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9,430,697 | 1 | 4 | 1. A face recognition method on a computing device, comprising: obtaining a plurality of training face images which belongs to a plurality of face classes, wherein a face class includes one or more training face images and represents an identification of the one or more training face images; obtaining a plurality of training dictionaries corresponding to the plurality of training face images, wherein the plurality of training dictionaries include a plurality of deep feature matrices; obtaining an input face image; partitioning the input face image into a plurality of blocks; extracting corresponding deep feature vectors of the plurality of blocks of the input face image using a deep learning network; applying a collaborative representation model to represent the deep feature vectors of the blocks of the input face image with the training dictionaries and representation vectors; computing residual errors for the face classes, a residual error for a face class being a summation of errors for all blocks corresponding to the training face images in the face class, wherein an error for a block exists between a feature vector of the block in the input face image and the collaborative representation model of the block corresponding to the face class; classifying the input face image by selecting a face class that yields a minimum residual error as a recognition face class; and presenting the recognition face class of the input face image. | 1. A face recognition method on a computing device, comprising: obtaining a plurality of training face images which belongs to a plurality of face classes, wherein a face class includes one or more training face images and represents an identification of the one or more training face images; obtaining a plurality of training dictionaries corresponding to the plurality of training face images, wherein the plurality of training dictionaries include a plurality of deep feature matrices; obtaining an input face image; partitioning the input face image into a plurality of blocks; extracting corresponding deep feature vectors of the plurality of blocks of the input face image using a deep learning network; applying a collaborative representation model to represent the deep feature vectors of the blocks of the input face image with the training dictionaries and representation vectors; computing residual errors for the face classes, a residual error for a face class being a summation of errors for all blocks corresponding to the training face images in the face class, wherein an error for a block exists between a feature vector of the block in the input face image and the collaborative representation model of the block corresponding to the face class; classifying the input face image by selecting a face class that yields a minimum residual error as a recognition face class; and presenting the recognition face class of the input face image. 4. The face recognition face recognition method according to claim 1 , wherein: obtaining an input face image further includes: dividing an input video into different sets of frames; detecting faces of each frame in the input video; generating face tracks for the whole video, a face track being a group of detected faces within a same camera take; and obtaining detected faces and face tracks information, wherein the input face image is obtained from the detected faces; and presenting the face class of the input face image further includes outputting a video by adding annotations about the face classes of the detected faces in the input video according to the face tracks. | 0.743958 |
8,396,295 | 2 | 3 | 2. The method for recognizing a handwritten character of claim 1 , wherein the step A comprises the following sub-steps of: A1. gathering handwritten character samples of the character classes, and calculating a discrete coordinate sequence of the trajectory points of the handwritten character samples; A2. pre-processing the discrete coordinate sequence of the trajectory points of the handwritten character samples to obtain a normalized coordinate sequence of the handwritten character samples; A3. extracting eigenvalues according to the normalized coordinate sequence and decomposing vector line sections formed by all adjacent trajectory points into eight standard directions to obtain a multi-dimensional eigenvector of the handwritten character samples; A4. selecting a part of the eigenvalues from the multi-dimensional eigenvector of the samples of all the character classes and calculating first sample centers of the character classes to obtain a coarse classification template composed of the first sample centers of the character classes; and A5. calculating an eigen transformation matrix according to the Fisher criteria, performing eigen transformation on the multi-dimensional eigenvector of the samples of all the character classes by using the eigen transformation matrix, and re-calculating second sample centers of the character classes to obtain a fine classification template composed of the second sample centers of the character classes. | 2. The method for recognizing a handwritten character of claim 1 , wherein the step A comprises the following sub-steps of: A1. gathering handwritten character samples of the character classes, and calculating a discrete coordinate sequence of the trajectory points of the handwritten character samples; A2. pre-processing the discrete coordinate sequence of the trajectory points of the handwritten character samples to obtain a normalized coordinate sequence of the handwritten character samples; A3. extracting eigenvalues according to the normalized coordinate sequence and decomposing vector line sections formed by all adjacent trajectory points into eight standard directions to obtain a multi-dimensional eigenvector of the handwritten character samples; A4. selecting a part of the eigenvalues from the multi-dimensional eigenvector of the samples of all the character classes and calculating first sample centers of the character classes to obtain a coarse classification template composed of the first sample centers of the character classes; and A5. calculating an eigen transformation matrix according to the Fisher criteria, performing eigen transformation on the multi-dimensional eigenvector of the samples of all the character classes by using the eigen transformation matrix, and re-calculating second sample centers of the character classes to obtain a fine classification template composed of the second sample centers of the character classes. 3. The method for recognizing a handwritten character of claim 2 , wherein the sub-step A3 and the step C comprise the following sub-steps of: according to the normalized coordinate sequence, decomposing the vector line sections formed by all the adjacent trajectory points into eight standard directions, and obtaining length values of the vector line sections in each of the standard directions; and processing the obtained length values of the vector line sections, and calculating large-scale eigenvalues and small-scale eigenvalues to obtain a multi-dimensional eigenvector composed of the large-scale eigenvalues and the small-scale eigenvalues. | 0.889474 |
8,234,174 | 1 | 5 | 1. A method for managing inventory sales advertisement information by a host company over a network, comprising the steps of: a. forming an inventory advertisement based information network having at least two tiers of access with at least one host server and at least one remote company user I/O device; b. configuring the host server with an interactive inventory listing builder for generating inventory listings; c. configuring the host server to manage remote company user access to the inventory listings; and d. enabling remote access to the at least one host server for the remote company user to create and manage inventory listings. | 1. A method for managing inventory sales advertisement information by a host company over a network, comprising the steps of: a. forming an inventory advertisement based information network having at least two tiers of access with at least one host server and at least one remote company user I/O device; b. configuring the host server with an interactive inventory listing builder for generating inventory listings; c. configuring the host server to manage remote company user access to the inventory listings; and d. enabling remote access to the at least one host server for the remote company user to create and manage inventory listings. 5. The method of claim 1 , further comprising: a. configuring the host server with an interactive advertisement builder for generating advertisements; and b. enabling the remote company user to manage the advertisement builder and generate advertisements thereby. | 0.741142 |
10,013,787 | 7 | 10 | 7. A system for animating a digital character according to facial expressions of a user, comprising: memory containing a program code; a display coupled to the memory; and one or more processors coupled to the memory and the display, the one or more processors configured to execute the program code, the program code configured to cause the one or more processors to: obtain a first series of two-dimensional (2D) images of a face of a user; obtain a first series of three-dimensional (3D) depth maps of the face of the user; determine a set of blendshape weights associated with a generic expression model based on at least some of the first series of 2D images and at least some of the first series of 3D depth maps, the generic expression model representative of a generic person; identify expression parameters for a user-specific expression model based on at least some of the set of blendshape weights, the user-specific expression model representative of the face of the user; track the face of the user by decoupling rigid motion of the user from non-rigid motion of the user based on at least some of the first series of 2D images and at least some of the first series of 3D depth maps, wherein the rigid motion represents a movement of the 3D depth map of the face of the user and the non-rigid motion represents a change in expression of the face of the user; determine animation parameters for a digital character based on the expression parameters, the rigid and non-rigid motions of the user, and an animation prior, the animation prior including a collection of animation parameters of the digital character, the animation prior indicative of a pre-defined animation of the generic expression model; and animate, based on the animation parameters, the digital character to mimic the face of the user on the display. | 7. A system for animating a digital character according to facial expressions of a user, comprising: memory containing a program code; a display coupled to the memory; and one or more processors coupled to the memory and the display, the one or more processors configured to execute the program code, the program code configured to cause the one or more processors to: obtain a first series of two-dimensional (2D) images of a face of a user; obtain a first series of three-dimensional (3D) depth maps of the face of the user; determine a set of blendshape weights associated with a generic expression model based on at least some of the first series of 2D images and at least some of the first series of 3D depth maps, the generic expression model representative of a generic person; identify expression parameters for a user-specific expression model based on at least some of the set of blendshape weights, the user-specific expression model representative of the face of the user; track the face of the user by decoupling rigid motion of the user from non-rigid motion of the user based on at least some of the first series of 2D images and at least some of the first series of 3D depth maps, wherein the rigid motion represents a movement of the 3D depth map of the face of the user and the non-rigid motion represents a change in expression of the face of the user; determine animation parameters for a digital character based on the expression parameters, the rigid and non-rigid motions of the user, and an animation prior, the animation prior including a collection of animation parameters of the digital character, the animation prior indicative of a pre-defined animation of the generic expression model; and animate, based on the animation parameters, the digital character to mimic the face of the user on the display. 10. The system of claim 7 , wherein the program code to track the non-rigid motion of the user comprises program code to perform an optimization, using the animation prior and the expression parameters, to determine the animation parameters. | 0.572695 |
9,298,850 | 15 | 16 | 15. An apparatus for computing excluded data, the apparatus comprising: a communications fabric; a memory connected to the communications fabric, wherein the memory contains computer executable program code; a communications unit connected to the communications fabric; an input/output unit connected to the communications fabric; a display connected to the communications fabric; and a processor unit connected to the communications fabric, wherein the processor unit executes the computer executable program code to direct the apparatus to: identify a web page of interest to form an identified page; load the identified page a first time to form a first load; responsive to a determination that a delta has not been computed for the identified web page, load the identified page a second time to form a second load; wherein the second load is based, at least in part, upon the use of a proxy; determine whether portions of the first load differ from portions of the second load; responsive to a determination portions of the first load differ from portions of the second load, identify the portions that differ to form a delta; store the delta to form a stored delta; exclude the stored delta from a document object model associated with the identified page to form a modified document object model; exclude the stored delta from a document object model comparison process, wherein the document object model comparison process from which the stored delta is excluded is a document object model equivalence function, wherein the excluded stored delta includes one or more page sections ignored by crawlers; and if the identified page is part of a rich Internet application, add the identified page to a rich Internet application model. | 15. An apparatus for computing excluded data, the apparatus comprising: a communications fabric; a memory connected to the communications fabric, wherein the memory contains computer executable program code; a communications unit connected to the communications fabric; an input/output unit connected to the communications fabric; a display connected to the communications fabric; and a processor unit connected to the communications fabric, wherein the processor unit executes the computer executable program code to direct the apparatus to: identify a web page of interest to form an identified page; load the identified page a first time to form a first load; responsive to a determination that a delta has not been computed for the identified web page, load the identified page a second time to form a second load; wherein the second load is based, at least in part, upon the use of a proxy; determine whether portions of the first load differ from portions of the second load; responsive to a determination portions of the first load differ from portions of the second load, identify the portions that differ to form a delta; store the delta to form a stored delta; exclude the stored delta from a document object model associated with the identified page to form a modified document object model; exclude the stored delta from a document object model comparison process, wherein the document object model comparison process from which the stored delta is excluded is a document object model equivalence function, wherein the excluded stored delta includes one or more page sections ignored by crawlers; and if the identified page is part of a rich Internet application, add the identified page to a rich Internet application model. 16. The apparatus of claim 15 wherein the processor unit executes the computer executable program code, responsive to a determination that a delta has been computed for the identified web page, to load the identified page a second time to form a second load further directs the apparatus to: load the identified page one or more times at distinct points in time after loading the identified page the first time to form the first load, wherein a time interval between the first load and the second load is predetermined. | 0.500962 |
6,023,578 | 1 | 12 | 1. A method for generating an object oriented application for an object oriented environment, said object oriented environment comprising a programming model and a data model, said method comprising the steps of: generating a computer program design for said object oriented model application using a modeling tool; and mapping the modeling tool generated computer program design to the data model of said object oriented environment to thereby create metadata in said data model wherein said mapping step comprises defining a first package, wherein said first package partitions the computer program design into at least two parts without requiring reference to model semantics. | 1. A method for generating an object oriented application for an object oriented environment, said object oriented environment comprising a programming model and a data model, said method comprising the steps of: generating a computer program design for said object oriented model application using a modeling tool; and mapping the modeling tool generated computer program design to the data model of said object oriented environment to thereby create metadata in said data model wherein said mapping step comprises defining a first package, wherein said first package partitions the computer program design into at least two parts without requiring reference to model semantics. 12. The generating method of claim 1, wherein said computer program design mapping step is followed by the step of generating code based on the metadata. | 0.925439 |
8,843,359 | 1 | 8 | 1. A computer-implemented method of translating text from a source language to a target language comprising the steps of: (a) detecting a source language on a first communication device; (b) detecting a location of the first communication device; (c) determining the target language based upon the detected location of the first communication device; (d) receiving an input for translation from the first communication device; (e) displaying a list of popular source phrases that are similar to the received input on the first communication device; (f) translating a user selected similar popular source phrase if the user selects the similar popular source phrase, else translating the input by means of a machine translation engine; and (g) displaying the translation output of the user selected similar popular source phrase if the user selected the similar popular source phrase, else determining if the translation output from the machine translation engine has been approved by a human translator, submitting the translation output from the machine translation engine to a human translator and displaying the translation output from the machine translation engine together with a measure of the accuracy of the translation output from the machine translation engine. | 1. A computer-implemented method of translating text from a source language to a target language comprising the steps of: (a) detecting a source language on a first communication device; (b) detecting a location of the first communication device; (c) determining the target language based upon the detected location of the first communication device; (d) receiving an input for translation from the first communication device; (e) displaying a list of popular source phrases that are similar to the received input on the first communication device; (f) translating a user selected similar popular source phrase if the user selects the similar popular source phrase, else translating the input by means of a machine translation engine; and (g) displaying the translation output of the user selected similar popular source phrase if the user selected the similar popular source phrase, else determining if the translation output from the machine translation engine has been approved by a human translator, submitting the translation output from the machine translation engine to a human translator and displaying the translation output from the machine translation engine together with a measure of the accuracy of the translation output from the machine translation engine. 8. The method of claim 1 , further comprising requesting a context for the input from the user. | 0.856928 |
9,444,773 | 16 | 24 | 16. A system comprising: a data repository that stores language capabilities of users within a pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and an analysis engine comprising a processor, the analysis engine configured to: receive data entered at a user interface of a user device by a first user associated with the pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested, determine, using data from the data repository, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, and cause an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to be transmitted to the user device for display on the user interface; wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group. | 16. A system comprising: a data repository that stores language capabilities of users within a pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and an analysis engine comprising a processor, the analysis engine configured to: receive data entered at a user interface of a user device by a first user associated with the pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested, determine, using data from the data repository, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, and cause an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to be transmitted to the user device for display on the user interface; wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group. 24. The system of claim 16 , wherein the electronic documents comprise one or more of emails and documents attached to emails. | 0.89322 |
4,441,201 | 9 | 10 | 9. The speech synthesis system according to claim 8, wherein said operator input means comprises a keyboard having a plurality of operator actuatable key switches. | 9. The speech synthesis system according to claim 8, wherein said operator input means comprises a keyboard having a plurality of operator actuatable key switches. 10. The speech synthesis system according to claim 9, wherein said speech synthesis system comprises a portable learning aid. | 0.970196 |
8,250,169 | 10 | 11 | 10. An article of manufacture comprising a machine readable storage medium having content stored thereon to provide instructions to cause a machine to perform operations including: accessing, at a client device, business context data received from a server, the business context data describing a resource, a view, and actionable context data related to a business scenario, the business context data including an instance of at least one data object, the instance generated from a model of the data object and enriched with metadata identifying the business scenario, the business scenario providing an end business purpose for a work action, the business context data not specific to a particular user interface (UI) type, without UI model or UI information in the business context data, wherein the resource includes a functional resource used to perform the work action, wherein the view includes a metadata definition of a generic presentation form to be processed to render the business context data in a UI, wherein the actionable context data includes interactive content to perform the work action and cause an action at the server, and wherein the type includes interface hardware and associated drivers; processing the business context data to determine a UI component to generate to represent a portion of the business context data, the UI component having graphical user interface (GUI) elements with interfaces to render the view on the business context data; generating the UI component based on the business scenario and based on a UI type available on the client device and a data processing control layer at the client device, the component being specific to the UI type available on the client device, to render the view on the business context data from the generic presentation form to a format supported by the UI type available on the client device; and rendering the UI component in a desktop widget to provide access to the actionable context data on the client device, where an operation on the instance of the business context data is to cause the operation to be applied to the data at the server. | 10. An article of manufacture comprising a machine readable storage medium having content stored thereon to provide instructions to cause a machine to perform operations including: accessing, at a client device, business context data received from a server, the business context data describing a resource, a view, and actionable context data related to a business scenario, the business context data including an instance of at least one data object, the instance generated from a model of the data object and enriched with metadata identifying the business scenario, the business scenario providing an end business purpose for a work action, the business context data not specific to a particular user interface (UI) type, without UI model or UI information in the business context data, wherein the resource includes a functional resource used to perform the work action, wherein the view includes a metadata definition of a generic presentation form to be processed to render the business context data in a UI, wherein the actionable context data includes interactive content to perform the work action and cause an action at the server, and wherein the type includes interface hardware and associated drivers; processing the business context data to determine a UI component to generate to represent a portion of the business context data, the UI component having graphical user interface (GUI) elements with interfaces to render the view on the business context data; generating the UI component based on the business scenario and based on a UI type available on the client device and a data processing control layer at the client device, the component being specific to the UI type available on the client device, to render the view on the business context data from the generic presentation form to a format supported by the UI type available on the client device; and rendering the UI component in a desktop widget to provide access to the actionable context data on the client device, where an operation on the instance of the business context data is to cause the operation to be applied to the data at the server. 11. The article of manufacture of claim 10 , wherein the content to provide instructions for receiving the business context data comprises content to provide instructions for receiving a meta object that includes business objects from multiple different backend systems; and wherein the content to provide instructions for rendering the UI component in the desktop widget comprises content to provide instructions for rendering multiple business objects in the desktop widget to provide access to data and functionality of the multiple business objects. | 0.500903 |
10,083,009 | 12 | 17 | 12. A computer program product, comprising a non-transitory computer-readable medium having a computer-readable program code embodied therein to be executed by one or more processors, the program code including instructions to: form an intent based on a user input using a natural language intent interpreter, the intent being associated with an input concept object; create a first plan based on the intent, the first plan comprising a first input action object that transforms the input concept object into an intermediate concept object and a first output action object that transforms another intermediate concept object into an output concept object associated with a goal of the intent, the other intermediate concept object comprising one of a same object as the intermediate concept object and a different object from the intermediate concept object, the first input action object and the first output action object being selected from a plurality of action objects; create a second plan based on the intent, wherein the second plan comprises a second input action object that transforms the input concept object into an alternative intermediate concept object and a second output action object that transforms another alternative intermediate concept object into the output concept object associated with the goal of the intent, the other alternative intermediate concept object comprising one of a same object as the alternative intermediate concept object and a different object from the alternative intermediate concept object, the second input action object and the second output action object being selected from the plurality of action objects; compare the first plan with the second plan, the first plan and the second plan each having an action object cost, an action quality cost, and a number of planned action objects; select a plan from the first plan and the second plan for execution based on the comparison of the first plan to the second plan, the selected plan having at least one of a lower action object cost, a best action object quality, and a fewer number of planned action objects; execute the selected plan, and output a value associated with the output concept object of the selected plan. | 12. A computer program product, comprising a non-transitory computer-readable medium having a computer-readable program code embodied therein to be executed by one or more processors, the program code including instructions to: form an intent based on a user input using a natural language intent interpreter, the intent being associated with an input concept object; create a first plan based on the intent, the first plan comprising a first input action object that transforms the input concept object into an intermediate concept object and a first output action object that transforms another intermediate concept object into an output concept object associated with a goal of the intent, the other intermediate concept object comprising one of a same object as the intermediate concept object and a different object from the intermediate concept object, the first input action object and the first output action object being selected from a plurality of action objects; create a second plan based on the intent, wherein the second plan comprises a second input action object that transforms the input concept object into an alternative intermediate concept object and a second output action object that transforms another alternative intermediate concept object into the output concept object associated with the goal of the intent, the other alternative intermediate concept object comprising one of a same object as the alternative intermediate concept object and a different object from the alternative intermediate concept object, the second input action object and the second output action object being selected from the plurality of action objects; compare the first plan with the second plan, the first plan and the second plan each having an action object cost, an action quality cost, and a number of planned action objects; select a plan from the first plan and the second plan for execution based on the comparison of the first plan to the second plan, the selected plan having at least one of a lower action object cost, a best action object quality, and a fewer number of planned action objects; execute the selected plan, and output a value associated with the output concept object of the selected plan. 17. The computer program product of claim 12 , wherein the user input is provided via at least one of typed entry of text via a keyboard, touch gestures, mouse gestures, and speech. | 0.670909 |
