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9,384,282 | 1 | 2 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue of the plurality of fact check queues contains the segments to be fact checked in real-time, and a second fact check queue of the plurality of fact check queues contains the segments to be fact checked in non-real-time; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and then searching the source information located on a slower access time hardware device; wherein utilizing pattern matching begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue of the plurality of fact check queues contains the segments to be fact checked in real-time, and a second fact check queue of the plurality of fact check queues contains the segments to be fact checked in non-real-time; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and then searching the source information located on a slower access time hardware device; wherein utilizing pattern matching begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device. 2. The method of claim 1 wherein most popular, most recent and most common information is stored in the fastest access time hardware device, and less popular, less recent and less common information is stored in the slower access hardware devices. | 0.891093 |
9,449,079 | 14 | 17 | 14. A method of providing to a client application running on at least one digital electronic device in communication with a search engine a plurality of user-selectable refinements to a first search query including at least one first search term, the method comprising: (a) receiving by the search engine from the client application the first search query; (b) effecting by the search engine a first search in respect of the first search query yielding first search results; (c) determining dynamically first suggested search query refinements based at least in part on an analysis of groups of related search queries being related to the first search query, the analysis of groups including: determining the related search queries as being meaningful based on past user behaviours by filtering the related search queries to only those identified as having provided search results which provided a user with information sought by the user; grouping the meaningful related search queries into the groups based on past behaviors of users with search results that are provided in response to the meaningful related search queries, wherein the past behaviors of users include common Internet resources having been visited by the users after they were provided with the search results in response to the meaningful related search queries; and determining a first suggested search query refinement for each group based on a comparison of the first search query and the meaningful related search queries of a respective group, each of the first suggested search query refinements corresponding to a refined search query including the at least one first search term and at least one additional search term derived from one of the meaningful related search queries, the one of the meaningful related search queries having been determined as being the most popular in its respective group, the at least one additional search term having being determined as being the most unique as compared with previously identified suggested search query refinements; (d) sending by the search engine to the client application the first search results, the first suggested search query refinements, and instructions for displaying (1) at least one first search result and (2) apart from a search bar, the first suggested search query refinements, the first suggested search query refinements being selectable by a user via at least one first graphical object; (e) effecting by the search engine a first refined search in respect of a first refined search query including the at least one first search term and at least one first additional search term, the first refined search yielding first refined search results; And (f) sending by the search engine to the client application the first refined search results and instructions for displaying at least one first refined search result and a visual representation of a refinement relationship between the first search query and the first refined search query. | 14. A method of providing to a client application running on at least one digital electronic device in communication with a search engine a plurality of user-selectable refinements to a first search query including at least one first search term, the method comprising: (a) receiving by the search engine from the client application the first search query; (b) effecting by the search engine a first search in respect of the first search query yielding first search results; (c) determining dynamically first suggested search query refinements based at least in part on an analysis of groups of related search queries being related to the first search query, the analysis of groups including: determining the related search queries as being meaningful based on past user behaviours by filtering the related search queries to only those identified as having provided search results which provided a user with information sought by the user; grouping the meaningful related search queries into the groups based on past behaviors of users with search results that are provided in response to the meaningful related search queries, wherein the past behaviors of users include common Internet resources having been visited by the users after they were provided with the search results in response to the meaningful related search queries; and determining a first suggested search query refinement for each group based on a comparison of the first search query and the meaningful related search queries of a respective group, each of the first suggested search query refinements corresponding to a refined search query including the at least one first search term and at least one additional search term derived from one of the meaningful related search queries, the one of the meaningful related search queries having been determined as being the most popular in its respective group, the at least one additional search term having being determined as being the most unique as compared with previously identified suggested search query refinements; (d) sending by the search engine to the client application the first search results, the first suggested search query refinements, and instructions for displaying (1) at least one first search result and (2) apart from a search bar, the first suggested search query refinements, the first suggested search query refinements being selectable by a user via at least one first graphical object; (e) effecting by the search engine a first refined search in respect of a first refined search query including the at least one first search term and at least one first additional search term, the first refined search yielding first refined search results; And (f) sending by the search engine to the client application the first refined search results and instructions for displaying at least one first refined search result and a visual representation of a refinement relationship between the first search query and the first refined search query. 