter the orbit's radius is, the stronger a social connection between the vertex in the orbit and the center vertex is; clustering the vertices into different clusters according to connectivity between the vertices; placing the vertices in the same cluster closer to each other than to vertices in other clusters; placing clusters of vertices so that clusters of vertices do not overlap each other; and using a force-directed model to improve the uniformity of the 2D layout.

5. A computer-implemented process for graphing social connections among entities' names extracted from general Web pages by creating a 2-D graph with a set of vertices representing names, and a set of edges representing social connections, comprising: using a computing device to perform: receiving a ranked list of social connections between a social graph owner and additional entities obtained from information blocks extracted from the general Web pages, wherein the ranked list was obtained by using a context measure of a relationship and a distance measure of relationship, wherein the context measure of relationship is based on a keyword of a keyword set being found between the name of the social graph owner and a name of an entity in an information block, and wherein the distance measure of relationship is determined by measuring the distance between the name of the social graph owner and a name of an entity; on a display placing the social graph owner in the center of the 2D graph as a center vertex; for each of the additional entities, placing a vertex representing a name of an entity in the ranked list in a difference orbit around the center vertex where the shorter the orbit's radius is, the stronger a social connection between the vertex in the orbit and the center vertex is; clustering the vertices into different clusters according to connectivity between the vertices; placing the vertices in the same cluster closer to each other than to vertices in other clusters; placing clusters of vertices so that clusters of vertices do not overlap each other; and using a force-directed model to improve the uniformity of the 2D layout. 9. The computer-implemented process of claim 5 wherein the force directed model further comprises creating an unpenetratable boundary to isolate the clusters that have no connection to each other.