9,672,247 | 11 | 13 | 11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to translate a first query into an edge query, the program module including: instructions for receiving the first query, wherein the first query is associated with a first type of database; instructions for translating the first query into the edge query, wherein: the edge query is associated with a graph database storing a graph; and the graph comprises nodes, edges between the nodes, and predicates to represent data with index-free adjacency; instructions for executing the edge query against the graph database, wherein the edge query identifies an edge associated with a predicate that specifies one or more of the nodes of the graph; and instructions for receiving a result in response to the edge query. | 11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to translate a first query into an edge query, the program module including: instructions for receiving the first query, wherein the first query is associated with a first type of database; instructions for translating the first query into the edge query, wherein: the edge query is associated with a graph database storing a graph; and the graph comprises nodes, edges between the nodes, and predicates to represent data with index-free adjacency; instructions for executing the edge query against the graph database, wherein the edge query identifies an edge associated with a predicate that specifies one or more of the nodes of the graph; and instructions for receiving a result in response to the edge query. 13. The apparatus of claim 11 , wherein the first type of database includes one of: a relational database, and a hierarchical database. | 0.811978 |
8,527,874 | 11 | 18 | 11. A system for grouping search results using information representations, the system comprising: a server computer having a processor, memory, and a graphical user interface for displaying at least one tile that graphically represents at least one user in response to an input for selecting an object associated with the at least one user, wherein the selected object has a first object type; the server computer configured to perform operations for: a correlation determining system, the operations performed by the server computer for the correlation determining system including: determining a chronological timeline that represents a plurality of actions performed by the at least one user wherein the plurality of actions performed by the at least one user have a plurality of chronological positions in the chronological timeline; and inferring one or more relationships between the selected object and one or more other objects associated with the at least one user from the plurality of actions represented in the chronological timeline, wherein inferring the one or more relationships comprises: identifies identifying one or more of the plurality of actions that are related to the selected object from the plurality of chronological positions that the plurality of actions have in the chronological timeline, wherein the at least one user performed the identified one or more actions on the one or more other objects, and wherein the one or more other objects have a second object type different from the first object type; and determining that the one or more other objects are related to the selected object from a strength of the one or more inferred relationships, wherein the strength of the one or more inferred relationships is derived from the chronological positions that the identified one or more actions have in the chronological timeline; and a tile generator, the operations performed by the server computer for the tile generator including: generating one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user in response to a selection of the at least one tile that graphically represents the at least one user; and causing the graphical user interface to simultaneously display the one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user, wherein the graphical user interface further organizes the at least one tile and the one or more additional tiles based on the first object type for the selected object and the second object type for the one or more other objects. | 11. A system for grouping search results using information representations, the system comprising: a server computer having a processor, memory, and a graphical user interface for displaying at least one tile that graphically represents at least one user in response to an input for selecting an object associated with the at least one user, wherein the selected object has a first object type; the server computer configured to perform operations for: a correlation determining system, the operations performed by the server computer for the correlation determining system including: determining a chronological timeline that represents a plurality of actions performed by the at least one user wherein the plurality of actions performed by the at least one user have a plurality of chronological positions in the chronological timeline; and inferring one or more relationships between the selected object and one or more other objects associated with the at least one user from the plurality of actions represented in the chronological timeline, wherein inferring the one or more relationships comprises: identifies identifying one or more of the plurality of actions that are related to the selected object from the plurality of chronological positions that the plurality of actions have in the chronological timeline, wherein the at least one user performed the identified one or more actions on the one or more other objects, and wherein the one or more other objects have a second object type different from the first object type; and determining that the one or more other objects are related to the selected object from a strength of the one or more inferred relationships, wherein the strength of the one or more inferred relationships is derived from the chronological positions that the identified one or more actions have in the chronological timeline; and a tile generator, the operations performed by the server computer for the tile generator including: generating one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user in response to a selection of the at least one tile that graphically represents the at least one user; and causing the graphical user interface to simultaneously display the one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user, wherein the graphical user interface further organizes the at least one tile and the one or more additional tiles based on the first object type for the selected object and the second object type for the one or more other objects. 18. The system of claim 11 , wherein the operations performed by the server computer for the correlation determining system further include: deriving the strength of the one or more inferred relationships based on content of the selected object, content of the one or more other objects, or a combination of both. | 0.723009 |
7,606,428 | 1 | 12 | 1. A computer readable recording medium having encoded thereon an XMT (extensible MPEG-4 textual format) schema for DIBR data, the XMT schema comprising: a BitWrapper node schema used for graphics data compression; and a DepthImage node schema, which is used for depthimage-based model rendering, includes camera information and texture information having a depth information, defines diTexture as an element including SFDepthTextureNode as a model group, wherein the BitWrapper node schema comprises: a node element, which contains graphics data including data to be compressed and refers to SFWorldNode as a subelement; a BitWrapperEncodingParameter element; and three attributes having the names type, url, and buffer and the types SFInt32, MFUrl, and SFString, respectively, and the camera information of the depthimage node schema defines at least one of position, orientation, fieldOfView, nearPlane, farPlane, and orthographic as an attribute name, and attribute types defined in the camera information include SFVec3f, SFRotation, SFVec2f, SFFloat, SFFloat, and SFBool, respectively. | 1. A computer readable recording medium having encoded thereon an XMT (extensible MPEG-4 textual format) schema for DIBR data, the XMT schema comprising: a BitWrapper node schema used for graphics data compression; and a DepthImage node schema, which is used for depthimage-based model rendering, includes camera information and texture information having a depth information, defines diTexture as an element including SFDepthTextureNode as a model group, wherein the BitWrapper node schema comprises: a node element, which contains graphics data including data to be compressed and refers to SFWorldNode as a subelement; a BitWrapperEncodingParameter element; and three attributes having the names type, url, and buffer and the types SFInt32, MFUrl, and SFString, respectively, and the camera information of the depthimage node schema defines at least one of position, orientation, fieldOfView, nearPlane, farPlane, and orthographic as an attribute name, and attribute types defined in the camera information include SFVec3f, SFRotation, SFVec2f, SFFloat, SFFloat, and SFBool, respectively. 12. A computer readable recording medium having encoded thereon an XMT style sheet for parsing an input XMT (extensible MPEG-4 textual format) file including depth image-based representation (DIBR) data using a schema of claim 1 for the DIBR data, the XMT style sheet comprising: an XMT2BIFS style sheet used to generate a scene file for the DIBR data; and an XMT2MUX style sheet used to generate an mux file for the DIBR data. | 0.68695 |
8,150,698 | 1 | 3 | 1. A method for invoking tapered prompts in a multimodal application, the method implemented with a multimodal browser and a multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the method comprising acts of: identifying a first prompt element and a second prompt element of a tapered prompt associated with a multimodal application; rendering, in a first style, a first multimodal prompt associated with the first prompt element, the first multimodal prompt comprising a first speech prompt and a first non-speech prompt, the first style comprising a first speech style for the first speech prompt and a first non-speech style for the first non-speech prompt; and rendering, in a second style, a second multimodal prompt associated with the second prompt element, the second multimodal prompt comprising a second speech prompt and a second non-speech prompt, the second non-speech prompt having content that is different from content of the first non-speech prompt, the second style comprising a second speech style for the second speech prompt and a second non-speech style for the second non-speech prompt, the second speech style being different from the first speech style, the second non-speech style being different from the first non-speech style and being selected in conjunction with the second speech style. | 1. A method for invoking tapered prompts in a multimodal application, the method implemented with a multimodal browser and a multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the method comprising acts of: identifying a first prompt element and a second prompt element of a tapered prompt associated with a multimodal application; rendering, in a first style, a first multimodal prompt associated with the first prompt element, the first multimodal prompt comprising a first speech prompt and a first non-speech prompt, the first style comprising a first speech style for the first speech prompt and a first non-speech style for the first non-speech prompt; and rendering, in a second style, a second multimodal prompt associated with the second prompt element, the second multimodal prompt comprising a second speech prompt and a second non-speech prompt, the second non-speech prompt having content that is different from content of the first non-speech prompt, the second style comprising a second speech style for the second speech prompt and a second non-speech style for the second non-speech prompt, the second speech style being different from the first speech style, the second non-speech style being different from the first non-speech style and being selected in conjunction with the second speech style. 3. The method of claim 1 wherein the first prompt element is associated with a prompt counter shadow variable and a source expression attribute whose value depends upon a value of the prompt counter shadow variable; and wherein the act of rendering the first multimodal prompt comprises identifying the first speech prompt based at least in part on the value of the source expression attribute. | 0.730506 |
8,166,161 | 8 | 10 | 8. Logic encoded in one or more non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving data propagating in a network environment; verifying whether the data is associated with a first end user represented in a registered user list; verifying a ratification of a policy by the first end user that authorizes monitoring of e-mail traffic generated by the first end user; identifying selected words within the data based on a whitelist, wherein the whitelist includes a plurality of designated words to be tagged; and generating a resultant composite of the selected words that are tagged. | 8. Logic encoded in one or more non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving data propagating in a network environment; verifying whether the data is associated with a first end user represented in a registered user list; verifying a ratification of a policy by the first end user that authorizes monitoring of e-mail traffic generated by the first end user; identifying selected words within the data based on a whitelist, wherein the whitelist includes a plurality of designated words to be tagged; and generating a resultant composite of the selected words that are tagged. 10. The logic of claim 8 , the processor being further operable to perform operations comprising: verifying whether the data is associated with a business uniform resource locator (URL) domain, wherein if the data is associated with the business URL domain, one or more words in the data are tagged. | 0.665548 |
9,152,998 | 1 | 2 | 1. A method of retrieving data from a data store according to a user intent, the method comprising: receiving a query in an intermediate language, the intermediate language specific to a vertical domain, the query comprising multiple query terms from a user expressing the user's intent, the multiple query terms associated with the vertical domain; selecting a parser from a plurality of parsers, the parser configured to support the multiple query terms associated with the vertical domain; parsing the intermediate language query into the multiple query terms using the parser; and converting the multiple query terms to a data retrieval language query using a processor, the data retrieval language query having data retrieval terms specific to retrieving data from the data store, the data retrieval terms configured to operate directly against the data store. | 1. A method of retrieving data from a data store according to a user intent, the method comprising: receiving a query in an intermediate language, the intermediate language specific to a vertical domain, the query comprising multiple query terms from a user expressing the user's intent, the multiple query terms associated with the vertical domain; selecting a parser from a plurality of parsers, the parser configured to support the multiple query terms associated with the vertical domain; parsing the intermediate language query into the multiple query terms using the parser; and converting the multiple query terms to a data retrieval language query using a processor, the data retrieval language query having data retrieval terms specific to retrieving data from the data store, the data retrieval terms configured to operate directly against the data store. 2. The method of claim 1 , wherein the vertical domain of the intermediate language is that of investor relations. | 0.836676 |
9,558,473 | 3 | 5 | 3. The method of claim 1 , further comprising: obtaining a set of selected contacts, the set of selected contacts comprising a subset of the set of candidate contacts; and requesting a collaboration session with each selected contact in the set of selected contacts. | 3. The method of claim 1 , further comprising: obtaining a set of selected contacts, the set of selected contacts comprising a subset of the set of candidate contacts; and requesting a collaboration session with each selected contact in the set of selected contacts. 5. The method of claim 3 , further comprising conducting the collaboration session with each of the set of selected contacts. | 0.962462 |
8,340,405 | 7 | 10 | 7. A non-transitory computer readable storage medium, storing one or more programs for execution by one or more processors, the one or more programs comprising instructions for: identifying a plurality of first features of a plurality of first digital files having one or more associated annotations; partitioning the plurality of first features into a plurality of subsets of the first features, including a respective subset of the first features; generating one or more classifiers based on the respective subset of the first features; identifying a plurality of second features of a respective second digital file; for each respective first digital file of two or more of the plurality of first digital files, determining a distance vector corresponding to a respective partial distance between a representation of features of the respective second digital file and a representation of features of the respective first digital file using a respective classifier; identifying a subset of the plurality of first digital files as candidate nearest neighbors to the respective second digital file based on the partial distances; determining scores corresponding to full distances between features of a plurality of the candidate nearest neighbors and features of the respective second digital file and ranking the determined scores; selecting a subset of the candidate nearest neighbors as matched files based on the ranking, wherein the matched files are associated with a respective annotation; and associating the respective annotation with the respective second digital file. | 7. A non-transitory computer readable storage medium, storing one or more programs for execution by one or more processors, the one or more programs comprising instructions for: identifying a plurality of first features of a plurality of first digital files having one or more associated annotations; partitioning the plurality of first features into a plurality of subsets of the first features, including a respective subset of the first features; generating one or more classifiers based on the respective subset of the first features; identifying a plurality of second features of a respective second digital file; for each respective first digital file of two or more of the plurality of first digital files, determining a distance vector corresponding to a respective partial distance between a representation of features of the respective second digital file and a representation of features of the respective first digital file using a respective classifier; identifying a subset of the plurality of first digital files as candidate nearest neighbors to the respective second digital file based on the partial distances; determining scores corresponding to full distances between features of a plurality of the candidate nearest neighbors and features of the respective second digital file and ranking the determined scores; selecting a subset of the candidate nearest neighbors as matched files based on the ranking, wherein the matched files are associated with a respective annotation; and associating the respective annotation with the respective second digital file. 10. The computer readable storage medium of claim 7 , wherein the one or more programs further comprise instructions for: generating a plurality of classifiers from the plurality of first features; applying the respective second digital file to the plurality of classifiers and determining a weight value corresponding to each of the plurality of classifiers; combining the weight values corresponding to one or more of the classifiers; and associating one or more annotations from a respective subset of matched files to the respective second digital file based on the combined weight values. | 0.764496 |
9,076,441 | 1 | 3 | 1. A speech recognition circuit comprising: a circuit for providing state identifiers which identify states corresponding to nodes or groups of adjacent nodes in a lexical tree, and for providing scores corresponding to said state identifiers, the lexical tree comprising a model of words; a memory structure for receiving and storing state identifiers identified by a node identifier identifying a node or group of adjacent nodes, said memory structure being adapted to allow lookup to identify particular state identifiers, reading of the scores corresponding to the state identifiers, and writing back of the scores to the memory structure after modification of the scores; an accumulator for receiving score updates corresponding to particular state identifiers from a score update generating circuit which generates the score updates using audio input, for receiving scores from the memory structure, and for modifying said scores by adding said score updates to said scores; and a selector circuit for selecting at least one node or group of adjacent nodes of the lexical tree according to said scores. | 1. A speech recognition circuit comprising: a circuit for providing state identifiers which identify states corresponding to nodes or groups of adjacent nodes in a lexical tree, and for providing scores corresponding to said state identifiers, the lexical tree comprising a model of words; a memory structure for receiving and storing state identifiers identified by a node identifier identifying a node or group of adjacent nodes, said memory structure being adapted to allow lookup to identify particular state identifiers, reading of the scores corresponding to the state identifiers, and writing back of the scores to the memory structure after modification of the scores; an accumulator for receiving score updates corresponding to particular state identifiers from a score update generating circuit which generates the score updates using audio input, for receiving scores from the memory structure, and for modifying said scores by adding said score updates to said scores; and a selector circuit for selecting at least one node or group of adjacent nodes of the lexical tree according to said scores. 3. The speech recognition circuit of claim 1 , wherein the lexical tree is arranged with each node corresponding to a phone, and each said state corresponds to a phone or group of adjacent phones in the lexical tree. | 0.849372 |
8,280,823 | 261 | 271 | 261. A graphical user interface, comprising: a first data entry region including at least one required phrase; a second data entry region including a search string comprising at least one search phrase, each said at least one search phrase including one of said at least one required phrase, wherein a one-to-one mapping exists between said at least one search phrase and said at least one required phrase; and a search button operative to send a database query to a database, the database query including the search string, wherein the database includes at least one resume, and a parsed resume associated with each resume, wherein each resume includes at least one skill or experience-related phrase, wherein each skill or experience-related phrase has an experience range determined by examining a use of the skill or experience-related phrase in the resume, and a term of experience based on the experience range, wherein the term of experience for each skill or experience-related phrase having multiple occurrences in the resume is a summation of the term of experience, or a portion of the term of experience, for each occurrence of the skill or experience-related phrase associated with a different experience range, wherein each parsed resume includes each said at least one skill or experience-related phrase located in the resume, the term of experience for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase, and wherein in response to clicking the search button, a processor sends the database query and receives a result set that includes at least one matching resume, each matching resume is one of said at least one resume having the parsed resume associated with the matching resume satisfying the search string. | 261. A graphical user interface, comprising: a first data entry region including at least one required phrase; a second data entry region including a search string comprising at least one search phrase, each said at least one search phrase including one of said at least one required phrase, wherein a one-to-one mapping exists between said at least one search phrase and said at least one required phrase; and a search button operative to send a database query to a database, the database query including the search string, wherein the database includes at least one resume, and a parsed resume associated with each resume, wherein each resume includes at least one skill or experience-related phrase, wherein each skill or experience-related phrase has an experience range determined by examining a use of the skill or experience-related phrase in the resume, and a term of experience based on the experience range, wherein the term of experience for each skill or experience-related phrase having multiple occurrences in the resume is a summation of the term of experience, or a portion of the term of experience, for each occurrence of the skill or experience-related phrase associated with a different experience range, wherein each parsed resume includes each said at least one skill or experience-related phrase located in the resume, the term of experience for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase, and wherein in response to clicking the search button, a processor sends the database query and receives a result set that includes at least one matching resume, each matching resume is one of said at least one resume having the parsed resume associated with the matching resume satisfying the search string. 271. The graphical user interface of claim 261 , wherein to satisfy the search string, the parsed resume associated with each said at least one matching resume includes each said at least one search phrase. | 0.772124 |
9,411,855 | 4 | 5 | 4. The method recited in claim 2 , wherein the first entity is an information service provider providing information services to a plurality of recipients. | 4. The method recited in claim 2 , wherein the first entity is an information service provider providing information services to a plurality of recipients. 5. The method recited in claim 4 , wherein the second entity is one of the plurality of recipients. | 0.966689 |
9,588,966 | 7 | 9 | 7. The method of claim 1 further comprising using the engine training data to train a classifier component of an engine to perform automated language processing functions. | 7. The method of claim 1 further comprising using the engine training data to train a classifier component of an engine to perform automated language processing functions. 9. The method of claim 7 , wherein the trained engine is a machine translation engine that performs automated language translation processing functions. | 0.965025 |