17. The method of claim 14 , further comprising: (g) effecting by the search engine a second refined search in respect of a second refined search query including the at least one first search term and at least one second additional search term, the second refined search query yielding second refined search results; and (h) sending by the search engine to the client application the second refined search results and instructions for displaying at least one second refined search result and a visual representation of a refinement relationship between the first search query and the second refined search query. | 0.768707 |
9,216,041 | 27 | 31 | 27. A medical implant assembly comprising: a) first and second bone anchors cooperating with a longitudinal connecting member having a tensioned cord, each of the first and second bone anchors having a receiver with a first pair of opposed upstanding arms having inner surfaces and an insert, each insert being positioned within a respective receiver and having a channel formed by a second pair of upstanding arms; a) a sleeve for attachment to the first bone anchor and having a first end and a second end, the sleeve having a body positionable between the inner surfaces of the first pair of opposed upstanding arms of a respective bone anchor receiver, an elongate solid rod portion on and extending from the second end of the sleeve, and a longitudinal bore extending partially through the body for receiving the tensioned cord therein, the sleeve including first and second body portions, the first body portion sized and shaped for being closely received within the channel of a respective insert and the second body portion being sized and shaped to be received between the first pair of opposed upstanding arms of a respective bone anchor receiver, the second body portion also engaging top surfaces of the second pair of upstanding arms of the respective insert. | 27. A medical implant assembly comprising: a) first and second bone anchors cooperating with a longitudinal connecting member having a tensioned cord, each of the first and second bone anchors having a receiver with a first pair of opposed upstanding arms having inner surfaces and an insert, each insert being positioned within a respective receiver and having a channel formed by a second pair of upstanding arms; a) a sleeve for attachment to the first bone anchor and having a first end and a second end, the sleeve having a body positionable between the inner surfaces of the first pair of opposed upstanding arms of a respective bone anchor receiver, an elongate solid rod portion on and extending from the second end of the sleeve, and a longitudinal bore extending partially through the body for receiving the tensioned cord therein, the sleeve including first and second body portions, the first body portion sized and shaped for being closely received within the channel of a respective insert and the second body portion being sized and shaped to be received between the first pair of opposed upstanding arms of a respective bone anchor receiver, the second body portion also engaging top surfaces of the second pair of upstanding arms of the respective insert. 31. The medical implant assembly of claim 27 , wherein a first smooth aperture being formed in the sleeve substantially transverse to the longitudinal through bore, the sleeve body maintaining first smooth aperture in alignment with top surfaces of the first pair of opposed upstanding arms of the respective receiver. | 0.5 |
8,650,141 | 5 | 6 | 5. The server according to claim 1 , wherein said databases and modules further comprise a personal emotional code database, said personal emotional code database configured for storing a plurality of the personal emotional codes for a plurality of users; each said personal emotional code corresponding to the emotional code assigned to the cluster to which said user belongs. | 5. The server according to claim 1 , wherein said databases and modules further comprise a personal emotional code database, said personal emotional code database configured for storing a plurality of the personal emotional codes for a plurality of users; each said personal emotional code corresponding to the emotional code assigned to the cluster to which said user belongs. 6. The server according to claim 5 wherein the personal emotional code of a specific user is stored in a non-volatile storage device under said specific user's possession, and said non-volatile storage device is a credit card, a debit card, a smart card, an identity card, a Subscriber Identification Module (SIM) card, or a Universal Subscriber Identification Module (USIM) card. | 0.723837 |
9,495,345 | 7 | 8 | 7. The method of claim 6 , wherein classifying the document according to the logical hierarchy further comprises: determining that the document is to be classified into the second node based at least in part on the at least one rule; and based on said determination, analyzing the document utilizing the at least one rule to determine if the document is to be classified into one or more child nodes of the second node, the one or more child nodes including the first node. | 7. The method of claim 6 , wherein classifying the document according to the logical hierarchy further comprises: determining that the document is to be classified into the second node based at least in part on the at least one rule; and based on said determination, analyzing the document utilizing the at least one rule to determine if the document is to be classified into one or more child nodes of the second node, the one or more child nodes including the first node. 8. The method of claim 7 , wherein determining that the document is to be classified into the second node based at least in part on the at least one rule further comprises: determining at least one region of text within the document that satisfies the first factor specified by the at least one rule; and temporarily storing the at least one region of text in a cache in response to the determination. | 0.5 |