9,247,015 | 2 | 3 | 2. The method of claim 1 , further comprising selecting the context from a plurality of contexts based on a relevance of the context to the member in comparison to a relevance of an additional context of the plurality of contexts to the member. | 2. The method of claim 1 , further comprising selecting the context from a plurality of contexts based on a relevance of the context to the member in comparison to a relevance of an additional context of the plurality of contexts to the member. 3. The method of claim 2 , wherein the selecting the context from the plurality of contexts is further based on information specified by the member in a profile of the member. | 0.942661 |
9,606,969 | 1 | 2 | 1. A computer implemented method for customizing the size of content displayed by a web browser at a view-based level based on user preference, the method comprising the steps of: receiving a minimum font size to display for a specific user; monitoring retrieval of webpages by the web browser on a computer system, wherein a retrieved webpage comprises multiple views, wherein a view of a webpage comprises content to be displayed by the browser while at a current scrolled position in the webpage; prior to displaying a specific view of the retrieved webpage, resizing text in the specific view by examining all of the text in the specific view of the retrieved webpage and dynamically calculating font sizes for the text in the specific view of the retrieved webpage based on the minimum font size for the specific user, so that size proportionality between different font sizes in the specific view is maintained; displaying the specific view of the retrieved webpage with the resized text to the specific user; and as the specific user scrolls to additional views of the retrieved webpage, prior to displaying each specific additional view, resizing text in the specific additional view based on the minimum font size, and displaying the specific additional view of the retrieved webpage with the resized text to the specific user. | 1. A computer implemented method for customizing the size of content displayed by a web browser at a view-based level based on user preference, the method comprising the steps of: receiving a minimum font size to display for a specific user; monitoring retrieval of webpages by the web browser on a computer system, wherein a retrieved webpage comprises multiple views, wherein a view of a webpage comprises content to be displayed by the browser while at a current scrolled position in the webpage; prior to displaying a specific view of the retrieved webpage, resizing text in the specific view by examining all of the text in the specific view of the retrieved webpage and dynamically calculating font sizes for the text in the specific view of the retrieved webpage based on the minimum font size for the specific user, so that size proportionality between different font sizes in the specific view is maintained; displaying the specific view of the retrieved webpage with the resized text to the specific user; and as the specific user scrolls to additional views of the retrieved webpage, prior to displaying each specific additional view, resizing text in the specific additional view based on the minimum font size, and displaying the specific additional view of the retrieved webpage with the resized text to the specific user. 2. The method of claim 1 wherein receiving a minimum font size to display for a specific user further comprises: prompting the specific user to enter a desired minimum font size through a user interface. | 0.852685 |
9,430,570 | 1 | 3 | 1. A system for creating a personal ranking of specific to a user information, the system comprising: an interface for interfacing with online data, stored user data, and user device data; a processor executing an application to configured for analyzing information derived or inferred at least in part from the online data, the stored user data, and the user device data, wherein the analysis incorporates criteria derived or inferred from both the stored user data and the user device data; a database, the database configured for storing data relating to inputs and/or outputs of the relevance engine or the application, wherein the relevance engine is further configured for generating a series of personalised attention rankings outputs accessible by the user device by applying both a user-specific attention profile and a user-specific psychometric profile in producing machine readable, user-specific attention ranking of the online data; and further wherein the personalised attention rankings outputs are generated at least partially in response to changes in the personalised attention profile outputs or changes in the personalised the psychometric profile outputs specific to the user. | 1. A system for creating a personal ranking of specific to a user information, the system comprising: an interface for interfacing with online data, stored user data, and user device data; a processor executing an application to configured for analyzing information derived or inferred at least in part from the online data, the stored user data, and the user device data, wherein the analysis incorporates criteria derived or inferred from both the stored user data and the user device data; a database, the database configured for storing data relating to inputs and/or outputs of the relevance engine or the application, wherein the relevance engine is further configured for generating a series of personalised attention rankings outputs accessible by the user device by applying both a user-specific attention profile and a user-specific psychometric profile in producing machine readable, user-specific attention ranking of the online data; and further wherein the personalised attention rankings outputs are generated at least partially in response to changes in the personalised attention profile outputs or changes in the personalised the psychometric profile outputs specific to the user. 3. The system according to claim 1 , wherein the application further comprises an ontology repository containing a list of ontologies. | 0.859833 |
4,860,219 | 14 | 18 | 14. A printing system comprising: (a) a font storage means including a font storage memory for storing a plurality of characters to be printed, each stored character being comprised of a matrix of pixels contained in a plurality of lines having a first line, a plurality of intermediate lines, and a last line, each line having one or more successively addressed words, with the beginning word having a lowest address, with each successive word having a higher address, and with a last word having the highest address, each word having a plurality of pixels; (b) means, coupled to the font storage means, for causing the readout of words stored in the font storage memory in either a first direction or a second direction, the first direction being from the first line thru the last line with each line being read out in a direction from the lowest addressed word to the highest addressed word and the second direction being from the last line thru the first line with each line being read out in a direction from the highest addressed word to the lowest addressed word, and the storage of the words of a character, which have been readout from the font storage memory, in a page memory contained within a raster storage means which stores one or more pages of information to be printed; and (c) printing means, coupled to the raster storage means, for printing on a printing medium pages of information stored in the page memory. | 14. A printing system comprising: (a) a font storage means including a font storage memory for storing a plurality of characters to be printed, each stored character being comprised of a matrix of pixels contained in a plurality of lines having a first line, a plurality of intermediate lines, and a last line, each line having one or more successively addressed words, with the beginning word having a lowest address, with each successive word having a higher address, and with a last word having the highest address, each word having a plurality of pixels; (b) means, coupled to the font storage means, for causing the readout of words stored in the font storage memory in either a first direction or a second direction, the first direction being from the first line thru the last line with each line being read out in a direction from the lowest addressed word to the highest addressed word and the second direction being from the last line thru the first line with each line being read out in a direction from the highest addressed word to the lowest addressed word, and the storage of the words of a character, which have been readout from the font storage memory, in a page memory contained within a raster storage means which stores one or more pages of information to be printed; and (c) printing means, coupled to the raster storage means, for printing on a printing medium pages of information stored in the page memory. 18. A printing system in accordance with claim 14, further comprising: (a) a processing unit, coupled to the font storage means and the raster storage means, for controlling the retrieval of characters from the font storage memory and the storage of retrieved characters in the page memory; and (b) means, coupled to the page memory, for generating addresses where words of a character are to be stored in the page memory, the address of a first word of a character to be stored in the page memory being specified by the processing unit but all addresses of any other words of a character being generated by the means for generating addresses independently of the operation of the processing unit. | 0.836845 |
8,074,176 | 1 | 10 | 1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal. | 1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal. 10. The method for an electronic communications dialog of claim 1 wherein the selected template comprises at least one of a sentence template, a social template, and a business template, the selected template configured to convey messages via pictures in lieu of words. | 0.74283 |
8,924,209 | 1 | 11 | 1. A method to identify a spoken command comprising voiced and unvoiced intervals in a particular order, and to responsively select an action from a set of predetermined actions, said method comprising the steps: 3.1 Converting sound of the spoken command into a digital signal comprising periodic digital measurements of the sound using a transducer and a converter; 3.2 Analyzing the digital signal to detect slow variations therein, by deriving an integrated signal by additively combining successive digital measurements, and comparing the integrated signal to a slow-variation threshold, a slow variation being detected when the integrated signal exceeds the slow-variation threshold; 3.3 Analyzing the digital signal to detect fast variations therein, by deriving a differentiated signal by subtractively combining successive digital measurements, and comparing the differentiated signal to a fast-variation threshold, a fast variation being detected when the differentiated signal exceeds the fast-variation threshold; 3.4 Analyzing the slow variations to detect voiced intervals having voiced sound, and analyzing the fast variations to detect unvoiced intervals having unvoiced sound; 3.5 Preparing a command sequence indicating the order of voiced and unvoiced intervals in the spoken command; 3.6 Comparing the command sequence to templates that indicate the order of voiced and unvoiced intervals in acceptable commands using a computer, each template being associated with one action in the set of predetermined actions; 3.7 And, when the command matches one of the templates, selecting the action associated with the matched template. | 1. A method to identify a spoken command comprising voiced and unvoiced intervals in a particular order, and to responsively select an action from a set of predetermined actions, said method comprising the steps: 3.1 Converting sound of the spoken command into a digital signal comprising periodic digital measurements of the sound using a transducer and a converter; 3.2 Analyzing the digital signal to detect slow variations therein, by deriving an integrated signal by additively combining successive digital measurements, and comparing the integrated signal to a slow-variation threshold, a slow variation being detected when the integrated signal exceeds the slow-variation threshold; 3.3 Analyzing the digital signal to detect fast variations therein, by deriving a differentiated signal by subtractively combining successive digital measurements, and comparing the differentiated signal to a fast-variation threshold, a fast variation being detected when the differentiated signal exceeds the fast-variation threshold; 3.4 Analyzing the slow variations to detect voiced intervals having voiced sound, and analyzing the fast variations to detect unvoiced intervals having unvoiced sound; 3.5 Preparing a command sequence indicating the order of voiced and unvoiced intervals in the spoken command; 3.6 Comparing the command sequence to templates that indicate the order of voiced and unvoiced intervals in acceptable commands using a computer, each template being associated with one action in the set of predetermined actions; 3.7 And, when the command matches one of the templates, selecting the action associated with the matched template. 11. The method of claim 1 wherein NSvar and NFvar are positive integers, and wherein Step 3.4 further includes the steps: 14.1 Determining that a voiced interval begins when NSvar slow variations are detected in succession; 14.2 And determining that an unvoiced interval begins when NFvar fast variations are detected in succession. | 0.836935 |
7,937,386 | 1 | 2 | 1. A method for extraction of text from a set of text documents, the method comprising the steps of: a) identifying a plurality of document segments within a given text document; b) for each given document segment identified in a), generating and storing at least one structured annotation embedded within the document and associated with the given segment, the at least one structured annotation specifying the start and end of the given document segment and a rhetorical relation associated with the given segment; c) processing the structured annotations generated and stored in b) to generate a plurality of variables that represent document segments and associated rhetorical relations as specified by the structured annotations; d) storing the variables generated in c) in a repository; e) receiving query input from a user that specifies at least one rhetorical relation of interest; and f) in response to receipt of said query input, querying the variables stored in the repository to identify zero or more document segments that are associated with a rhetorical relation that matches the at least one rhetorical relation of interest specified by said query input for output to the user. | 1. A method for extraction of text from a set of text documents, the method comprising the steps of: a) identifying a plurality of document segments within a given text document; b) for each given document segment identified in a), generating and storing at least one structured annotation embedded within the document and associated with the given segment, the at least one structured annotation specifying the start and end of the given document segment and a rhetorical relation associated with the given segment; c) processing the structured annotations generated and stored in b) to generate a plurality of variables that represent document segments and associated rhetorical relations as specified by the structured annotations; d) storing the variables generated in c) in a repository; e) receiving query input from a user that specifies at least one rhetorical relation of interest; and f) in response to receipt of said query input, querying the variables stored in the repository to identify zero or more document segments that are associated with a rhetorical relation that matches the at least one rhetorical relation of interest specified by said query input for output to the user. 2. A method according to claim 1 , wherein: the rhetorical relations include a set of RST relations whose meaning is dictated by nuclearity of the associated text. | 0.874034 |
9,262,135 | 9 | 15 | 9. A system comprising: one or more computer processors configured to: provide an input computer program expressed in an input computer language, wherein: the input computer language includes a first set of data types for elements or constructs to be evaluated at runtime, and a second set of data types for elements or constructs to be evaluated at translation time; and the input computer program includes at least one element or construct having a type in the first set of data types and includes at least one element or construct having a type in the second set of data types, the second set of data types being designated as embedded interpreter types (EITs) using type tags or type indicators; and automatically translate the input computer program to a computer executable output representation, including to: determine, at translation-time, whether a data type of a specific element or construct in the input computer program is among the first set of data types or the second set of data types, the determination includes to recognize whether the specific element or construct includes an EIT; in the event that the data type of the specific element or construct does not include an EIT, and the data type of the specific element or construct is among the first set of data types, at translation-time, perform translation without evaluating the specific element or construct; and in the event that the data type of the specific element or construct includes an EIT and the specific element or construct is among the second set of data types, at translation-time, execute code pertaining to the specific element or construct to evaluate the specific element or construct and perform translation; and provide the computer executable output representation as an output. | 9. A system comprising: one or more computer processors configured to: provide an input computer program expressed in an input computer language, wherein: the input computer language includes a first set of data types for elements or constructs to be evaluated at runtime, and a second set of data types for elements or constructs to be evaluated at translation time; and the input computer program includes at least one element or construct having a type in the first set of data types and includes at least one element or construct having a type in the second set of data types, the second set of data types being designated as embedded interpreter types (EITs) using type tags or type indicators; and automatically translate the input computer program to a computer executable output representation, including to: determine, at translation-time, whether a data type of a specific element or construct in the input computer program is among the first set of data types or the second set of data types, the determination includes to recognize whether the specific element or construct includes an EIT; in the event that the data type of the specific element or construct does not include an EIT, and the data type of the specific element or construct is among the first set of data types, at translation-time, perform translation without evaluating the specific element or construct; and in the event that the data type of the specific element or construct includes an EIT and the specific element or construct is among the second set of data types, at translation-time, execute code pertaining to the specific element or construct to evaluate the specific element or construct and perform translation; and provide the computer executable output representation as an output. 15. The system of claim 9 , wherein the input computer program includes one or more elements or constructs of the input computer language having data types in the second set of data types that provide for deferred instantiation of corresponding data elements or structures during translation. | 0.54232 |
9,239,660 | 1 | 7 | 1. A method for communicating over a network, the method comprising: transmitting, by an application server to a remote user computing device, a predefined interface in response to a contact request by the remote user, wherein the predefined interface is presented to the remote user, by displaying the predefined interface on the remote user computing device, the predefined interface being customized by the application server based on specified conditions including a location of the remote user computing device, a time of day, a day of a week, and a type of remote user language in which the contact request is received by the application server; analyzing, by an analysis server in communication with the application server by a communication link different from the network, a natural language inquiry from the remote user based on the type of remote user language of the contact request; transmitting, by the application server to the remote user computing device, a customized interface; wherein the customized interface is presented to the remote user, the customized interface including a customized plurality of communications options for the remote user to route subsequent communications, wherein the customized interface comprises customized content that is customized based on a context of the natural language inquiry, and wherein a customized plurality of predefined inquiries is changed based on the remote user selecting a customized communications option. | 1. A method for communicating over a network, the method comprising: transmitting, by an application server to a remote user computing device, a predefined interface in response to a contact request by the remote user, wherein the predefined interface is presented to the remote user, by displaying the predefined interface on the remote user computing device, the predefined interface being customized by the application server based on specified conditions including a location of the remote user computing device, a time of day, a day of a week, and a type of remote user language in which the contact request is received by the application server; analyzing, by an analysis server in communication with the application server by a communication link different from the network, a natural language inquiry from the remote user based on the type of remote user language of the contact request; transmitting, by the application server to the remote user computing device, a customized interface; wherein the customized interface is presented to the remote user, the customized interface including a customized plurality of communications options for the remote user to route subsequent communications, wherein the customized interface comprises customized content that is customized based on a context of the natural language inquiry, and wherein a customized plurality of predefined inquiries is changed based on the remote user selecting a customized communications option. 7. The method according to claim 1 , wherein the customized plurality of communications options includes a plurality of email addresses. | 0.908969 |
6,088,671 | 6 | 11 | 6. The method of claim 1 further including biasing, the designating in favor of the recognized speech element being a text element or a command element. | 6. The method of claim 1 further including biasing, the designating in favor of the recognized speech element being a text element or a command element. 11. The method of claim 6 in which the biasing includes determining whether actions of the user imply that the recognized speech element cannot be text. | 0.910377 |
9,342,794 | 15 | 16 | 15. A method, comprising: a computer system receiving an unknown text sample that includes user-generated content (UGC) submitted to a first website in connection with a user comment about a product or service, wherein the unknown text sample includes one or more words in one or more human languages; the computer system classifying the unknown text sample into one of a plurality of categories, wherein a first one of the plurality of categories corresponds to content prohibited from being published on a particular website, and wherein a second one of the plurality of categories corresponds to content allowed to be published on the particular website; wherein the classifying comprises: generating a set of features from the unknown text sample; performing one or more dimension reduction operations on the generated set of features; and using a first set of criteria and data generated from the performing the one or more dimension reduction operations to determine a classification for the unknown text sample, wherein the first set of criteria was established by a training procedure that includes: performing one or more dimension reduction operations on features within text samples in a training set that includes text samples for each of the plurality of categories; populating a data structure having entries corresponding to text samples in the training set, wherein the populating is based on the one or more dimension reduction operations; using a non-linear classifier on the data structure to establish the first set of criteria; wherein each text sample in the training set is made up of characters within a text character set having C characters, wherein features corresponding to text samples in the training set have N characters, and wherein populating an entry in the data structure for a given text sample includes a dimension reduction operation such that a corresponding feature value is reduced from C N possible values to not greater than C N-1 possible values, where N is an integer greater than or equal to 3 and C is an integer greater than or equal to 20. | 15. A method, comprising: a computer system receiving an unknown text sample that includes user-generated content (UGC) submitted to a first website in connection with a user comment about a product or service, wherein the unknown text sample includes one or more words in one or more human languages; the computer system classifying the unknown text sample into one of a plurality of categories, wherein a first one of the plurality of categories corresponds to content prohibited from being published on a particular website, and wherein a second one of the plurality of categories corresponds to content allowed to be published on the particular website; wherein the classifying comprises: generating a set of features from the unknown text sample; performing one or more dimension reduction operations on the generated set of features; and using a first set of criteria and data generated from the performing the one or more dimension reduction operations to determine a classification for the unknown text sample, wherein the first set of criteria was established by a training procedure that includes: performing one or more dimension reduction operations on features within text samples in a training set that includes text samples for each of the plurality of categories; populating a data structure having entries corresponding to text samples in the training set, wherein the populating is based on the one or more dimension reduction operations; using a non-linear classifier on the data structure to establish the first set of criteria; wherein each text sample in the training set is made up of characters within a text character set having C characters, wherein features corresponding to text samples in the training set have N characters, and wherein populating an entry in the data structure for a given text sample includes a dimension reduction operation such that a corresponding feature value is reduced from C N possible values to not greater than C N-1 possible values, where N is an integer greater than or equal to 3 and C is an integer greater than or equal to 20. 16. The method of claim 15 , wherein the classifying includes classifying the unknown text sample into the first category based on the unknown text sample including at least one word in a first human language and at least one word in a second human language. | 0.600619 |
7,797,261 | 1 | 8 | 1. A consultative system containing an advice and having a projection device, for helping a user to improve one's interactive ability by analyzing a particular person's behaviors in a simulation environment, said particular person being selected from a group including said user, a person different from said user, and a virtual person, said system comprising: building a plurality of virtual events for said advice, said plurality of virtual events involving interactions among two or more persons; projecting said plurality of virtual events by said projection device; capturing a response from said particular person; analyzing said response according to said advice to produce a report; and providing said report to said user, whereby said system guides said user to observe and examine said particular person's behaviors in a simulation scenario so that said user can learn effectively from both one's own behaviors and other person's behaviors and is able to apply said advice more naturally in a real life. | 1. A consultative system containing an advice and having a projection device, for helping a user to improve one's interactive ability by analyzing a particular person's behaviors in a simulation environment, said particular person being selected from a group including said user, a person different from said user, and a virtual person, said system comprising: building a plurality of virtual events for said advice, said plurality of virtual events involving interactions among two or more persons; projecting said plurality of virtual events by said projection device; capturing a response from said particular person; analyzing said response according to said advice to produce a report; and providing said report to said user, whereby said system guides said user to observe and examine said particular person's behaviors in a simulation scenario so that said user can learn effectively from both one's own behaviors and other person's behaviors and is able to apply said advice more naturally in a real life. 8. The system in claim 1 , said system having a recording device to record a plurality of real events, said system further comprising means for providing a plurality of variations on said plurality of real events to produce said plurality of virtual events, means for replaying said plurality of virtual events from a different direction, means for repeating a consulting session, means for tracking said plurality of virtual events, means for dispatching a corresponding advice in a plurality of formats, means for making comments, means for providing suggestions, means for providing an affirmation, wherein said report comprises items selected from a group including comments, suggestions, critical issues, responding modes, responding delays, if responding is proper, if facial expression is proper, if word used is proper, if speaking tune is proper, if gesture is proper, if said particular person focuses on a right thing, how emotion sensitive words is used, if there is any misused word, and if there is any misconduct, wherein means for providing a plurality of variations on said plurality of real events further comprise means selected from a group including means for building a different virtual environment, means for specifying a virtual person with different personality, means for changing a word by one of its synonyms, and means for changing a sentence pattern with a different one, whereby said system provides a simulation environment for said user to keep practicing so that said user can gradually enhance controllable ability on one's behavior, increase emotional sensibility, accelerate response speed, and increase observational sharpness. | 0.766274 |