7,519,201 | 1 | 3 | 1. A method for human detection and a pose classification comprising: using a computer to perform the steps of: receiving a probabilistic model derived from a set of training images in at least one of an unsupervised training stage or a semi-supervised training stage; generating a set of test image descriptors representing a test image; determining a likelihood that the test image contains a human based on parameters of the probabilistic model and the test image descriptors; and classifying a body pose of a detected human in the test image based on the test image descriptors and the parameters of the probabilistic model. | 1. A method for human detection and a pose classification comprising: using a computer to perform the steps of: receiving a probabilistic model derived from a set of training images in at least one of an unsupervised training stage or a semi-supervised training stage; generating a set of test image descriptors representing a test image; determining a likelihood that the test image contains a human based on parameters of the probabilistic model and the test image descriptors; and classifying a body pose of a detected human in the test image based on the test image descriptors and the parameters of the probabilistic model. 3. The method of claim 1 wherein the training stage comprises a semi-supervised training stage wherein at least one human pose in the set of training images is manually labeled and at least one human pose in the set of training images is unlabeled. | 0.5 |
8,380,743 | 6 | 9 | 6. A computer-implemented method for supporting targeted sharing and early curation of information, comprising: identifying a personal digital data item selected by a user within a personal information management client and data set that is unique to the user; recommending from a shared information repository separate from the personal information management client, shared documents similar to the digital data item from the personal information management client and dataset, comprising: selecting recommendation criteria; comparing the personal digital data item from the personal information management client and dataset with a set of shared documents from the shared information repository; applying the recommendation criteria to the comparison of the personal digital data item and the set of shared documents; and identifying one or more of the shared documents from the shared information repository that satisfy the recommendation criteria as the similar shared documents; displaying the similar shared documents visually proximate to the personal digital data item in the personal information client; receiving a selection of one of the similar shared documents; and incorporating the personal digital data item into the selected similar shared document in the shared information repository. | 6. A computer-implemented method for supporting targeted sharing and early curation of information, comprising: identifying a personal digital data item selected by a user within a personal information management client and data set that is unique to the user; recommending from a shared information repository separate from the personal information management client, shared documents similar to the digital data item from the personal information management client and dataset, comprising: selecting recommendation criteria; comparing the personal digital data item from the personal information management client and dataset with a set of shared documents from the shared information repository; applying the recommendation criteria to the comparison of the personal digital data item and the set of shared documents; and identifying one or more of the shared documents from the shared information repository that satisfy the recommendation criteria as the similar shared documents; displaying the similar shared documents visually proximate to the personal digital data item in the personal information client; receiving a selection of one of the similar shared documents; and incorporating the personal digital data item into the selected similar shared document in the shared information repository. 9. A computer-implemented method according to claim 6 , further comprising: identifying user selections of recommended documents; adjusting the recommendation criteria from the identified user selections; and applying the adjusted recommendation criteria to later recommendations of shared documents. | 0.628713 |
7,668,860 | 27 | 28 | 27. The computer readable storage medium of claim 26 further comprising executable instructions to use a path location to identify the location of the entity within the entity relationship model definition. | 27. The computer readable storage medium of claim 26 further comprising executable instructions to use a path location to identify the location of the entity within the entity relationship model definition. 28. The computer readable storage medium of claim 27 wherein the executable instructions to group data source entities into sets include executable instructions to group entities into groups based on the path location of the entity within the entity relationship model definition. | 0.5 |
8,600,743 | 1 | 8 | 1. A method comprising: at a computer system including one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: automatically without human intervention, determining whether a handheld electronic device is not in use; upon determining that the handheld electronic device is not in use, automatically without human intervention activating a microphone associated with the handheld electronic device; obtaining ambient sound using the microphone; determining a first context of use of the handheld electronic device; determining, at the handheld electronic device, a first noise profile based at least in part on the ambient sound, wherein the first noise profile is configured to enable the handheld electronic device to at least partially filter other ambient sound obtained at a later time when a voice-related feature of the handheld electronic device is in use; storing the first noise profile in association with the first context of use, wherein the first noise profile is one of a plurality of stored noise profiles each associated with a respective context of use; receiving an audio signal including voice and background sound; determining a second context of use of the handheld electronic device; determining whether the second context of use is substantially similar to the first context of use; upon determining that the second context of use is substantially similar to the first context of use, selecting the first noise profile; and using the first noise profile to at least partially filter the background sound from the audio signal to obtain the voice. | 1. A method comprising: at a computer system including one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: automatically without human intervention, determining whether a handheld electronic device is not in use; upon determining that the handheld electronic device is not in use, automatically without human intervention activating a microphone associated with the handheld electronic device; obtaining ambient sound using the microphone; determining