8,208,765 | 1 | 2 | 1. A document image processing apparatus comprising: a character image feature dictionary for storing image features of character images in units of character; a character string clipping portion for clipping character images in units of character string composed of a plurality of characters from an inputted document image; an image feature extracting portion for extracting an image feature of each character image which is obtained by dividing character images of character string clipped by the character string clipping portion, for each of the characters; a feature similarity measurement portion for selecting N (N>1, integer) pieces of character images in descending order of degree of similarity of image feature as candidate characters, from the character image feature dictionary which stores image features of character image in units of character based on the image features of each of the character images extracted by the image feature extracting portion, preparing a first index matrix of M×N cells where M (M>1, integer) represents a number of characters in the clipped character string, and preparing a second index matrix of character strings including a meaningful character string which is formed by adjusting candidate character strings by application of a lexical analysis using a predetermined language model to the candidate character strings composed of a plurality of candidate characters constituting a first column of the first index matrix; an index information storing portion for storing the second index matrix prepared by the feature similarity measurement portion, so as to correspond to the inputted document image; and a searching section for searching, in a searching operation, the index information storing portion in units of search character constituting a search keyword of an inputted search formula, to take out the document image which includes the second index matrix containing the search character, wherein a position-based correlation value is set for each of the elements in the second index matrix, and the searching section comprises: an index matrix search processing portion for searching the index information storing portion for the second index matrix in units of search character constituting the search keyword to detect the second index matrix containing the search characters, and storing in a storing portion, information of matching position of search characters in the second index matrix together with information of the document images having the second index matrix; a degree-of-correlation calculating portion for calculating a degree of correlation between the search keyword and the second index matrix by accumulating correlation values of the respective search characters according to the information of matching position stored in the storing portion; and an order determining portion for determining a take-out order of document image based on the calculated result of the degree-of-correlation calculating portion. | 1. A document image processing apparatus comprising: a character image feature dictionary for storing image features of character images in units of character; a character string clipping portion for clipping character images in units of character string composed of a plurality of characters from an inputted document image; an image feature extracting portion for extracting an image feature of each character image which is obtained by dividing character images of character string clipped by the character string clipping portion, for each of the characters; a feature similarity measurement portion for selecting N (N>1, integer) pieces of character images in descending order of degree of similarity of image feature as candidate characters, from the character image feature dictionary which stores image features of character image in units of character based on the image features of each of the character images extracted by the image feature extracting portion, preparing a first index matrix of M×N cells where M (M>1, integer) represents a number of characters in the clipped character string, and preparing a second index matrix of character strings including a meaningful character string which is formed by adjusting candidate character strings by application of a lexical analysis using a predetermined language model to the candidate character strings composed of a plurality of candidate characters constituting a first column of the first index matrix; an index information storing portion for storing the second index matrix prepared by the feature similarity measurement portion, so as to correspond to the inputted document image; and a searching section for searching, in a searching operation, the index information storing portion in units of search character constituting a search keyword of an inputted search formula, to take out the document image which includes the second index matrix containing the search character, wherein a position-based correlation value is set for each of the elements in the second index matrix, and the searching section comprises: an index matrix search processing portion for searching the index information storing portion for the second index matrix in units of search character constituting the search keyword to detect the second index matrix containing the search characters, and storing in a storing portion, information of matching position of search characters in the second index matrix together with information of the document images having the second index matrix; a degree-of-correlation calculating portion for calculating a degree of correlation between the search keyword and the second index matrix by accumulating correlation values of the respective search characters according to the information of matching position stored in the storing portion; and an order determining portion for determining a take-out order of document image based on the calculated result of the degree-of-correlation calculating portion. 2. The document image processing apparatus of claim 1 , wherein the feature similarity measurement portion performs the lexical analysis on the candidate character strings by adopting a bi-gram or multi-gram model as a language model. | 0.703046 |
9,020,935 | 4 | 5 | 4. The system of claim 2 , wherein the instructions further cause the processor to perform the operations of: receiving an input indicating selection of one of the displayed variants; and adjusting a weighting assigned to the selected variant. | 4. The system of claim 2 , wherein the instructions further cause the processor to perform the operations of: receiving an input indicating selection of one of the displayed variants; and adjusting a weighting assigned to the selected variant. 5. The system of claim 4 , wherein the instructions further cause the processor to perform the operations of: determining that the input indicating selection comprises a keystroke on a spacebar key or a punctuation key, and selecting, as the selected variant, a first variant of the displayed variants. | 0.791436 |
8,364,755 | 12 | 14 | 12. The method for providing a customized digital yearbook of claim 11 further comprising integrating external data with the customized yearbook data at the device associated with the particular yearbook user. | 12. The method for providing a customized digital yearbook of claim 11 further comprising integrating external data with the customized yearbook data at the device associated with the particular yearbook user. 14. The method for providing a customized digital yearbook of claim 12 , wherein the external data comprises updates to the approved content. | 0.968736 |
8,249,869 | 4 | 5 | 4. A semantic, syntactic and/or lexical electronic correction apparatus for facilitating the semantic and/or syntactic and/or lexical correction of an erroneous expression in a digital text comprising eventual erroneous textual expressions, comprising: a module using a computer for transforming the entire digital text into a digital voice message, the transformation module being able to convert at least one grapheme of the digital text comprising eventual erroneous textual expressions into at least one phoneme comprising an intelligible vocal expression of the entire digital text, including any erroneous textual expression, and a module using the computer and a pre-established base of writing rules for processing the digital voice message provided by the transformation module, the processing module being able to convert the at least one phoneme comprising the intelligible vocal expression and provided by the transformation module, into at least one grapheme comprising a new digital text in which any erroneous textual expression is corrected, wherein the transformation module uses the computer to provide the at least one phoneme according to a predetermined voice model, with the aid of a voice model base, and wherein the processing module is able to identify the at least one phoneme to be converted, with the aid of a base of recognition rules for the predetermined voice model. | 4. A semantic, syntactic and/or lexical electronic correction apparatus for facilitating the semantic and/or syntactic and/or lexical correction of an erroneous expression in a digital text comprising eventual erroneous textual expressions, comprising: a module using a computer for transforming the entire digital text into a digital voice message, the transformation module being able to convert at least one grapheme of the digital text comprising eventual erroneous textual expressions into at least one phoneme comprising an intelligible vocal expression of the entire digital text, including any erroneous textual expression, and a module using the computer and a pre-established base of writing rules for processing the digital voice message provided by the transformation module, the processing module being able to convert the at least one phoneme comprising the intelligible vocal expression and provided by the transformation module, into at least one grapheme comprising a new digital text in which any erroneous textual expression is corrected, wherein the transformation module uses the computer to provide the at least one phoneme according to a predetermined voice model, with the aid of a voice model base, and wherein the processing module is able to identify the at least one phoneme to be converted, with the aid of a base of recognition rules for the predetermined voice model. 5. The electronic correction apparatus of claim 4 , further comprising: at least one loudspeaker able to synthesize as audible sounds the digital voice message provided by the transformation module, and an activation device for activating the processing module so as to apply the processing module to the digital voice message synthesized by the loudspeaker. | 0.690846 |
7,712,073 | 7 | 10 | 7. A method for creating and loading an interface control document, comprising: selecting features of a destination interface control document to generate, wherein the destination interface control document defines one or more of a communication technology employed, a structure of information communicated, or a mandatory message sequence; providing a template document having a list of standard interface control document components; providing a computer aided software engineering tool for maintaining interface control documents; generating the destination interface control document defining a structure using one of the standard interface control document components from the template document that correspond with the selected features, wherein the structure of the destination interface control document is empty and the structure is compatible with the computer aided software engineering tool; storing the destination interface control document as an mdl file type in the computer aided software engineering tool, wherein the mdl file type is a modeling file in a proprietary format compatible with the computer aided software engineering tool; designating a source document having source data elements for the destination interface control document, wherein each of the source data elements include a structure name portion, an attribute name portion, a documentation portion maintaining a description of the data element, and a data type portion, and where the source document is an artifact of a software development tool that is incompatible with the computer aided software engineering tool; reading at least some of the data elements from the source document; transforming the read data elements from a format compatible with the software development tool to a format compatible with the computer aided software engineering tool; loading the transformed data elements into the structure of the destination interface control document; and storing the destination interface control document having at least some of the data elements in the computer aided software engineering tool. | 7. A method for creating and loading an interface control document, comprising: selecting features of a destination interface control document to generate, wherein the destination interface control document defines one or more of a communication technology employed, a structure of information communicated, or a mandatory message sequence; providing a template document having a list of standard interface control document components; providing a computer aided software engineering tool for maintaining interface control documents; generating the destination interface control document defining a structure using one of the standard interface control document components from the template document that correspond with the selected features, wherein the structure of the destination interface control document is empty and the structure is compatible with the computer aided software engineering tool; storing the destination interface control document as an mdl file type in the computer aided software engineering tool, wherein the mdl file type is a modeling file in a proprietary format compatible with the computer aided software engineering tool; designating a source document having source data elements for the destination interface control document, wherein each of the source data elements include a structure name portion, an attribute name portion, a documentation portion maintaining a description of the data element, and a data type portion, and where the source document is an artifact of a software development tool that is incompatible with the computer aided software engineering tool; reading at least some of the data elements from the source document; transforming the read data elements from a format compatible with the software development tool to a format compatible with the computer aided software engineering tool; loading the transformed data elements into the structure of the destination interface control document; and storing the destination interface control document having at least some of the data elements in the computer aided software engineering tool. 10. The method of claim 7 , wherein the transforming and the loading of the data elements includes writing object attributes into the destination interface control document by importing structure names, attribute names, descriptions, and data types based on the data elements read from the source document. | 0.858595 |
7,882,116 | 8 | 9 | 8. Computer apparatus as claimed in claim 7 wherein the storage device includes property files for storing element name-string value pairs. | 8. Computer apparatus as claimed in claim 7 wherein the storage device includes property files for storing element name-string value pairs. 9. Computer apparatus as claimed in claim 8 wherein the element name is in a qualified manner in the element name-string value pairs. | 0.966899 |
7,512,620 | 1 | 7 | 1. A computer program product for indexing an object on a computer desktop, the object having an assigned score and an associated name, the computer program product comprising a computer-readable storage medium containing computer program code for performing a method comprising: indexing the object into an index, the indexing being responsive to a plurality of prefixes of the name associated with the object and the score assigned to the objects, wherein the index comprises a plurality of fixed-sized arrays and the indexing is performed responsive to a variable B representing an integer between 1 and the fixed-size of the arrays in the index, and wherein the indexing comprises: storing a reference to the object as an entry in the fixed-sized array associated with the shortest prefix of the name if the array after the storing contains B array entries and if the score of the object is within the top B scores of objects in the array. | 1. A computer program product for indexing an object on a computer desktop, the object having an assigned score and an associated name, the computer program product comprising a computer-readable storage medium containing computer program code for performing a method comprising: indexing the object into an index, the indexing being responsive to a plurality of prefixes of the name associated with the object and the score assigned to the objects, wherein the index comprises a plurality of fixed-sized arrays and the indexing is performed responsive to a variable B representing an integer between 1 and the fixed-size of the arrays in the index, and wherein the indexing comprises: storing a reference to the object as an entry in the fixed-sized array associated with the shortest prefix of the name if the array after the storing contains B array entries and if the score of the object is within the top B scores of objects in the array. 7. The computer program product of claim 1 , wherein indexing comprises: storing the score assigned to the object in the index. | 0.928167 |
9,002,834 | 1 | 5 | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages, wherein the list of inquiries includes search terms used in a search that identified the first file and the plurality of web pages, wherein the search terms are included within text of citations of the first file; providing, by the system server, the list of inquiries to at least one author of the first file; receiving from the at least one author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; and storing information related to the selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one author to the user. | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages, wherein the list of inquiries includes search terms used in a search that identified the first file and the plurality of web pages, wherein the search terms are included within text of citations of the first file; providing, by the system server, the list of inquiries to at least one author of the first file; receiving from the at least one author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; and storing information related to the selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one author to the user. 5. The method of claim 1 , further comprising: providing, by the system server, the selected subset of the plurality of web pages to a user that selects the first file and identifying the at least one author of the first file, and the at least one author of the plurality of web pages to the user, wherein identifying the at least one author comprises providing the user with a name, qualifications or institution of the at least one author. | 0.667421 |
7,475,005 | 1 | 2 | 1. A translation system for translating a document, comprising: a dictionary management unit for managing a plurality of categorized dictionaries classified according to predetermined categories; a phrase extraction unit for extracting a noun phrase from said document; a registration category selection unit for selecting a category into which said extracted noun phrase is registered among a plurality of categories corresponding to said plurality of categorized dictionaries, respectively; a translation unit for translating said noun phrase to generate a noun phrase translation which is a translation of said noun phrase; a dictionary registration unit for registering a pair of said noun phrase and said noun phrase translation on said categorized dictionary corresponding to the category selected by said registration category selection unit; a document category selection unit for selecting the category of said document on the basis of the frequencies of use of said plurality of categorized dictionaries in translation of said document; and a registration destination selection unit selects a category into which said extracted noun phrase is registered on the basis of the category selected by said document category selection unit. | 1. A translation system for translating a document, comprising: a dictionary management unit for managing a plurality of categorized dictionaries classified according to predetermined categories; a phrase extraction unit for extracting a noun phrase from said document; a registration category selection unit for selecting a category into which said extracted noun phrase is registered among a plurality of categories corresponding to said plurality of categorized dictionaries, respectively; a translation unit for translating said noun phrase to generate a noun phrase translation which is a translation of said noun phrase; a dictionary registration unit for registering a pair of said noun phrase and said noun phrase translation on said categorized dictionary corresponding to the category selected by said registration category selection unit; a document category selection unit for selecting the category of said document on the basis of the frequencies of use of said plurality of categorized dictionaries in translation of said document; and a registration destination selection unit selects a category into which said extracted noun phrase is registered on the basis of the category selected by said document category selection unit. 2. The translation system according to claim 1 , wherein said document category selection unit selects the category of each of said plurality of documents on the basis of the frequencies of use of said plurality of categorized dictionaries in translation of said plurality of documents, and wherein said phrase extraction unit extracts said noun phrase from said plurality of documents, and said registration destination selection unit selects a category into which said extracted noun phrase is registered, on the basis of the frequencies of appearance of said noun phrase in said plurality of documents and the categories of the documents. | 0.745231 |
8,892,420 | 8 | 12 | 8. A system for text processing, comprising: one or more processors configured to: train a classifier for classifying text, wherein: the training is based on a plurality of training sample entries; a training sample entry in the plurality of training sample entries includes: a character count; an independent use rate; a phrase structure rule value indicating whether the training sample entry complies with phrase structure rules; a semantic attribute value indicating an inclusion state of the training sample entry in a predetermined set of enumerated entries; an overlap attribute value indicating overlap of the training sample entry with another entry in the predetermined set of enumerated entries; and a classification result indicating whether the training sample entry is a compound semantic unit or a smallest semantic unit; and build a lexicon of smallest semantic units, comprising: receiving an entry to be classified; using the trained classifier to determine whether the entry to be classified is a smallest semantic unit or a compound semantic unit; and in the event that the entry is determined to be a smallest semantic unit, adding the entry to the lexicon of smallest semantic units; segment received text based on the lexicon of smallest semantic units to obtain medium-grained segmentation results; merge the medium-grained segmentation results to obtain coarse-grained segmentation results, the coarse-grained segmentation results having coarser granularity than the medium-grained segmentation results; look up in the lexicon of smallest semantic units respective search elements that correspond to segments in the medium-grained segmentation results; and form fine-grained segmentation results based on the respective search elements, the fine-grained segmentation results having finer granularity than the medium-grained segmentation results; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. | 8. A system for text processing, comprising: one or more processors configured to: train a classifier for classifying text, wherein: the training is based on a plurality of training sample entries; a training sample entry in the plurality of training sample entries includes: a character count; an independent use rate; a phrase structure rule value indicating whether the training sample entry complies with phrase structure rules; a semantic attribute value indicating an inclusion state of the training sample entry in a predetermined set of enumerated entries; an overlap attribute value indicating overlap of the training sample entry with another entry in the predetermined set of enumerated entries; and a classification result indicating whether the training sample entry is a compound semantic unit or a smallest semantic unit; and build a lexicon of smallest semantic units, comprising: receiving an entry to be classified; using the trained classifier to determine whether the entry to be classified is a smallest semantic unit or a compound semantic unit; and in the event that the entry is determined to be a smallest semantic unit, adding the entry to the lexicon of smallest semantic units; segment received text based on the lexicon of smallest semantic units to obtain medium-grained segmentation results; merge the medium-grained segmentation results to obtain coarse-grained segmentation results, the coarse-grained segmentation results having coarser granularity than the medium-grained segmentation results; look up in the lexicon of smallest semantic units respective search elements that correspond to segments in the medium-grained segmentation results; and form fine-grained segmentation results based on the respective search elements, the fine-grained segmentation results having finer granularity than the medium-grained segmentation results; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. 12. The system of claim 8 , wherein the one or more processors are further configured to: determine a search element that corresponds to the entry; and save the search element in the lexicon of smallest semantic units. | 0.791188 |
9,946,790 | 7 | 8 | 7. A system, comprising: at least one computing device; and an item categorizing service executable in the at least one computing device, wherein, when executed, the item categorizing service causes the at least one computing device to at least: generate a user interface to facilitate creation of a plurality of user-created item lists via a plurality of client devices; receive the plurality of user-created item lists from the plurality of client devices via the user interface rendered on the plurality of client devices; maintain the plurality of user-created item lists in an item list registry, individual user-created item lists of the plurality of user-created item lists including a plurality of items available for purchase, lease, or download via an electronic commerce system, and the individual user-created item lists being identified by a respective item list title that includes a title term; obtain a particular item list of the plurality of user-created item lists from the item list registry; compare the title term of the particular item list with a plurality of predefined keywords; assign a keyword tag associated with a particular predefined keyword of the plurality of predefined keywords to individual items of the plurality of items included in the particular item list in response to the title term matching the particular predefined keyword; create an item category associated with the particular predefined keyword; and populate the item category associated with the particular predefined keyword with a particular item of the plurality of items based at least in part upon a number of keyword tags assigned to the particular item reaching a predefined threshold. | 7. A system, comprising: at least one computing device; and an item categorizing service executable in the at least one computing device, wherein, when executed, the item categorizing service causes the at least one computing device to at least: generate a user interface to facilitate creation of a plurality of user-created item lists via a plurality of client devices; receive the plurality of user-created item lists from the plurality of client devices via the user interface rendered on the plurality of client devices; maintain the plurality of user-created item lists in an item list registry, individual user-created item lists of the plurality of user-created item lists including a plurality of items available for purchase, lease, or download via an electronic commerce system, and the individual user-created item lists being identified by a respective item list title that includes a title term; obtain a particular item list of the plurality of user-created item lists from the item list registry; compare the title term of the particular item list with a plurality of predefined keywords; assign a keyword tag associated with a particular predefined keyword of the plurality of predefined keywords to individual items of the plurality of items included in the particular item list in response to the title term matching the particular predefined keyword; create an item category associated with the particular predefined keyword; and populate the item category associated with the particular predefined keyword with a particular item of the plurality of items based at least in part upon a number of keyword tags assigned to the particular item reaching a predefined threshold. 8. The system of claim 7 , wherein the individual user-created item lists of the plurality of user-created item lists are created by a respective user of a plurality of users, and the respective user-created item list title for the individual item lists is defined by the respective user. | 0.731844 |
8,387,029 | 27 | 35 | 27. A system for parsing and executing an input software program written in an original linguistic form in a high level language, the system comprising: at least one processor-readable medium storing executable instructions to implement: a tokenizer operable to tokenize the software program to generate an input stream of tokens representing the software program; a parser operable to use one or more production rules to directly execute a nonlinear program element in the software program, by manipulating a parse state and the input stream of tokens representing the body of the nonlinear program element, while preserving the original linguistic form of the software program, wherein the one or more production rules include a type conversion production rule useable by the parser to perform type conversion and production rules useable by the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein manipulating the input stream of tokens comprises using the type conversion production rule to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions to skip tokens during execution of the nonlinear program element; and at least one processor operable to execute the executable instructions. | 27. A system for parsing and executing an input software program written in an original linguistic form in a high level language, the system comprising: at least one processor-readable medium storing executable instructions to implement: a tokenizer operable to tokenize the software program to generate an input stream of tokens representing the software program; a parser operable to use one or more production rules to directly execute a nonlinear program element in the software program, by manipulating a parse state and the input stream of tokens representing the body of the nonlinear program element, while preserving the original linguistic form of the software program, wherein the one or more production rules include a type conversion production rule useable by the parser to perform type conversion and production rules useable by the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein manipulating the input stream of tokens comprises using the type conversion production rule to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions to skip tokens during execution of the nonlinear program element; and at least one processor operable to execute the executable instructions. 35. The system as recited in claim 27 , wherein the parser is table-driven. | 0.941223 |
9,134,999 | 1 | 2 | 1. A system for monitoring software development and project flow in the insurance industry using user stories, the system comprising: a communication interface that receives, via one or more networks, information included in communications among distributed experts following a centralized process; a processor and memory that are integrated to: identify from a monitored communication a plurality of user stories for completion during software development; estimate a priority of each of the plurality of user stories; assign a value to each of the plurality of user stories, the assigned value represents an amount of effort needed to complete a user story; store each of the plurality of user stories and associated priority and value in the memory as a product backlog; calibrate a difference in the assigned value of each of the plurality of user stories by comparing a centralized position of each of the plurality of user stories and an associated Fibonacci position, and iteratively adjusting the Fibonacci position of each of the plurality of user stories based on the difference between the centralized position and the assigned value as compared to a median value until the difference is below a threshold; and update a product backlog of user stories with the user story's associated calibrated assigned value; and a display device for displaying the status of the software development and project flow based on a plurality of user stories remaining in the product backlog as compared to a plurality of user completed stories. | 1. A system for monitoring software development and project flow in the insurance industry using user stories, the system comprising: a communication interface that receives, via one or more networks, information included in communications among distributed experts following a centralized process; a processor and memory that are integrated to: identify from a monitored communication a plurality of user stories for completion during software development; estimate a priority of each of the plurality of user stories; assign a value to each of the plurality of user stories, the assigned value represents an amount of effort needed to complete a user story; store each of the plurality of user stories and associated priority and value in the memory as a product backlog; calibrate a difference in the assigned value of each of the plurality of user stories by comparing a centralized position of each of the plurality of user stories and an associated Fibonacci position, and iteratively adjusting the Fibonacci position of each of the plurality of user stories based on the difference between the centralized position and the assigned value as compared to a median value until the difference is below a threshold; and update a product backlog of user stories with the user story's associated calibrated assigned value; and a display device for displaying the status of the software development and project flow based on a plurality of user stories remaining in the product backlog as compared to a plurality of user completed stories. 2. The system of claim 1 wherein the associated priority of each of the plurality of user stories is updated based on feedback from the completed story points in the product backlog. | 0.899225 |
8,725,492 | 9 | 13 | 9. A computing device for recognizing multiple semantic items from a single utterance, the computing device comprising: a memory; a processor coupled to the memory, the processor capable of executing a first application for speech recognition and a second application for consuming results of the speech recognition, wherein the first application is configured to: receive a single utterance including at least two semantically distinct items from a user, the semantically distinct items comprising at least one from a set of: words, phrases, and fragments; process the single utterance to recognize a first item of the at least two semantically distinct items; provide the recognized first item to the user for one of confirmation and correction; receive one of the user correction and confirmation for the first item; determine a specific language model based on the first item; process the single utterance again to recognize a second item of the at least two semantically distinct items applying the specific language model; determine alternative values for the first item based on recognizing the first item; provide the alternative values to the user and the second application; receive input from the second application for specific language models associated with each of the alternative values; receive a user selection for one of the alternative values; and recognize the second item based on one of the specific language models associated with the selected alternative value for the first item; and wherein the second application is configured to: in response to consuming the first item, provide input to the first application for the specific language model; and in response to consuming the second item, provide feedback to the user based on a combination of the first and second items. | 9. A computing device for recognizing multiple semantic items from a single utterance, the computing device comprising: a memory; a processor coupled to the memory, the processor capable of executing a first application for speech recognition and a second application for consuming results of the speech recognition, wherein the first application is configured to: receive a single utterance including at least two semantically distinct items from a user, the semantically distinct items comprising at least one from a set of: words, phrases, and fragments; process the single utterance to recognize a first item of the at least two semantically distinct items; provide the recognized first item to the user for one of confirmation and correction; receive one of the user correction and confirmation for the first item; determine a specific language model based on the first item; process the single utterance again to recognize a second item of the at least two semantically distinct items applying the specific language model; determine alternative values for the first item based on recognizing the first item; provide the alternative values to the user and the second application; receive input from the second application for specific language models associated with each of the alternative values; receive a user selection for one of the alternative values; and recognize the second item based on one of the specific language models associated with the selected alternative value for the first item; and wherein the second application is configured to: in response to consuming the first item, provide input to the first application for the specific language model; and in response to consuming the second item, provide feedback to the user based on a combination of the first and second items. 13. The computing device of claim 9 , wherein the second application is a web-based search application, the first item is a geographical location, and the second item is a business name. | 0.889417 |
8,976,373 | 14 | 15 | 14. The image processing method of claim 6 , wherein after the first processor core completes the rendering processing of the intermediate language data stored in the memory by the second processor core performing the analysis processing of the first page, the first processor core resumes the analysis processing of a second page that was being performed at the time the analysis processing was discontinued, the second page corresponding to a page other than the forefront page number, and the first processor core performs the analysis processing of the second page in parallel with the second processor core performing the analysis processing of the first page. | 14. The image processing method of claim 6 , wherein after the first processor core completes the rendering processing of the intermediate language data stored in the memory by the second processor core performing the analysis processing of the first page, the first processor core resumes the analysis processing of a second page that was being performed at the time the analysis processing was discontinued, the second page corresponding to a page other than the forefront page number, and the first processor core performs the analysis processing of the second page in parallel with the second processor core performing the analysis processing of the first page. 15. The image processing method of claim 14 , wherein after the second processor core completes the analysis processing of the first page, the second processor core performs the rendering processing of the first page, and the first processor core discontinues the analysis processing of the second page and performs the rendering processing of the first page in parallel with the second processor performing the rendering processing of the first page. | 0.917217 |
10,032,081 | 1 | 8 | 1. A method, comprising: receiving a video file for classification; analyzing images captured in frames of the video file to identify one or more elements; matching each element of the one or more elements identified in the images of frames to a corresponding term defined in a vocabulary list; determining a number of frames within the video file in which each element appears, which corresponds to the term in the vocabulary list; and generating a vector for the video file, the vector identifying each term in the vocabulary list, the vector represented in textual format as a name-value pair, wherein name in the name-value pair corresponds to the name of the term in the vocabulary list, and value in the name-value pair corresponds to the number of frames within the video file in which each element appears, which corresponds to the term in the vocabulary list, information provided in the vector used to identify one or more frames where the respective element is detected in the video file. | 1. A method, comprising: receiving a video file for classification; analyzing images captured in frames of the video file to identify one or more elements; matching each element of the one or more elements identified in the images of frames to a corresponding term defined in a vocabulary list; determining a number of frames within the video file in which each element appears, which corresponds to the term in the vocabulary list; and generating a vector for the video file, the vector identifying each term in the vocabulary list, the vector represented in textual format as a name-value pair, wherein name in the name-value pair corresponds to the name of the term in the vocabulary list, and value in the name-value pair corresponds to the number of frames within the video file in which each element appears, which corresponds to the term in the vocabulary list, information provided in the vector used to identify one or more frames where the respective element is detected in the video file. 8. The method of claim 1 , wherein the vector is a one-dimensional vector. | 0.949454 |
4,037,208 | 1 | 3 | 1. In a serial printer comprising a carriage, a print member rotatably mounted to said carriage and including a plurality of character elements of a predetermined font style, drive means coupled to said print member for rotating said print member to a desired rotational position order to place a selected character element at a printing position adjacent a record medium to be printed upon, print hammer means mounted to said carriage and capable when enabled of impacting the character element located at said printing position with a desired level of force, and hammer control apparatus coupled to said print hammer means for enabling said print hammer means when said selected character element has been rotated to said desired rotational position, said hammer control apparatus comprising: means responsive to a first signal representative of said selected character element to be impacted for generating a second signal proportional to a desired level of force with which said selected character element is to be impacted by said print hammer means when said plurality of character elements are defined in any one of at least two different font styles, one of which being said predetermined font style; means coupled to said means for generating a second signal for multiplying said second signal by a constant identifying said predetermined font style to form a third signal representative of the desired level of force with which said selected character element is to be impacted; said means for multiplying including switch means capable of selectively attenuating said second signal by a predetermined amount for each of said at least two different font styles; said switch means including, a manually operable switch having a common contact and at least two selectable contacts, an amplifier having first and second inputs and an output, first impedance means for coupling the first input of said amplifier to said means for generating said second signal and to said common contact, second impedance means for coupling the second input of said amplifier to one of said selectable contacts, and means coupled to the output of said amplifier for generating said third signal; means coupled to said print member for detecting when said selected character element has been rotated to said desired rotational position; and means responsive to such detection for coupling said third signal to said print hammer means thereby enabling said print hammer means to impact said selected character element with said desired level of force. | 1. In a serial printer comprising a carriage, a print member rotatably mounted to said carriage and including a plurality of character elements of a predetermined font style, drive means coupled to said print member for rotating said print member to a desired rotational position order to place a selected character element at a printing position adjacent a record medium to be printed upon, print hammer means mounted to said carriage and capable when enabled of impacting the character element located at said printing position with a desired level of force, and hammer control apparatus coupled to said print hammer means for enabling said print hammer means when said selected character element has been rotated to said desired rotational position, said hammer control apparatus comprising: means responsive to a first signal representative of said selected character element to be impacted for generating a second signal proportional to a desired level of force with which said selected character element is to be impacted by said print hammer means when said plurality of character elements are defined in any one of at least two different font styles, one of which being said predetermined font style; means coupled to said means for generating a second signal for multiplying said second signal by a constant identifying said predetermined font style to form a third signal representative of the desired level of force with which said selected character element is to be impacted; said means for multiplying including switch means capable of selectively attenuating said second signal by a predetermined amount for each of said at least two different font styles; said switch means including, a manually operable switch having a common contact and at least two selectable contacts, an amplifier having first and second inputs and an output, first impedance means for coupling the first input of said amplifier to said means for generating said second signal and to said common contact, second impedance means for coupling the second input of said amplifier to one of said selectable contacts, and means coupled to the output of said amplifier for generating said third signal; means coupled to said print member for detecting when said selected character element has been rotated to said desired rotational position; and means responsive to such detection for coupling said third signal to said print hammer means thereby enabling said print hammer means to impact said selected character element with said desired level of force. 3. The serial printer of claim 1, wherein said means for generating, said means for detecting and said means for coupling are all included in a data processing means. | 0.75942 |
8,055,672 | 13 | 16 | 13. A method for a user to build a query to a database, the method comprising the steps of: displaying in a first window a graphical representation of at least one relationship in the database specified in a database relationship document when building a query in a series of steps, the graphical representation comprising at least one item in the database that the user may select; and displaying in a second window information that is filtered at each step in building the query according to all user selections on the graphical representation in all previous steps. | 13. A method for a user to build a query to a database, the method comprising the steps of: displaying in a first window a graphical representation of at least one relationship in the database specified in a database relationship document when building a query in a series of steps, the graphical representation comprising at least one item in the database that the user may select; and displaying in a second window information that is filtered at each step in building the query according to all user selections on the graphical representation in all previous steps. 16. The method of claim 13 wherein the database relationship document comprises an XML document. | 0.909263 |
8,176,412 | 5 | 6 | 5. The method of claim 1 , wherein enabling specification of a structure to be used in the one or more generated formatted documents comprises using a graphical user interface (GUI) to determine where a data model element will appear within a document and how the document will be formatted. | 5. The method of claim 1 , wherein enabling specification of a structure to be used in the one or more generated formatted documents comprises using a graphical user interface (GUI) to determine where a data model element will appear within a document and how the document will be formatted. 6. The method of claim 5 , wherein enabling specification of a structure to be used in the one or more generated formatted documents comprises determining the formatting element used to render a document. | 0.92025 |
9,288,039 | 5 | 9 | 5. The method of claim 2 , wherein the server receives doubly-encrypted resources from the client generated from the encrypted resources provided to the client, the doubly-encrypted resources including doubly-encrypted frequencies generated by further encrypting the encrypted frequencies of n-grams in the encrypted resources with a key for homomorphic multiplication. | 5. The method of claim 2 , wherein the server receives doubly-encrypted resources from the client generated from the encrypted resources provided to the client, the doubly-encrypted resources including doubly-encrypted frequencies generated by further encrypting the encrypted frequencies of n-grams in the encrypted resources with a key for homomorphic multiplication. 9. The method of claim 5 , wherein the doubly-encrypted frequency for each of the n-grams in each set of n-grams is generated with a key for homomorphic multiplication which is not provided to the server. | 0.920125 |
7,761,436 | 1 | 9 | 1. A computer-implemented method for sharing annotated content with an annotating user, comprising: receiving from a user a first set of keywords for annotating content from the annotating user; receiving from a user a second set of keywords that designate whether the annotated content annotated by at least one keyword included in the second set of keywords is shared with the annotating user; storing in a data store a first association of the first set of keywords with the annotating user, and a second association of to second set of keywords with the annotating user; receiving via a client system, which is associated with the annotating user, a keyword selection for a select keyword and an identifier for the annotating user; retrieving the first and second associations from the data store; determining from the first association and the identifier whether the annotated content from the annotating user is annotated by at least one keyword in the first set of keywords; determining from the second association whether the select keyword is included in the second set of keywords; and displaying on the client system content annotated by the select keyword if the annotated content from the annotating user is annotated by at least one keyword in the first set of keywords, and if the select keyword is included in the second set of keywords. | 1. A computer-implemented method for sharing annotated content with an annotating user, comprising: receiving from a user a first set of keywords for annotating content from the annotating user; receiving from a user a second set of keywords that designate whether the annotated content annotated by at least one keyword included in the second set of keywords is shared with the annotating user; storing in a data store a first association of the first set of keywords with the annotating user, and a second association of to second set of keywords with the annotating user; receiving via a client system, which is associated with the annotating user, a keyword selection for a select keyword and an identifier for the annotating user; retrieving the first and second associations from the data store; determining from the first association and the identifier whether the annotated content from the annotating user is annotated by at least one keyword in the first set of keywords; determining from the second association whether the select keyword is included in the second set of keywords; and displaying on the client system content annotated by the select keyword if the annotated content from the annotating user is annotated by at least one keyword in the first set of keywords, and if the select keyword is included in the second set of keywords. 9. The method according to claim 1 . wherein the user is a computer. | 0.928118 |
7,610,227 | 1 | 3 | 1. A processor-based method for creating a set of work papers with cross-reference links to tax documents comprising: receiving, at a computer, a tax document; displaying, on a display screen, a page of the tax document; receiving, at the computer, a form type corresponding to the page of the tax document; receiving, at the computer, a form name corresponding to the page of the tax document; displaying, on the display screen, a plurality of categories related to the form type; providing, at the computer, a category selection from the plurality of categories; providing, at the computer, a link corresponding to the selected category; receiving, at the computer, a number or a description corresponding to the link; providing, at the computer, a tax return reconciliation template that includes a tax item description field and a tax page identifier field; providing, at the computer, a tax return reconciliation page by populating the tax item description field and the tax page identifier field with information from the tax document; and displaying, on the display screen, the tax return reconciliation page, wherein the tax page identifier field includes a clickable link to the page of the tax document containing a value corresponding to the tax item description field. | 1. A processor-based method for creating a set of work papers with cross-reference links to tax documents comprising: receiving, at a computer, a tax document; displaying, on a display screen, a page of the tax document; receiving, at the computer, a form type corresponding to the page of the tax document; receiving, at the computer, a form name corresponding to the page of the tax document; displaying, on the display screen, a plurality of categories related to the form type; providing, at the computer, a category selection from the plurality of categories; providing, at the computer, a link corresponding to the selected category; receiving, at the computer, a number or a description corresponding to the link; providing, at the computer, a tax return reconciliation template that includes a tax item description field and a tax page identifier field; providing, at the computer, a tax return reconciliation page by populating the tax item description field and the tax page identifier field with information from the tax document; and displaying, on the display screen, the tax return reconciliation page, wherein the tax page identifier field includes a clickable link to the page of the tax document containing a value corresponding to the tax item description field. 3. The method of claim 1 wherein the receiving the form name includes providing a form name selection from a plurality of preexisting form names or inputting a form name. | 0.502924 |