a first context of use of the handheld electronic device; determining, at the handheld electronic device, a first noise profile based at least in part on the ambient sound, wherein the first noise profile is configured to enable the handheld electronic device to at least partially filter other ambient sound obtained at a later time when a voice-related feature of the handheld electronic device is in use; storing the first noise profile in association with the first context of use, wherein the first noise profile is one of a plurality of stored noise profiles each associated with a respective context of use; receiving an audio signal including voice and background sound; determining a second context of use of the handheld electronic device; determining whether the second context of use is substantially similar to the first context of use; upon determining that the second context of use is substantially similar to the first context of use, selecting the first noise profile; and using the first noise profile to at least partially filter the background sound from the audio signal to obtain the voice. 8. The method of claim 1 , wherein the first and the second context of use are defined by at least a location of the handheld electronic device and a time. | 0.869529 |
8,326,622 | 1 | 5 | 1. A computer system, comprising a processor and a computer readable medium storing program code configured to be executed by the processor to implement a method for filling out a form from a dialog, said method comprising: said processor providing a dialog having elements relevant for filing out said form; said processor providing a list of named entities; said processor separating said elements from said dialog using said list of named entities; said processor displaying the separated elements and said form on a computer display screen; and said processor transferring the separated elements to fill said form on said computer screen display. | 1. A computer system, comprising a processor and a computer readable medium storing program code configured to be executed by the processor to implement a method for filling out a form from a dialog, said method comprising: said processor providing a dialog having elements relevant for filing out said form; said processor providing a list of named entities; said processor separating said elements from said dialog using said list of named entities; said processor displaying the separated elements and said form on a computer display screen; and said processor transferring the separated elements to fill said form on said computer screen display. 5. The computer system of claim 1 , wherein said transferring is implemented using a command control. | 0.816364 |
8,676,768 | 13 | 17 | 13. A system comprising: a memory to store instructions; and a processor to execute the instructions in the memory to: receive at least one of: a rating for a model, or a comment for the model, the model being created by a user, the model including information relating to a computation, associate, in the memory, the at least one of the rating or the comment with information associated with the model, receive a request for the model, the request being received after associating the at least one of the rating or the comment with the information associated with the model, and provide, based on receiving the request, a document that includes the information associated with the model and information that is based on the at least one of the rating or the comment, the information associated with the model including: information identifying a quantity of comments received for the model, information identifying a date or a range of dates when the model was received by the processor, and information identifying a quantity of downloads of the model. | 13. A system comprising: a memory to store instructions; and a processor to execute the instructions in the memory to: receive at least one of: a rating for a model, or a comment for the model, the model being created by a user, the model including information relating to a computation, associate, in the memory, the at least one of the rating or the comment with information associated with the model, receive a request for the model, the request being received after associating the at least one of the rating or the comment with the information associated with the model, and provide, based on receiving the request, a document that includes the information associated with the model and information that is based on the at least one of the rating or the comment, the information associated with the model including: information identifying a quantity of comments received for the model, information identifying a date or a range of dates when the model was received by the processor, and information identifying a quantity of downloads of the model. 17. The system of claim 13 , where, when receiving the at least one of the rating or the comment, the processor is to receive the rating, and where the processor is further to: receive another rating for the model, determine a rating, for the model, that is based on the rating and the other rating, where the information that is based on the at least one of the rating or the comment includes the determined rating. | 0.695015 |
9,575,950 | 1 | 6 | 1. A method comprising: receiving, by a computing device, a spreadsheet model; receiving, by the computing device, a model template wherein the model template further comprises instructions for spreadsheet evaluation, template management, and web representation; and template management instructions on how to manage evaluations; and deploying, by the computing device, an instance of the model template into a model relationship structure relating one or more model template instances wherein the deploying of an instance of the model template occurs in a model relationship structure selected from a tree, a directed acyclic graph (DAG), and a matrix; wherein the template management instructions includes instructions on how evaluations using the model template interrelate with evaluations from the one or more other model template instances. | 1. A method comprising: receiving, by a computing device, a spreadsheet model; receiving, by the computing device, a model template wherein the model template further comprises instructions for spreadsheet evaluation, template management, and web representation; and template management instructions on how to manage evaluations; and deploying, by the computing device, an instance of the model template into a model relationship structure relating one or more model template instances wherein the deploying of an instance of the model template occurs in a model relationship structure selected from a tree, a directed acyclic graph (DAG), and a matrix; wherein the template management instructions includes instructions on how evaluations using the model template interrelate with evaluations from the one or more other model template instances. 6. The method of claim 1 , further comprising separating, by the computing device, inputs and outputs of the model template. | 0.783972 |