8,392,443 | 1 | 4 | 1. A computer-implemented method comprising: obtaining a submitted search query, and in response to obtaining the search query: obtaining search results responsive to the search query; selecting a document from a group of documents identified by the search results; generating, from each entity text string in a subset of one or more entity text strings associated with the document, one or more candidates for refined search queries, including: identifying three or more terms in the search query that each have a respective term score satisfying a term threshold, where the three or more terms occur in the search query in a particular order relative to each other, and combining the three or more terms with the entity text string to generate a respective candidate, where the three or more terms occur in the candidate in the particular order relative to each other; and identifying one or more of the candidates as being refined search queries to be provided with the search results in response to the search query. | 1. A computer-implemented method comprising: obtaining a submitted search query, and in response to obtaining the search query: obtaining search results responsive to the search query; selecting a document from a group of documents identified by the search results; generating, from each entity text string in a subset of one or more entity text strings associated with the document, one or more candidates for refined search queries, including: identifying three or more terms in the search query that each have a respective term score satisfying a term threshold, where the three or more terms occur in the search query in a particular order relative to each other, and combining the three or more terms with the entity text string to generate a respective candidate, where the three or more terms occur in the candidate in the particular order relative to each other; and identifying one or more of the candidates as being refined search queries to be provided with the search results in response to the search query. 4. The method of claim 1 , further comprising: ranking each of the one or more entity text strings according to a respective frequency of occurrence of the entity text strings as previously-submitted search queries; and determining that the subset of the identified entity text strings includes only entity text strings with a ranking beyond a threshold rank. | 0.673042 |
7,783,658 | 7 | 11 | 7. The method of claim 1 , further comprising: determining one or more related candidate entities that are related to each of the candidate entities. | 7. The method of claim 1 , further comprising: determining one or more related candidate entities that are related to each of the candidate entities. 11. The method of claim 7 , wherein for ones of the candidate entities that are vehicles, the method further comprises: searching for owners or registered addresses correspond to the vehicles. | 0.922267 |
9,715,877 | 15 | 16 | 15. Non-transitory computer-readable media bearing software instructions configured to instruct a processor to search navigation system data including phonetic data and text data stored in a storage device accessible from within a mobile platform, wherein the phonetic data includes a set of point-of-interest names in phonetic form, and the text data includes at least a portion of the same set of point-of-interest names in text form, by performing the steps of: receiving a representation of spoken utterance from a user; querying the phonetic data of the navigation system data with the spoken utterance to find a corresponding match; if a corresponding match is not found via the querying of the phonetic data, processing the representation of the spoken utterance to produce a dictation text substantially corresponding to the spoken utterance, wherein the dictation text is tuned for speech that is typical of navigation destination entry types; and querying the text data of the navigation system data with the dictation text using an approximate string matching criteria and producing a results list associated therewith. | 15. Non-transitory computer-readable media bearing software instructions configured to instruct a processor to search navigation system data including phonetic data and text data stored in a storage device accessible from within a mobile platform, wherein the phonetic data includes a set of point-of-interest names in phonetic form, and the text data includes at least a portion of the same set of point-of-interest names in text form, by performing the steps of: receiving a representation of spoken utterance from a user; querying the phonetic data of the navigation system data with the spoken utterance to find a corresponding match; if a corresponding match is not found via the querying of the phonetic data, processing the representation of the spoken utterance to produce a dictation text substantially corresponding to the spoken utterance, wherein the dictation text is tuned for speech that is typical of navigation destination entry types; and querying the text data of the navigation system data with the dictation text using an approximate string matching criteria and producing a results list associated therewith. 16. The non-transitory computer-readable media of claim 15 , wherein the approximate string matching criteria includes a partial text search. | 0.634715 |
8,010,560 | 1 | 4 | 1. One or more computer-readable storage media comprising computer-executable instructions to perform a method of facilitating access to a resource, the method comprising: creating a first answer set that comprises a first assertion, a first variable, and a first constraint that have been chosen, said first answer set satisfying one or more conditions comprising: that a first set of assertions that comprises or is derived from said first answer set will, when presented to a guard that controls access to the resource, cause said guard to find that a query evaluates to true under a policy implemented by said guard; creating a second answer set that comprises a second assertion, a second variable, and a second constraint that have been chosen, said second answer set satisfying one or more conditions comprising: that a second set of assertions that comprises or is derived from said second answer set will, when presented to said guard, cause said guard to find that said query evaluates to true under said policy; determining that said first answer set is not subsumed by said second answer set; and providing a solution that comprises said first answer set. | 1. One or more computer-readable storage media comprising computer-executable instructions to perform a method of facilitating access to a resource, the method comprising: creating a first answer set that comprises a first assertion, a first variable, and a first constraint that have been chosen, said first answer set satisfying one or more conditions comprising: that a first set of assertions that comprises or is derived from said first answer set will, when presented to a guard that controls access to the resource, cause said guard to find that a query evaluates to true under a policy implemented by said guard; creating a second answer set that comprises a second assertion, a second variable, and a second constraint that have been chosen, said second answer set satisfying one or more conditions comprising: that a second set of assertions that comprises or is derived from said second answer set will, when presented to said guard, cause said guard to find that said query evaluates to true under said policy; determining that said first answer set is not subsumed by said second answer set; and providing a solution that comprises said first answer set. 4. The one or more computer-readable storage media of claim 1 , wherein said first answer set comprises a third set of one or more abduced assertions that comprise said first assertion, wherein said second answer set comprises a fourth set of one or more abduced assertions that comprise said second assertion, wherein said third set involves a first collection of one or more variables that comprise said first variable, wherein said fourth set involves a second collection of one or more variables that comprise said second variable, and wherein said determining comprises: determining whether there is a substitution under which: said fourth set, is a superset of, or the same set as said third set, with said first collection of one or more variables substituted according to said substitution. | 0.611111 |
9,966,112 | 19 | 27 | 19. A computer implemented method of automatically generating a playlist of snippets of multimedia content, the method comprising: receiving multimedia content on a user device; generating a first plurality of snippets from the received multimedia content according to a specified parameter; selecting a second plurality of snippets from the first plurality of snippets according to a predefined threshold; ordering the second plurality of snippets in a playlist according to a start time of each snippet in the ordered playlist; and processing snippets from the ordered playlist that are overlapping to automatically remove duplication of multimedia content from the ordered playlist and generate a final playlist with non-overlapping snippets. | 19. A computer implemented method of automatically generating a playlist of snippets of multimedia content, the method comprising: receiving multimedia content on a user device; generating a first plurality of snippets from the received multimedia content according to a specified parameter; selecting a second plurality of snippets from the first plurality of snippets according to a predefined threshold; ordering the second plurality of snippets in a playlist according to a start time of each snippet in the ordered playlist; and processing snippets from the ordered playlist that are overlapping to automatically remove duplication of multimedia content from the ordered playlist and generate a final playlist with non-overlapping snippets. 27. The computer implemented method of claim 19 , wherein the specified parameter is an indication of a user request to generate one or more snippets. | 0.904459 |
8,644,458 | 1 | 9 | 1. A method for processing a call, the method comprising: receiving a call from a caller over a communication network; determining a telephone number of the caller; determining if the telephone number of the caller is a telephone number assigned to a specific individual; accessing an electronic database to determine a stored language preference of the specific individual when the telephone number of the caller is determined to be assigned to a specific individual, the specific individual's stored language preference being associated with the caller's telephone number in the electronic database; prompting the caller to select a language preference when the telephone number of the caller is determined to be assigned to a specific individual and the specific individual does not have a stored language preference, and storing the language preference selected by the caller based on the prompting in the electronic database; routing the call to a predetermined destination based on the stored language preference of the specific individual in the electronic database when the telephone number of the caller is determined to be assigned to the specific individual; routing the call to a first default destination when the telephone number of the caller is determined to not be assigned to a specific individual. | 1. A method for processing a call, the method comprising: receiving a call from a caller over a communication network; determining a telephone number of the caller; determining if the telephone number of the caller is a telephone number assigned to a specific individual; accessing an electronic database to determine a stored language preference of the specific individual when the telephone number of the caller is determined to be assigned to a specific individual, the specific individual's stored language preference being associated with the caller's telephone number in the electronic database; prompting the caller to select a language preference when the telephone number of the caller is determined to be assigned to a specific individual and the specific individual does not have a stored language preference, and storing the language preference selected by the caller based on the prompting in the electronic database; routing the call to a predetermined destination based on the stored language preference of the specific individual in the electronic database when the telephone number of the caller is determined to be assigned to the specific individual; routing the call to a first default destination when the telephone number of the caller is determined to not be assigned to a specific individual. 9. The method of claim 1 , wherein the predetermined destination is an automated interactive voice response unit that implements a language associated with the stored language preference of the specific individual. | 0.783401 |
8,417,528 | 13 | 15 | 13. The method of claim 12 , further comprising: converting the phoneme graph to a word-phoneme graph, the word-phoneme graph assigning a word and associated phonetic transcription to each edge. | 13. The method of claim 12 , further comprising: converting the phoneme graph to a word-phoneme graph, the word-phoneme graph assigning a word and associated phonetic transcription to each edge. 15. The method according to claim 13 , further comprising: determining and adding phoneme sequence hypotheses to the phoneme graph thereby providing an extended phoneme graph, and wherein the word-phoneme graph is based on the extended phoneme graph. | 0.855491 |
9,302,393 | 7 | 8 | 7. The auditory RRC-humanoid robot of claim 1 , wherein the DHTD specification comprises a programming methodology that is used to program each auditory TSM. | 7. The auditory RRC-humanoid robot of claim 1 , wherein the DHTD specification comprises a programming methodology that is used to program each auditory TSM. 8. The auditory RRC-humanoid robot of claim 7 further comprising a declarative memory system comprising all programmed auditory TSMs within the RRC. | 0.969472 |
9,613,153 | 1 | 5 | 1. A method comprising: identifying, by a social networking system, a target user of the social networking system as being engaged in malicious activity performed on the social networking system; identifying, by the social networking system, an object maintained by the social networking system associated with the malicious activity; identifying, by the social networking system, objects connected to the target user through the social networking system and disabled by the social networking system; retrieving, by the social networking system, information describing a type of remedial action taken by the social networking system to disable one or more of the identified objects connected to the target user; calculating, by a computer processor of the social networking system, a disabled connectivity score for the target user based at least in part on the retrieved information, the disabled connectivity score indicating a relationship between the target user and the identified objects that were disabled by the social networking system; and performing, by the social networking system, an action affecting the object associated with the malicious activity based on the calculated disabled connectivity score. | 1. A method comprising: identifying, by a social networking system, a target user of the social networking system as being engaged in malicious activity performed on the social networking system; identifying, by the social networking system, an object maintained by the social networking system associated with the malicious activity; identifying, by the social networking system, objects connected to the target user through the social networking system and disabled by the social networking system; retrieving, by the social networking system, information describing a type of remedial action taken by the social networking system to disable one or more of the identified objects connected to the target user; calculating, by a computer processor of the social networking system, a disabled connectivity score for the target user based at least in part on the retrieved information, the disabled connectivity score indicating a relationship between the target user and the identified objects that were disabled by the social networking system; and performing, by the social networking system, an action affecting the object associated with the malicious activity based on the calculated disabled connectivity score. 5. The method of claim 1 , wherein calculating, by the computer processor of the social networking system, the disabled connectivity score comprises: associating weights with different types of remedial actions taken by the social networking system to disable one or more of the identified objects connected to the target user; and determining the disabled connectivity score based at least in part on the associated weights. | 0.685651 |
9,659,003 | 1 | 4 | 1. An apparatus comprising: a processor; a memory that stores code executable by the processor, the code comprising: code that identifies one or more user specific terms in a user generated portion of text, wherein the one or more user specific terms each have a user specific meaning; code that determines the user specific meaning corresponding to the one or more user specific terms, wherein the user specific meaning has a meaning local to the apparatus and stored on the apparatus, and the meaning local to the apparatus comprises a meaning found in a location selected from the group comprising a contact list, a browser, and a list of installed applications; code that dynamically modifies the portion of text by replacing one or more of the user specific terms with general tokens as a direct result of the code identifying the one or more user specific terms in the user generated portion of text; code that converts the modified portion of text using the user specific meaning corresponding to the one or more user specific terms to one or more commands to be executed by the processor as a direct result of the code dynamically modifying the portion of the text; and code that executes the one or more commands in response to converting the modified portion. | 1. An apparatus comprising: a processor; a memory that stores code executable by the processor, the code comprising: code that identifies one or more user specific terms in a user generated portion of text, wherein the one or more user specific terms each have a user specific meaning; code that determines the user specific meaning corresponding to the one or more user specific terms, wherein the user specific meaning has a meaning local to the apparatus and stored on the apparatus, and the meaning local to the apparatus comprises a meaning found in a location selected from the group comprising a contact list, a browser, and a list of installed applications; code that dynamically modifies the portion of text by replacing one or more of the user specific terms with general tokens as a direct result of the code identifying the one or more user specific terms in the user generated portion of text; code that converts the modified portion of text using the user specific meaning corresponding to the one or more user specific terms to one or more commands to be executed by the processor as a direct result of the code dynamically modifying the portion of the text; and code that executes the one or more commands in response to converting the modified portion. 4. The apparatus of claim 1 , wherein the general tokens comprise general language. | 0.821121 |
8,174,559 | 20 | 24 | 20. A videoconferencing apparatus, comprising: means for generating compressed video data from a videoconferencing video stream; means for generating a compressed audio data based on a videoconferencing audio stream; means for generating text data based on the videoconferencing audio stream; and means for generating time alignment information indicative of a time of generation of the compressed video, audio, and text data and operable for time aligning the compressed video data, compressed audio data, and the text data. | 20. A videoconferencing apparatus, comprising: means for generating compressed video data from a videoconferencing video stream; means for generating a compressed audio data based on a videoconferencing audio stream; means for generating text data based on the videoconferencing audio stream; and means for generating time alignment information indicative of a time of generation of the compressed video, audio, and text data and operable for time aligning the compressed video data, compressed audio data, and the text data. 24. An apparatus as in claim 20 , further comprising means for transmitting the compressed video data, the compressed audio data, the text data, and the time alignment information. | 0.829222 |
8,010,343 | 16 | 18 | 16. At least one tangible computer readable storage medium encoded with instructions that, when executed by at least one processing unit, perform a method for generating grammars for use in an interactive application, wherein the grammars are generated from a data record source and each data record includes one or more fields, the method comprising: prior to identifying, in response to a user-issued query, a set of the data records that satisfy the query and on which disambiguation is to be performed, receiving human input specifying on which of the fields of each of the data records homonym and/or synonym disambiguation is to be performed; resolving ambiguities relating to at least one homophone and/or at least one synonym in data in the specified fields to generate disambiguated data; and based on the disambiguated data, generating one or more grammar files for use in the interactive application. | 16. At least one tangible computer readable storage medium encoded with instructions that, when executed by at least one processing unit, perform a method for generating grammars for use in an interactive application, wherein the grammars are generated from a data record source and each data record includes one or more fields, the method comprising: prior to identifying, in response to a user-issued query, a set of the data records that satisfy the query and on which disambiguation is to be performed, receiving human input specifying on which of the fields of each of the data records homonym and/or synonym disambiguation is to be performed; resolving ambiguities relating to at least one homophone and/or at least one synonym in data in the specified fields to generate disambiguated data; and based on the disambiguated data, generating one or more grammar files for use in the interactive application. 18. The at least one tangible computer readable storage medium of claim 16 , the method further comprising: identifying annotation fields, the annotation fields representing additional disambiguation fields used to further resolve ambiguities. | 0.752041 |
7,494,046 | 21 | 25 | 21. A method comprising: (a) receiving a stack of documents comprising a plurality of checks into an interior area of a housing through an opening in the housing while in stack form, wherein the housing is a housing of an automated banking machine including a currency dispenser device and operative to cause at least one document to be dispensed from the housing through the opening, wherein the opening is in communication with the interior area; (b) subsequent to step (a), operating the machine to move the stack received in step (a) in the housing in a direction away from the opening while remaining in stack form; (c) subsequent to step (b), separating each check individually from the stack through operation of an unstack device in the housing; (d) generating an electronic image of at least a portion of each check through operation of an imaging device in the housing. | 21. A method comprising: (a) receiving a stack of documents comprising a plurality of checks into an interior area of a housing through an opening in the housing while in stack form, wherein the housing is a housing of an automated banking machine including a currency dispenser device and operative to cause at least one document to be dispensed from the housing through the opening, wherein the opening is in communication with the interior area; (b) subsequent to step (a), operating the machine to move the stack received in step (a) in the housing in a direction away from the opening while remaining in stack form; (c) subsequent to step (b), separating each check individually from the stack through operation of an unstack device in the housing; (d) generating an electronic image of at least a portion of each check through operation of an imaging device in the housing. 25. The method according to claim 21 and further comprising: (e) receiving information identifying an account of a user providing the stack of documents received in step (a), through at least one input device in supporting connection with the housing; (f) crediting the account for at least one check in the stack received in step (a) through operation of the machine; (g) dispensing at least one currency sheet from the machine through the opening through operation of the currency dispenser device; (h) assessing the account for the dispense of the at least one currency sheet in step (g). | 0.603887 |
8,392,438 | 12 | 17 | 12. A server comprising hardware configured to perform operations comprising: obtaining two words to be identified; determining that a shortest edit distance between the two words is less than or equal to an edit distance threshold; determining whether both of the two words exist in a preset knowledge database; if at least one of the two words does not exist in the preset knowledge database, segmenting one or more unfound words; determining whether all of the words after segmentation exist in the knowledge database; and if all of the words after segmentation exist in the knowledge database, finding a smallest granularity type with highest weight value for each such word in the knowledge database; and if both of the two words exist in the preset knowledge database, finding the smallest granularity type with highest weight value for each word in the knowledge database; determining whether the two words have a same smallest granularity type with highest weight value; if the two words have the same smallest granularity type with highest weight value, determining that the two words are synonyms; and if the two words do not have the same smallest granularity type with highest weight value, determining that the two words are non-synonyms. | 12. A server comprising hardware configured to perform operations comprising: obtaining two words to be identified; determining that a shortest edit distance between the two words is less than or equal to an edit distance threshold; determining whether both of the two words exist in a preset knowledge database; if at least one of the two words does not exist in the preset knowledge database, segmenting one or more unfound words; determining whether all of the words after segmentation exist in the knowledge database; and if all of the words after segmentation exist in the knowledge database, finding a smallest granularity type with highest weight value for each such word in the knowledge database; and if both of the two words exist in the preset knowledge database, finding the smallest granularity type with highest weight value for each word in the knowledge database; determining whether the two words have a same smallest granularity type with highest weight value; if the two words have the same smallest granularity type with highest weight value, determining that the two words are synonyms; and if the two words do not have the same smallest granularity type with highest weight value, determining that the two words are non-synonyms. 17. A server as recited in claim 12 , wherein the operations further comprise: receiving a query request from a user, the query request including a query term to be searched; searching the query term in the synonym database to find a synonym of the query term; conducting a search by using the query term and the synonym of the query term; and returning a result including both the query term and the synonym of the query term to the user. | 0.76797 |
8,335,754 | 1 | 3 | 1. A method of generating a document representation, the method comprising: a. receiving into a memory of a system a resource containing at least one sentence of text information, said system comprising a server and a client computer, and further receiving as user input into said memory a root concept and associating said root concept with said resource; b. producing in response to each of said at least one sentence a system-storable tree based on the root concept, the system-storable tree comprising a plurality of tree elements and grammatical relations between said tree elements, each said tree element indicating a part of-speech contained within said each sentence; c. producing in response to each said tree one or more semantic structures such that each said semantic structure comprises three said tree elements selected by said system such that said each semantic structure represents a simple clause associated with said each tree; d. storing in said memory said one or more semantic structures in association with one or more connections between common said tree elements, thereby generating a set of one or more semantic networks representing said resource; e. presenting to the user at said client computer information about said set of one or more semantic networks; f. receiving a response from the user; and g. based on said response, modifying said set of one or more semantic networks. | 1. A method of generating a document representation, the method comprising: a. receiving into a memory of a system a resource containing at least one sentence of text information, said system comprising a server and a client computer, and further receiving as user input into said memory a root concept and associating said root concept with said resource; b. producing in response to each of said at least one sentence a system-storable tree based on the root concept, the system-storable tree comprising a plurality of tree elements and grammatical relations between said tree elements, each said tree element indicating a part of-speech contained within said each sentence; c. producing in response to each said tree one or more semantic structures such that each said semantic structure comprises three said tree elements selected by said system such that said each semantic structure represents a simple clause associated with said each tree; d. storing in said memory said one or more semantic structures in association with one or more connections between common said tree elements, thereby generating a set of one or more semantic networks representing said resource; e. presenting to the user at said client computer information about said set of one or more semantic networks; f. receiving a response from the user; and g. based on said response, modifying said set of one or more semantic networks. 3. The method of claim 1 wherein presenting to the user at said client computer information about said set of one or more semantic networks comprises presenting a proposed fact comprising at least one of said one or more semantic structures. | 0.848618 |
8,661,069 | 10 | 14 | 10. A system, comprising: a memory; and a processor, connected to the memory, to: group documents into a plurality of clusters, where subsets of the documents grouped, respectively, into the plurality of clusters, are duplicative and differ from documents grouped into other ones the plurality of clusters; determine a measure of quality for each of the documents; select a representative document, respectively, for two of the plurality of clusters, based on the measure of quality; determine a target document associated with each of the representative documents; determine addresses associated with the target documents; determine that the target documents are duplicative based on the addresses associated with the target documents; and combine the target documents and the two of the plurality of clusters into a combined single cluster, in response to determining that the target documents are duplicative. | 10. A system, comprising: a memory; and a processor, connected to the memory, to: group documents into a plurality of clusters, where subsets of the documents grouped, respectively, into the plurality of clusters, are duplicative and differ from documents grouped into other ones the plurality of clusters; determine a measure of quality for each of the documents; select a representative document, respectively, for two of the plurality of clusters, based on the measure of quality; determine a target document associated with each of the representative documents; determine addresses associated with the target documents; determine that the target documents are duplicative based on the addresses associated with the target documents; and combine the target documents and the two of the plurality of clusters into a combined single cluster, in response to determining that the target documents are duplicative. 14. The system of claim 10 , where, when determining whether the target documents are duplicative based on the addresses, the processor is further to: determine the target documents are duplicative using a predictive-based clustering technique. | 0.862302 |
7,646,317 | 15 | 16 | 15. The apparatus of claim 9 , wherein the mapping comprises an output control module, which is coupled to the input sequence divider for receiving the text input and the control input. | 15. The apparatus of claim 9 , wherein the mapping comprises an output control module, which is coupled to the input sequence divider for receiving the text input and the control input. 16. The apparatus of claim 15 , wherein the mapping further comprises a dictionary module, which is coupled to the output control module for receiving the text input and looks up the decoding sequence corresponding to the text input from a dictionary. | 0.888046 |
7,917,860 | 1 | 2 | 1. A method of applying styles to an object within a user interface during runtime, comprising: during runtime, ascertaining a first style and a second style associated with said object, wherein said object, said first style, and said second style are described in a high-level language, the high-level language description of the first style having been determined through operations comprising: displaying a graphical design interface, the graphical design interface comprising a graphical design element, the graphical design interface accepting input corresponding to defining a user interface, the user interface corresponding to a program; receiving input at the graphical design interface, the input corresponding to interaction with a graphical element of the graphical design interface; determining the first style corresponding to the input, the first style comprising a named set of at least one property and a corresponding value assignment, the first style corresponding to a selected object of the user interface displayed by the graphical design interface; and storing the style in the high-level language format; assigning a first property of the first style and the corresponding value assignment to the object, a property comprising a graphical attribute of the object in the user interface; assigning a second property of the first style and the corresponding value assignment to the object; determining that a third property of the second style and the corresponding value assignment is not to be assigned to the object because the third property is overridden by the first property; assigning a fourth property of the second style and the corresponding value assignment to the object because the fourth property is not overridden by a property of the first style; and displaying the object in the user interface with the first property's value assignment, the second property's value assignment, and the fourth property's value assignment. | 1. A method of applying styles to an object within a user interface during runtime, comprising: during runtime, ascertaining a first style and a second style associated with said object, wherein said object, said first style, and said second style are described in a high-level language, the high-level language description of the first style having been determined through operations comprising: displaying a graphical design interface, the graphical design interface comprising a graphical design element, the graphical design interface accepting input corresponding to defining a user interface, the user interface corresponding to a program; receiving input at the graphical design interface, the input corresponding to interaction with a graphical element of the graphical design interface; determining the first style corresponding to the input, the first style comprising a named set of at least one property and a corresponding value assignment, the first style corresponding to a selected object of the user interface displayed by the graphical design interface; and storing the style in the high-level language format; assigning a first property of the first style and the corresponding value assignment to the object, a property comprising a graphical attribute of the object in the user interface; assigning a second property of the first style and the corresponding value assignment to the object; determining that a third property of the second style and the corresponding value assignment is not to be assigned to the object because the third property is overridden by the first property; assigning a fourth property of the second style and the corresponding value assignment to the object because the fourth property is not overridden by a property of the first style; and displaying the object in the user interface with the first property's value assignment, the second property's value assignment, and the fourth property's value assignment. 2. The method of claim 1 , further comprising applying local properties on said object. | 0.866972 |
9,588,637 | 1 | 6 | 1. A method, comprising: receiving, by a client device and from a remote host, data associated with a user interface component of an application executing within a virtual machine hosted by the remote host; and rendering, by the client device, within a user interface associated with the client device, and with a graphical appearance based on at least one user interface component of the user interface associated with the client device, a user interface component corresponding to the user interface component of the application executing within the virtual machine hosted by the remote host. | 1. A method, comprising: receiving, by a client device and from a remote host, data associated with a user interface component of an application executing within a virtual machine hosted by the remote host; and rendering, by the client device, within a user interface associated with the client device, and with a graphical appearance based on at least one user interface component of the user interface associated with the client device, a user interface component corresponding to the user interface component of the application executing within the virtual machine hosted by the remote host. 6. The method of claim 1 , wherein rendering the user interface component corresponding to the user interface component comprises rendering the user interface component corresponding to the user interface component in at least one of a taskbar of the user interface associated with the client device or a dock of the user interface associated with the client device, the method comprising: determining, based on an identifier associated with the user interface component of the application executing within the virtual machine and a plurality of identifiers associated with the at least one of the taskbar of the user interface associated with the client device or the dock of the user interface associated with the client device, whether the at least one of the taskbar of the user interface associated with the client device or the dock of the user interface associated with the client device includes a group corresponding to the application executing within the virtual machine. | 0.557259 |
10,055,128 | 13 | 15 | 13. The one or more non-transitory computer-readable media of claim 12 , wherein the instructions further include instructions which, when executed by one or more hardware processors, cause determining whether a suitability metric evaluated over the sub-tree rooted at said each node exceeds a threshold value. | 13. The one or more non-transitory computer-readable media of claim 12 , wherein the instructions further include instructions which, when executed by one or more hardware processors, cause determining whether a suitability metric evaluated over the sub-tree rooted at said each node exceeds a threshold value. 15. The one or more non-transitory computer-readable media of claim 13 , wherein the suitability metric is based at least on one of a processing speed or I/O speed of a computer. | 0.951393 |
10,154,321 | 1 | 3 | 1. A computer system comprising a data processing apparatus for executing a computer program tangibly embodied in a machine-readable non-transitory medium for registering sensors, comprising: an interface adapted to receive a query, wherein the query is related to a specific event for a target system state, wherein the specific event is associated with a specific activity pattern; a decomposer configured to decompose the query into semantic expressions describing the target system state, and to identify a database entry associated with a semantic expression resulting from the decomposition; a retriever configured to retrieve behavioral data which corresponds to the identified database entry, wherein the behavioral data includes dependencies between elements of the behavioral data identifying the specific activity pattern, wherein the specific activity pattern is associated with a plurality of activity data structures; and a registration component configured to register at least one sensor, wherein the at least one sensor is assigned to the plurality of activity data structures. | 1. A computer system comprising a data processing apparatus for executing a computer program tangibly embodied in a machine-readable non-transitory medium for registering sensors, comprising: an interface adapted to receive a query, wherein the query is related to a specific event for a target system state, wherein the specific event is associated with a specific activity pattern; a decomposer configured to decompose the query into semantic expressions describing the target system state, and to identify a database entry associated with a semantic expression resulting from the decomposition; a retriever configured to retrieve behavioral data which corresponds to the identified database entry, wherein the behavioral data includes dependencies between elements of the behavioral data identifying the specific activity pattern, wherein the specific activity pattern is associated with a plurality of activity data structures; and a registration component configured to register at least one sensor, wherein the at least one sensor is assigned to the plurality of activity data structures. 3. The computer system of claim 1 , further comprising: a generator component configured to generate new behavioral data based on the query and the plurality of activity data structures. | 0.764557 |
9,053,361 | 1 | 10 | 1. A method of identifying regions to merge, in an image of a scene of real world captured by a camera in a handheld device, the method of identifying regions comprising: checking whether a first block, which contains a first region of pixels that are contiguous with one another and comprising a local extrema of intensity in the image, satisfies a predetermined test, for presence along a line, of pixels with intensities binarizable to a common value; marking the first block as pixel-line-present, in a memory, when a result of the checking indicates the predetermined test is satisfied; identifying a second block that is located in the image adjacent to the first block, wherein at least the first block is marked as pixel-line-present; merging a first set of positions indicative of the first region of pixels in the first block with a second set of positions indicative of a second region of pixels in the second block to obtain a merged set of positions in a merged block, when a predetermined rule is satisfied by one or more geometric attributes of the first block and the second block; wherein the first region of pixels and the second region of pixels do not contact one another in the merged block; wherein the merging is performed prior to classification of any pixel in the first region of pixels and in the second region of pixels as text or non-text; and re-doing the checking, on the merged block, to determine whether the merged block satisfies the predetermined test; wherein one or more of the checking, the marking, the identifying, the merging, and the re-doing are performed by at least one processor coupled to the memory. | 1. A method of identifying regions to merge, in an image of a scene of real world captured by a camera in a handheld device, the method of identifying regions comprising: checking whether a first block, which contains a first region of pixels that are contiguous with one another and comprising a local extrema of intensity in the image, satisfies a predetermined test, for presence along a line, of pixels with intensities binarizable to a common value; marking the first block as pixel-line-present, in a memory, when a result of the checking indicates the predetermined test is satisfied; identifying a second block that is located in the image adjacent to the first block, wherein at least the first block is marked as pixel-line-present; merging a first set of positions indicative of the first region of pixels in the first block with a second set of positions indicative of a second region of pixels in the second block to obtain a merged set of positions in a merged block, when a predetermined rule is satisfied by one or more geometric attributes of the first block and the second block; wherein the first region of pixels and the second region of pixels do not contact one another in the merged block; wherein the merging is performed prior to classification of any pixel in the first region of pixels and in the second region of pixels as text or non-text; and re-doing the checking, on the merged block, to determine whether the merged block satisfies the predetermined test; wherein one or more of the checking, the marking, the identifying, the merging, and the re-doing are performed by at least one processor coupled to the memory. 10. The method of claim 1 further comprising: prior to the checking, selecting the predetermined rule based at least on a language identified by user input. | 0.887931 |
9,601,112 | 9 | 10 | 9. The speech recognition system of claim 1 , wherein the speech recognizer comprises: a pre-processing part configured to pre-process speech signals inputted from the user device; a recognition part configured to perform speech recognition using feature-extracted data provided from the pre-processing part and the acoustic model selected by the model selector; and a reliability determining part configured to determine reliability of a result of speech recognition from the recognition part, output a result with the highest reliability as a recognition result, and transmit phonetic information, data and the device key to the model manager when the reliability exceeds a threshold value. | 9. The speech recognition system of claim 1 , wherein the speech recognizer comprises: a pre-processing part configured to pre-process speech signals inputted from the user device; a recognition part configured to perform speech recognition using feature-extracted data provided from the pre-processing part and the acoustic model selected by the model selector; and a reliability determining part configured to determine reliability of a result of speech recognition from the recognition part, output a result with the highest reliability as a recognition result, and transmit phonetic information, data and the device key to the model manager when the reliability exceeds a threshold value. 10. The speech recognition system of claim 9 , wherein the recognition part receives a plurality of acoustic models from the model selector and performs parallel speech recognition for the plurality of acoustic models. | 0.935995 |
9,940,933 | 26 | 28 | 26. A speech recognition apparatus comprising: a processor configured to: perform a first recognition, to recognize a sentence from speech expressed by a user using an acoustic model and a first linguistic model; perform a second recognition, to generate another sentence for the speech, by respectively substituting, to improve the accuracy of the sentence by using the acoustic model and a second linguistic model, at least one target word of the sentence, determined as being most likely incorrect through a processor evaluation of the words of the sentence using the second linguistic model having a higher complexity than the first linguistic model, with a selected one or more of sampled candidate words that are processor selected based on suitability evaluations of the sampled candidate words using the acoustic model and the second linguistic model. | 26. A speech recognition apparatus comprising: a processor configured to: perform a first recognition, to recognize a sentence from speech expressed by a user using an acoustic model and a first linguistic model; perform a second recognition, to generate another sentence for the speech, by respectively substituting, to improve the accuracy of the sentence by using the acoustic model and a second linguistic model, at least one target word of the sentence, determined as being most likely incorrect through a processor evaluation of the words of the sentence using the second linguistic model having a higher complexity than the first linguistic model, with a selected one or more of sampled candidate words that are processor selected based on suitability evaluations of the sampled candidate words using the acoustic model and the second linguistic model. 28. The apparatus of claim 26 , wherein, for the second recognition, the processor is configured to obtain the candidate words based on the target word, and select the one or more of sampled candidate words for improving the accuracy of the sentence. | 0.875869 |
7,756,313 | 1 | 3 | 1. A method for computer aided detection of anatomical abnormalities in medical images comprising the steps of: providing a plurality of abnormality candidates and features of said abnormality candidates; and classifying said abnormality candidates as true positives or false positives using a hierarchical cascade of linear classifiers of the form sign(w T x+b), wherein x is a feature vector, w is a weighting vector and b is a model parameter, wherein different weights are used to penalize false negatives and false positives, and wherein more computationally complex features are used for each successive stage of said cascade of classifiers, wherein each stage of said cascade solves a linear program formulated using a training error rate ξ equivalent to max {0,1−y(w T x+b)} and an l 1 -norm equivalent to w 1 = ∑ w i summed over all features, wherein said linear program is equivalent to the system represented by min u , v , ξ λ ∑ j = 1 d ( u j + v j ) + μ l + ∑ i ∈ C + ξ i + 1 - μ l - ∑ i ∈ C - ξ i , y ( ∑ j X ij ( u j - v j ) + b ) + ξ i ≥ 1 , such that ξ i ≥ 0 , i = 1 , … , l , u j , v j ≥ 0 , j = 1 , … , d , ( 1 ) wherein λ>0 is a regularization parameter, {x i , y i }, i=1, . . . , l denotes the abnormality candidates, y denotes a label indicating whether or not a candidate associated with a feature vector is a true positive, X denotes a feature matrix of d features wherein each row represents candidate feature vector x, and each column specifies a feature, l + is the number of positive candidates and l − the number of negative candidates, C + and C − contain, respectively, the sets of indices of positive candidates and negative candidates, 0≦μ≦1 is a tuning parameter for combining the false negative rate and false positive rate, and w j =u j −v j . | 1. A method for computer aided detection of anatomical abnormalities in medical images comprising the steps of: providing a plurality of abnormality candidates and features of said abnormality candidates; and classifying said abnormality candidates as true positives or false positives using a hierarchical cascade of linear classifiers of the form sign(w T x+b), wherein x is a feature vector, w is a weighting vector and b is a model parameter, wherein different weights are used to penalize false negatives and false positives, and wherein more computationally complex features are used for each successive stage of said cascade of classifiers, wherein each stage of said cascade solves a linear program formulated using a training error rate ξ equivalent to max {0,1−y(w T x+b)} and an l 1 -norm equivalent to w 1 = ∑ w i summed over all features, wherein said linear program is equivalent to the system represented by min u , v , ξ λ ∑ j = 1 d ( u j + v j ) + μ l + ∑ i ∈ C + ξ i + 1 - μ l - ∑ i ∈ C - ξ i , y ( ∑ j X ij ( u j - v j ) + b ) + ξ i ≥ 1 , such that ξ i ≥ 0 , i = 1 , … , l , u j , v j ≥ 0 , j = 1 , … , d , ( 1 ) wherein λ>0 is a regularization parameter, {x i , y i }, i=1, . . . , l denotes the abnormality candidates, y denotes a label indicating whether or not a candidate associated with a feature vector is a true positive, X denotes a feature matrix of d features wherein each row represents candidate feature vector x, and each column specifies a feature, l + is the number of positive candidates and l − the number of negative candidates, C + and C − contain, respectively, the sets of indices of positive candidates and negative candidates, 0≦μ≦1 is a tuning parameter for combining the false negative rate and false positive rate, and w j =u j −v j . 3. The method of claim 1 , wherein a false negative penalty is set to infinity for the early stages of said cascade of classifiers. | 0.91255 |
9,342,581 | 15 | 16 | 15. A system comprising: program code comprising: an object management system to call a constructor to register an interface to a description of a persistent class; and a database management system kernel to access the registered interface to determine an internal structure of the persistent class, to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object, to determine, based on the determined internal structure, members of the persistent database object that are filled with default values, to store the persistent database object in a database, to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database, to read the persistent database object from the database after the storing of the persistent database object in the database, and to, after the reading of the persistent database object from the database, populate the determined members of the persistent database object with the default values of the persistent database object that were removed from the persistent database object before the storing of the persistent database object to reduce storage demands on the database; and at least one processor to execute the program code. | 15. A system comprising: program code comprising: an object management system to call a constructor to register an interface to a description of a persistent class; and a database management system kernel to access the registered interface to determine an internal structure of the persistent class, to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object, to determine, based on the determined internal structure, members of the persistent database object that are filled with default values, to store the persistent database object in a database, to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database, to read the persistent database object from the database after the storing of the persistent database object in the database, and to, after the reading of the persistent database object from the database, populate the determined members of the persistent database object with the default values of the persistent database object that were removed from the persistent database object before the storing of the persistent database object to reduce storage demands on the database; and at least one processor to execute the program code. 16. The system according to claim 15 , the object management system to register the persistent class and the interface. | 0.850503 |
8,775,923 | 21 | 28 | 21. A system for restoring web pages, comprising: a root node identifier, implemented on a computing device and configured to: identify a root node of a node graph based on a scripting language object list remaining after garbage collection of a scripting language heap of a web page, wherein each node of the node graph represents an object of a plurality of objects that form a last state of the web page, wherein the plurality of objects includes at least one scripting language object that refers to a document object model (DOM) object; traverse the node graph to a next frontier node; determine an object identifier of the next frontier node; and an object queue builder, implemented on the computing device and configured to store the object identifier and object properties associated with the object identified by the object identifier into a queue of objects when the object identifier of the next frontier node is not found in the queue of objects, whereby the queue of objects is used to restore objects with object properties having values according to the last state of the web page. | 21. A system for restoring web pages, comprising: a root node identifier, implemented on a computing device and configured to: identify a root node of a node graph based on a scripting language object list remaining after garbage collection of a scripting language heap of a web page, wherein each node of the node graph represents an object of a plurality of objects that form a last state of the web page, wherein the plurality of objects includes at least one scripting language object that refers to a document object model (DOM) object; traverse the node graph to a next frontier node; determine an object identifier of the next frontier node; and an object queue builder, implemented on the computing device and configured to store the object identifier and object properties associated with the object identified by the object identifier into a queue of objects when the object identifier of the next frontier node is not found in the queue of objects, whereby the queue of objects is used to restore objects with object properties having values according to the last state of the web page. 28. The system of claim 21 , further comprising a web page restorer configured to restore event handlers for stored scripting language functions with corresponding values according to the last state of the web page. | 0.573413 |
8,094,905 | 7 | 8 | 7. The system according to claim 1 , wherein the first selecting means for enabling the user to select a graphical and/or textual information which represents two or more data which are represented to said graphical and/or textual information and wherein the first generating means for generating generate first data for at least some or all of said data which are represented by said graphical and/or textual information. | 7. The system according to claim 1 , wherein the first selecting means for enabling the user to select a graphical and/or textual information which represents two or more data which are represented to said graphical and/or textual information and wherein the first generating means for generating generate first data for at least some or all of said data which are represented by said graphical and/or textual information. 8. The system according to claim 7 , wherein the first data are grouped according to a first criterion and wherein the changing means are adapted for changing said first criterion to said at least one second criterion for each of said first data upon activation by said triggering means. | 0.84436 |
9,594,835 | 7 | 8 | 7. The method as recited in claim 6 , wherein each of the documents is associated with a corresponding one of a plurality of categories, the method further comprising: providing an indicator identifying each of one or more of the plurality of categories in association with corresponding document(s) in the provided set of previously clicked documents. | 7. The method as recited in claim 6 , wherein each of the documents is associated with a corresponding one of a plurality of categories, the method further comprising: providing an indicator identifying each of one or more of the plurality of categories in association with corresponding document(s) in the provided set of previously clicked documents. 8. The method as recited in claim 7 , wherein each of the plurality of categories corresponds to a different web site, data source, database, or document type. | 0.948242 |