9,588,637 | 16 | 20 | 16. One or more non-transitory computer-readable media having instructions stored thereon that when executed by a computing device cause the computing device to: receive, 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 render, within a user interface associated with the computing device and with a graphical appearance based on at least one user interface component of the user interface associated with the computing device, a user interface component corresponding to the user interface component of the application executing within the virtual machine hosted by the remote host. | 16. One or more non-transitory computer-readable media having instructions stored thereon that when executed by a computing device cause the computing device to: receive, 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 render, within a user interface associated with the computing device and with a graphical appearance based on at least one user interface component of the user interface associated with the computing device, a user interface component corresponding to the user interface component of the application executing within the virtual machine hosted by the remote host. 20. The one or more non-transitory computer-readable media of claim 16 , wherein the instructions, when executed by the computing device, cause the computing device to at least one of: render the user interface component corresponding to the user interface component in a taskbar of the user interface associated with the computing device, render the user interface component corresponding to the user interface component in a dock of the user interface associated with the computing device, or render the user interface component corresponding to the user interface component on a desktop of the user interface associated with the computing device. | 0.505335 |
7,567,922 | 1 | 6 | 1. A method for generating a normalized configuration model, the method comprising: utilizing at least portions of a normalized model generation system to perform: generating product configuration instances from one or more product configuration models that include non-normalized feature references; identifying non-normalized feature references included in one or more of the product configuration instances; accessing a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locating normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replacing non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generating a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references. | 1. A method for generating a normalized configuration model, the method comprising: utilizing at least portions of a normalized model generation system to perform: generating product configuration instances from one or more product configuration models that include non-normalized feature references; identifying non-normalized feature references included in one or more of the product configuration instances; accessing a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locating normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replacing non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generating a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references. 6. The method of claim 1 further comprising: optimizing the normalized configuration model for run-time data retrieval. | 0.65407 |
8,195,659 | 1 | 14 | 1. A system for accessing mixed media reality document data structures, the system comprising: a mixed media processor for receiving, from a device, an image patch of a commercially printed document that includes a hotspot designation location, the image patch comprising at least a portion of an entire page of the commercially printed document that includes the hotspot designation location, for extracting features from the image patch including generating a histogram to discriminate between text and non-text, for determining a mixed media reality document data structure that corresponds to the image patch based on extracted features and the histogram, for capturing an x-y location of a hotspot in response to receiving a print command by identifying a begin mark designating a beginning point of the hotspot designation location and an end mark designating an ending point of the hotspot designation location, the begin mark and the end mark being represented by a visually imperceptible font, for instructing the device to highlight the hotspot based on the determining of the mixed media reality document data structure and for retrieving the mixed media reality document data structure, the mixed media reality document data structure comprising: a representation of the portion of the commercially printed document corresponding to the image patch; a supplemental media associated with the image patch; and the hotspot that is sent for display along with the representation, the hotspot comprising a pointer to the supplemental media, such that the supplemental media is sent in response to receipt of an indication that a user selected the hotspot. | 1. A system for accessing mixed media reality document data structures, the system comprising: a mixed media processor for receiving, from a device, an image patch of a commercially printed document that includes a hotspot designation location, the image patch comprising at least a portion of an entire page of the commercially printed document that includes the hotspot designation location, for extracting features from the image patch including generating a histogram to discriminate between text and non-text, for determining a mixed media reality document data structure that corresponds to the image patch based on extracted features and the histogram, for capturing an x-y location of a hotspot in response to receiving a print command by identifying a begin mark designating a beginning point of the hotspot designation location and an end mark designating an ending point of the hotspot designation location, the begin mark and the end mark being represented by a visually imperceptible font, for instructing the device to highlight the hotspot based on the determining of the mixed media reality document data structure and for retrieving the mixed media reality document data structure, the mixed media reality document data structure comprising: a representation of the portion of the commercially printed document corresponding to the image patch; a supplemental media associated with the image patch; and the hotspot that is sent for display along with the representation, the hotspot comprising a pointer to the supplemental media, such that the supplemental media is sent in response to receipt of an indication that a user selected the hotspot. 14. The system of claim 1 , wherein the mixed media reality document data structure further comprises an associated action. | 0.870253 |
6,073,127 | 11 | 13 | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a goal based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve presentation information indicative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and that provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that her motivates accomplishment of the goal. | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a goal based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve presentation information indicative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and that provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that her motivates accomplishment of the goal. 13. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component to provide a goal based educational environment as recited in claim 11, wherein the information includes electronic mail information. | 0.52057 |
8,429,740 | 1 | 3 | 1. A search result presentation system, the search result presentation system comprising: one or more processors; system memory; a database comprising tagged data, said tagged data tagged from one or more documents, for each of said one or more documents, said tagged data identifying items in said document for which said document may be searched and also identifying portions of said document that are eligible for alteration, based on classification of said identified portions, when presented to a user that does not have access to the entire document contents; an information retrieval system that: receives a search request from a user, said search request comprising search terms; and searches for said search terms in said database to identify a plurality of search results, said search results comprising references to the one or more documents; and a presentation engine for presenting the plurality of search results that: identifies a search result from within said plurality of search results, said search result for a document from among the one or more documents, said search result referencing a first tagged portion and a second tagged portion of said document; determines that said user has access privileges to at least a portion of said document based on an access policy; determines that said user does not have access to said first tagged portion of said document based on classification of the first tagged portion and based on the access policy; alters said search result so that said tagged first portion is not presented as part of said search result; and transmits said altered search result, including said second tagged portion of the document for presentation to said user. | 1. A search result presentation system, the search result presentation system comprising: one or more processors; system memory; a database comprising tagged data, said tagged data tagged from one or more documents, for each of said one or more documents, said tagged data identifying items in said document for which said document may be searched and also identifying portions of said document that are eligible for alteration, based on classification of said identified portions, when presented to a user that does not have access to the entire document contents; an information retrieval system that: receives a search request from a user, said search request comprising search terms; and searches for said search terms in said database to identify a plurality of search results, said search results comprising references to the one or more documents; and a presentation engine for presenting the plurality of search results that: identifies a search result from within said plurality of search results, said search result for a document from among the one or more documents, said search result referencing a first tagged portion and a second tagged portion of said document; determines that said user has access privileges to at least a portion of said document based on an access policy; determines that said user does not have access to said first tagged portion of said document based on classification of the first tagged portion and based on the access policy; alters said search result so that said tagged first portion is not presented as part of said search result; and transmits said altered search result, including said second tagged portion of the document for presentation to said user. 3. The system of claim 1 , wherein altering said search result so that said first tagged portion is not presented comprises redacting said first tagged portion from the search result. | 0.87551 |
8,255,427 | 1 | 15 | 1. A computer-readable medium having computer-executable instructions, when executed by a computer configured to: receive an input schema, the input schema specifying how to represent one or more elements in a document; receive one or more instance documents; generate one or more rules from the one or more instance documents; analyze the input schema for conformance to the one or more rules; and if the input schema does not conform to the one or more rules, generate a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the document in conformance with the one or more rules. | 1. A computer-readable medium having computer-executable instructions, when executed by a computer configured to: receive an input schema, the input schema specifying how to represent one or more elements in a document; receive one or more instance documents; generate one or more rules from the one or more instance documents; analyze the input schema for conformance to the one or more rules; and if the input schema does not conform to the one or more rules, generate a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the document in conformance with the one or more rules. 15. The computer-readable medium of claim 1 , wherein the modified schema is a Simple Network Management Protocol (SNMP) Management Information Base (MIB) schema. | 0.781081 |
9,672,812 | 15 | 19 | 15. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: producing output audio based, at least in part, on an output signal; analyzing an input audio signal to detect an occurrence of a trigger expression in the input audio signal; analyzing the output signal to detect an occurrence of the trigger expression in the output signal; and determining to disqualify the occurrence of the trigger expression in the input audio signal based, at least in part, on the occurrence of the trigger expression in the output signal. | 15. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: producing output audio based, at least in part, on an output signal; analyzing an input audio signal to detect an occurrence of a trigger expression in the input audio signal; analyzing the output signal to detect an occurrence of the trigger expression in the output signal; and determining to disqualify the occurrence of the trigger expression in the input audio signal based, at least in part, on the occurrence of the trigger expression in the output signal. 19. The one or more computer-readable media of claim 15 , wherein the output signal represents content comprising one or more of the following: music; radio; live, recorded, or machine-generated speech; person-to-person communications; command responses; or text. | 0.570261 |