8,850,309 | 1 | 3 | 1. A method of analyzing and processing an expression of the XPath type for evaluating said expression on a set of data of the binary XML type, an XPath type expression selecting relevant XML data, said set of data of the binary XML type being associated with at least one decoding table, the method comprising the following steps: generating a list comprising a set of at least one target from said expression of the XPath type, said at least one target being associated with a selection of XML data and representing a step in an evaluation of said expression of the XPath type; determining, for said at least one target, a parameter representing a discriminating character of said at least one target, based on a number of selected XML data associated with the at least one target, the at least one target being less discriminating as the number of selected XML data associated with the at least one target increases; linking the parameter representing a discriminating character with the at least one target; integrating the at least one target and linked parameter representing a discriminating character to said at least one decoding table; accessing at least one part of said set of data of the binary XML type; identifying at least one reference to an item in said at least one decoding table using said at least one part of said set of data of the binary XML type; and accessing said at least one target integrated to said at least one decoding table using said at least one reference. | 1. A method of analyzing and processing an expression of the XPath type for evaluating said expression on a set of data of the binary XML type, an XPath type expression selecting relevant XML data, said set of data of the binary XML type being associated with at least one decoding table, the method comprising the following steps: generating a list comprising a set of at least one target from said expression of the XPath type, said at least one target being associated with a selection of XML data and representing a step in an evaluation of said expression of the XPath type; determining, for said at least one target, a parameter representing a discriminating character of said at least one target, based on a number of selected XML data associated with the at least one target, the at least one target being less discriminating as the number of selected XML data associated with the at least one target increases; linking the parameter representing a discriminating character with the at least one target; integrating the at least one target and linked parameter representing a discriminating character to said at least one decoding table; accessing at least one part of said set of data of the binary XML type; identifying at least one reference to an item in said at least one decoding table using said at least one part of said set of data of the binary XML type; and accessing said at least one target integrated to said at least one decoding table using said at least one reference. 3. The method according to claim 1 , further comprising a step of analyzing said at least one target, said parameter representing a discriminating character of said at least one target being determined according to the result of said analysis of said at least one target. | 0.719462 |
9,195,650 | 1 | 4 | 1. A method for translating a first text in a first language style into a second text in a second language style, the method comprising acts of: performing, by at least one processor, natural language understanding (NLU) processing on the first text to obtain at least one semantic representation of the first text; and using, by the at least one processor, the at least one semantic representation to generate the second text in the second language style, the second language style being different from the first language style, wherein the act of using the at least one semantic representation to generate the second text comprises: identifying, from the first text, at least one first word or phrase that occurs in a first corpus, wherein the first corpus comprises a first plurality of texts in the first language style; mapping the at least one first word or phrase to at least one second word or phrase that occurs in a second corpus, wherein the second corpus comprises a second plurality of texts in the second language style, the second plurality of texts in the second corpus being in a same language as the first plurality of texts in the first corpus; and using the at least one semantic representation and the at least one second word or phrase to generate the second text. | 1. A method for translating a first text in a first language style into a second text in a second language style, the method comprising acts of: performing, by at least one processor, natural language understanding (NLU) processing on the first text to obtain at least one semantic representation of the first text; and using, by the at least one processor, the at least one semantic representation to generate the second text in the second language style, the second language style being different from the first language style, wherein the act of using the at least one semantic representation to generate the second text comprises: identifying, from the first text, at least one first word or phrase that occurs in a first corpus, wherein the first corpus comprises a first plurality of texts in the first language style; mapping the at least one first word or phrase to at least one second word or phrase that occurs in a second corpus, wherein the second corpus comprises a second plurality of texts in the second language style, the second plurality of texts in the second corpus being in a same language as the first plurality of texts in the first corpus; and using the at least one semantic representation and the at least one second word or phrase to generate the second text. 4. The method of claim 1 , wherein the NLU processing comprises: creating a plurality of candidate semantic representations of the first text; and selecting the at least one semantic representation from the plurality of candidate semantic representations. | 0.746521 |
9,406,019 | 1 | 5 | 1. A computer-implemented method comprising: receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output; generating first intermediate training records by inputting input data of a first subset of the initial training records to a first trained predictive model, the first trained predictive model generated using at least a second subset of the initial training records and a training function, each first intermediate training record having a first score; generating second intermediate training records by inputting input data of the second subset of the initial training records to a second trained predictive model, the second trained predictive model generated using the training function and at least the first subset of the initial training records, each second intermediate training record having a second score; and generating, for the first trained predictive model and the second trained predictive model, a score normalization model using a score normalization training function, the first intermediate training records, and the second intermediate training records. | 1. A computer-implemented method comprising: receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output; generating first intermediate training records by inputting input data of a first subset of the initial training records to a first trained predictive model, the first trained predictive model generated using at least a second subset of the initial training records and a training function, each first intermediate training record having a first score; generating second intermediate training records by inputting input data of the second subset of the initial training records to a second trained predictive model, the second trained predictive model generated using the training function and at least the first subset of the initial training records, each second intermediate training record having a second score; and generating, for the first trained predictive model and the second trained predictive model, a score normalization model using a score normalization training function, the first intermediate training records, and the second intermediate training records. 5. The method of claim 1 , further comprising: determining a high-end value for the scores of the first and second intermediate training records, the high-end value being a value at which a specified percent of scores of the first and second intermediate training records have a score that exceeds the high-end value; identifying a first intermediate training record having a score greater than the high-end value; and changing the score of the identified first intermediate training record to be the high-end value. | 0.708475 |
4,516,260 | 63 | 64 | 63. A talking electronic apparatus as set forth in claim 62, wherein said means responsive to said keyboard input and to said digital data in said memory means corresponding to the correct answer responds in a manner causing said speech synthesis means and said audio means to provide an audible comment in synthesized human speech indicative of the accuracy of said operator response with respect to the correct answer for said selected word-related problem. | 63. A talking electronic apparatus as set forth in claim 62, wherein said means responsive to said keyboard input and to said digital data in said memory means corresponding to the correct answer responds in a manner causing said speech synthesis means and said audio means to provide an audible comment in synthesized human speech indicative of the accuracy of said operator response with respect to the correct answer for said selected word-related problem. 64. A talking electronic apparatus as set forth in claim 63, wherein at least some of the plurality of word-related problems involve respective requests to the operator to spell individual words and the correct answers corresponding thereto comprising the correct spelling of those words as derived from said digital speech data stored in said memory means. | 0.915881 |
8,272,009 | 1 | 8 | 1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot. | 1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot. 8. The method of claim 1 , wherein utilizing said information comprises: comparing at least a first of the non-textual targeting criteria of each of the subset of the identified assets with audience classification information for said programming. | 0.807932 |
9,047,614 | 16 | 18 | 16. The method according to claim 15 , further comprising receiving at least one instruction to associate the first element with a second attribute of the second list, associating the first element with the second attribute, removing the association between first element and the first attribute, and associating the first element and the second attribute in a second parse map. | 16. The method according to claim 15 , further comprising receiving at least one instruction to associate the first element with a second attribute of the second list, associating the first element with the second attribute, removing the association between first element and the first attribute, and associating the first element and the second attribute in a second parse map. 18. The method according to claim 16 , further comprising receiving multiple instructions to associate the first element with different attributes of the second list, determining via clustering which among the different attributes of the second list is most often instructed to be associated with the first element, and associating the attribute of the second list which is most often instructed to be associated with the first element as the second attribute, removing the association between first element and the first attribute, and associating the first element and the second attribute in a second parse map. | 0.795333 |
8,849,799 | 1 | 7 | 1. A computer implemented method of selecting supplemental content for a document, the method comprising: receiving, by a data processing system, a notification of a request coming from a user device for a document; parsing the requested document into one or more tokens and determining a token priority score for each token; selecting a subset of tokens from the one or more tokens, each token in the subset of tokens having a token priority score above a predetermined threshold value; accessing, by the data processing system, a set of Boolean query expressions stored in association with a plurality of supplemental content records; identifying a subset of Boolean query expressions from the set of Boolean query expressions, each Boolean query expression in the identified subset of Boolean query expressions satisfied by the selected subset of tokens; determining a document relevance score for each Boolean query expression in the identified subset of Boolean query expressions, wherein each determined document relevance score reflects a relevance of the requested document to a corresponding Boolean query expression; selecting a Boolean query expression from the subset of Boolean query expressions that is best satisfied by the requested document based on the determined document relevance scores; selecting a supplemental content record associated with the selected Boolean query expression; and outputting data for supplementing the requested document with content indicated by the selected supplemental content record. | 1. A computer implemented method of selecting supplemental content for a document, the method comprising: receiving, by a data processing system, a notification of a request coming from a user device for a document; parsing the requested document into one or more tokens and determining a token priority score for each token; selecting a subset of tokens from the one or more tokens, each token in the subset of tokens having a token priority score above a predetermined threshold value; accessing, by the data processing system, a set of Boolean query expressions stored in association with a plurality of supplemental content records; identifying a subset of Boolean query expressions from the set of Boolean query expressions, each Boolean query expression in the identified subset of Boolean query expressions satisfied by the selected subset of tokens; determining a document relevance score for each Boolean query expression in the identified subset of Boolean query expressions, wherein each determined document relevance score reflects a relevance of the requested document to a corresponding Boolean query expression; selecting a Boolean query expression from the subset of Boolean query expressions that is best satisfied by the requested document based on the determined document relevance scores; selecting a supplemental content record associated with the selected Boolean query expression; and outputting data for supplementing the requested document with content indicated by the selected supplemental content record. 7. The method of claim 1 , wherein the document relevance score is calculated using a number of occurrence of a token from the subset of tokens within the document and a relative frequency. | 0.811753 |
8,515,977 | 1 | 3 | 1. A computer implemented method for identifying and translating a subset of partially translated data, the method comprising the steps of: extracting by a computer a translation file from a database, the translation file comprising a plurality of English keys and translation language values, and untranslated keys, wherein the extracting forms an XML file; determining, by the computer, whether there are XML unsupported characters in the XML file; responsive to a determination that XML unsupported characters are in the XML file, the computer filtering out, from the XML file, the XML unsupported characters and translated data such that the computer deletes from the filtered XML file, data which are XML unsupported characters based on existing XML standards; formatting, by the computer, the filtered XML file; sending the data to be translated, resulting from the filtering step, to a translation center to translate; receiving translated data from the translation center; and importing a translated file into the database. | 1. A computer implemented method for identifying and translating a subset of partially translated data, the method comprising the steps of: extracting by a computer a translation file from a database, the translation file comprising a plurality of English keys and translation language values, and untranslated keys, wherein the extracting forms an XML file; determining, by the computer, whether there are XML unsupported characters in the XML file; responsive to a determination that XML unsupported characters are in the XML file, the computer filtering out, from the XML file, the XML unsupported characters and translated data such that the computer deletes from the filtered XML file, data which are XML unsupported characters based on existing XML standards; formatting, by the computer, the filtered XML file; sending the data to be translated, resulting from the filtering step, to a translation center to translate; receiving translated data from the translation center; and importing a translated file into the database. 3. The computer implemented method of claim 1 , wherein filtering out comprises selecting a placeholder corresponding to a term having no translation in the XML file. | 0.909783 |
9,672,247 | 11 | 12 | 11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to translate a first query into an edge query, the program module including: instructions for receiving the first query, wherein the first query is associated with a first type of database; instructions for translating the first query into the edge query, wherein: the edge query is associated with a graph database storing a graph; and the graph comprises nodes, edges between the nodes, and predicates to represent data with index-free adjacency; instructions for executing the edge query against the graph database, wherein the edge query identifies an edge associated with a predicate that specifies one or more of the nodes of the graph; and instructions for receiving a result in response to the edge query. | 11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to translate a first query into an edge query, the program module including: instructions for receiving the first query, wherein the first query is associated with a first type of database; instructions for translating the first query into the edge query, wherein: the edge query is associated with a graph database storing a graph; and the graph comprises nodes, edges between the nodes, and predicates to represent data with index-free adjacency; instructions for executing the edge query against the graph database, wherein the edge query identifies an edge associated with a predicate that specifies one or more of the nodes of the graph; and instructions for receiving a result in response to the edge query. 12. The apparatus of claim 11 , wherein the first type of database has a different data model than the graph database. | 0.835655 |
9,304,736 | 5 | 9 | 5. A device comprising: a housing; one or more microphones arranged in the housing to receive verbal input; one or more speakers arranged in the housing; a processor to perform one or more functions; memory accessible by the processor; a control element; and a module stored in the memory and executable by the processor to facilitate non-verbal input of a code through actuation of the control element; and a light indicator arranged to emit light externally of the housing according to multiple appearance states, wherein a first appearance state of the multiple appearance states corresponds to a first value of the code received by actuation of the control element, and a second appearance state of the multiple appearance states corresponds to a second value of the code received by actuation of the control element. | 5. A device comprising: a housing; one or more microphones arranged in the housing to receive verbal input; one or more speakers arranged in the housing; a processor to perform one or more functions; memory accessible by the processor; a control element; and a module stored in the memory and executable by the processor to facilitate non-verbal input of a code through actuation of the control element; and a light indicator arranged to emit light externally of the housing according to multiple appearance states, wherein a first appearance state of the multiple appearance states corresponds to a first value of the code received by actuation of the control element, and a second appearance state of the multiple appearance states corresponds to a second value of the code received by actuation of the control element. 9. The device of claim 5 , wherein the one or more speakers output an audible sound in coordination with actuation of the control element. | 0.930373 |
7,555,431 | 1 | 4 | 1. A speech query recognition system adapted for responding to speech-based queries system comprising: a continuous speech recognition engine for generating recognized speech data from a speech signal resulting from a speech-based query provided by a speaker; wherein said continuous speech recognition engine uses a limited speech recognition grammar of words which is loaded for a context experienced by said speaker when said speech-based query is made, said context being determined automatically by an application program executing for said speaker at a time when said speaker provides said speech-based query; a natural language engine which generates recognized speech sentence data corresponding to a meaning of said speech-based query based on said recognized speech data; one or more query/response databases for storing question/answer pairs corresponding to said speech-based query; wherein a first limited set of question/answer pairs is determined based on said context from a complete set of question/answer pairs supported by such speech query recognition system; a query formulation engine adapted for retrieving one or more question/answer pairs from said first limited set of question/answer pairs based on said recognized speech sentence data provided by said natural language engine, which natural language engine is further adapted by said context to not consider every possible word or phrase present in said complete set of question/answer pairs and only considers words and phrases present in said first limited set of question/answer pairs to determine said meaning of said recognized speech sentence data; wherein the speech query recognition system is configured so that said context controls both a limited speech recognition grammar used for speech recognition of the speech-based query and a set of one or more answers to be provided in response thereto. | 1. A speech query recognition system adapted for responding to speech-based queries system comprising: a continuous speech recognition engine for generating recognized speech data from a speech signal resulting from a speech-based query provided by a speaker; wherein said continuous speech recognition engine uses a limited speech recognition grammar of words which is loaded for a context experienced by said speaker when said speech-based query is made, said context being determined automatically by an application program executing for said speaker at a time when said speaker provides said speech-based query; a natural language engine which generates recognized speech sentence data corresponding to a meaning of said speech-based query based on said recognized speech data; one or more query/response databases for storing question/answer pairs corresponding to said speech-based query; wherein a first limited set of question/answer pairs is determined based on said context from a complete set of question/answer pairs supported by such speech query recognition system; a query formulation engine adapted for retrieving one or more question/answer pairs from said first limited set of question/answer pairs based on said recognized speech sentence data provided by said natural language engine, which natural language engine is further adapted by said context to not consider every possible word or phrase present in said complete set of question/answer pairs and only considers words and phrases present in said first limited set of question/answer pairs to determine said meaning of said recognized speech sentence data; wherein the speech query recognition system is configured so that said context controls both a limited speech recognition grammar used for speech recognition of the speech-based query and a set of one or more answers to be provided in response thereto. 4. The speech query recognition system of claim 1 , wherein dictionary files of phonemes are also loaded in accordance with said context. | 0.802594 |
9,569,415 | 6 | 7 | 6. The information processing apparatus according to claim 5 , wherein the specifying unit specifies the form of representation of the objects included in the original document by creating a list including information on the types and the number of drawing commands of objects included in the original document. | 6. The information processing apparatus according to claim 5 , wherein the specifying unit specifies the form of representation of the objects included in the original document by creating a list including information on the types and the number of drawing commands of objects included in the original document. 7. The information processing apparatus according to claim 6 , wherein the converting unit converts, in a case where there is a plurality of candidates for converting the information corresponding to the editing portion, the information corresponding to the editing portion so that the form of representation of the editing portion conforms with a form of representation of a drawing command whose number is equal to or greater than 1 in the list among the plurality of candidates. | 0.74604 |
8,407,199 | 1 | 2 | 1. Apparatus comprising: a computer system having a processor and memory; computer instructions stored in said memory accessibly to said processor and effective when executing on said processor to: respond to entry of a core search query into a search program by a computer system user by displaying to the user a plurality of geometric figures including a core figure representing a number of results delivered by the search program for the core search query and a secondary figure representing a number of results delivered for a suggested related query; display the displayed figures in varying relative sizes determined by the number of results delivered by the search program for the core search query and the number of results delivered by the search program for the suggested query, with a larger sized display indicating a larger number of results; and respond to the system user pointing a screen cursor to a displayed figure by displaying the results delivered by the search program for whichever of the queries is represented by the figure to which the cursor points. | 1. Apparatus comprising: a computer system having a processor and memory; computer instructions stored in said memory accessibly to said processor and effective when executing on said processor to: respond to entry of a core search query into a search program by a computer system user by displaying to the user a plurality of geometric figures including a core figure representing a number of results delivered by the search program for the core search query and a secondary figure representing a number of results delivered for a suggested related query; display the displayed figures in varying relative sizes determined by the number of results delivered by the search program for the core search query and the number of results delivered by the search program for the suggested query, with a larger sized display indicating a larger number of results; and respond to the system user pointing a screen cursor to a displayed figure by displaying the results delivered by the search program for whichever of the queries is represented by the figure to which the cursor points. 2. Apparatus according to claim 1 wherein the displayed geometric figures are circles. | 0.868902 |
9,971,893 | 1 | 3 | 1. A method, said method comprising: a first computer executing a plurality of text blocks of code derived from a script from a web page in response to a request for the web page from a client computer, said text blocks executed sequentially in a sequential order, wherein the script is a first text block of the plurality of text blocks, the execution of one text block of the plurality of text blocks by the first computer generating a new text block of code; and said first computer determining that the new text block includes malicious code and in response, said first computer preventing transmission of the web page to the client computer. | 1. A method, said method comprising: a first computer executing a plurality of text blocks of code derived from a script from a web page in response to a request for the web page from a client computer, said text blocks executed sequentially in a sequential order, wherein the script is a first text block of the plurality of text blocks, the execution of one text block of the plurality of text blocks by the first computer generating a new text block of code; and said first computer determining that the new text block includes malicious code and in response, said first computer preventing transmission of the web page to the client computer. 3. The method of claim 1 , said method comprising: before said determining that the new text block includes malicious code, said first computer executing the new text block and copying the new text block to an output file in a data storage area. | 0.782416 |
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