7,548,651 | 5 | 6 | 5. The data process unit according to any of claims 1 to 3 , wherein the pattern models are generated using HMMs (Hidden Markov Models). | 5. The data process unit according to any of claims 1 to 3 , wherein the pattern models are generated using HMMs (Hidden Markov Models). 6. The data process unit according to claim 5 , wherein the mathematical distance calculating means calculates the mathematical distance using one of Euclidean distance determined based on a mean vector of normal distributions of the pattern models generated using the HMMs, Euclidean distance determined based on a mean vector of normal distributions of the pattern models normalized by the standard deviation of the normal distributions of the pattern models, and Bhattacharrya distance determined based on normal distributions of the pattern models. | 0.5 |
8,325,999 | 19 | 20 | 19. A hardware computer-readable storage media having instructions stored thereon that when executed by the hardware processor cause the hardware processor to perform the method of claim 15 . | 19. A hardware computer-readable storage media having instructions stored thereon that when executed by the hardware processor cause the hardware processor to perform the method of claim 15 . 20. A system comprising the hardware computer-readable storage media of claim 19 and the hardware processor. | 0.5 |
8,661,074 | 11 | 18 | 11. A service node for a communication network providing a service in the communication network, the service node, in operation, connected to one or more context sources, in which the service node is arranged for: receiving a request; evaluating the request, wherein the request comprises an expression, the expression being a function of a plurality of elements, each element relating to data originating from one or more context sources available in the communication network, each of the one or more context sources having an associated context source weight for a query by the service; determining one context source from the one or more context sources for which evaluation of the expression has a lowest expression evaluation weight, based on the associated context source weights for querying by the service, interrogating first the one context source determined to have the lowest expression evaluation weight; and wherein the expression comprising one or more intermediate expressions, the node is further arranged for iteratively determining a weight of evaluating the one or more intermediate expressions, until all elements relate only to data originating from the one or more context sources, wherein a lowest weight intermediate expression towards each of the context sources is determined for the expression until the expression elements comprise only context sources, at which point the context source to be interrogated first has been determined. | 11. A service node for a communication network providing a service in the communication network, the service node, in operation, connected to one or more context sources, in which the service node is arranged for: receiving a request; evaluating the request, wherein the request comprises an expression, the expression being a function of a plurality of elements, each element relating to data originating from one or more context sources available in the communication network, each of the one or more context sources having an associated context source weight for a query by the service; determining one context source from the one or more context sources for which evaluation of the expression has a lowest expression evaluation weight, based on the associated context source weights for querying by the service, interrogating first the one context source determined to have the lowest expression evaluation weight; and wherein the expression comprising one or more intermediate expressions, the node is further arranged for iteratively determining a weight of evaluating the one or more intermediate expressions, until all elements relate only to data originating from the one or more context sources, wherein a lowest weight intermediate expression towards each of the context sources is determined for the expression until the expression elements comprise only context sources, at which point the context source to be interrogated first has been determined. 18. The node according to claim 11 , in which the data of each one of the plurality of context sources is stored in an associated proxy server accessible for the service. | 0.595238 |
8,862,252 | 20 | 29 | 20. An electronic device for providing an audio menu to a user, comprising: a single sensing element for detecting user inputs; an audio output; and a processor operative to: direct the audio output to play back a first audio clip in a first manner; during the playback of the first audio clip in the first manner, receive from the single sensing element a first user input that is detected by the single sensing element; in response to the receiving the first user input, direct the audio output to alter the playback from the first manner to a second manner; during the playback of the first audio clip in the second manner, direct the audio output to play back a second audio clip to announce the first audio clip; and after the playback of the second audio clip, direct the audio output to play back a first menu audio clip that is associated with the audio menu. | 20. An electronic device for providing an audio menu to a user, comprising: a single sensing element for detecting user inputs; an audio output; and a processor operative to: direct the audio output to play back a first audio clip in a first manner; during the playback of the first audio clip in the first manner, receive from the single sensing element a first user input that is detected by the single sensing element; in response to the receiving the first user input, direct the audio output to alter the playback from the first manner to a second manner; during the playback of the first audio clip in the second manner, direct the audio output to play back a second audio clip to announce the first audio clip; and after the playback of the second audio clip, direct the audio output to play back a first menu audio clip that is associated with the audio menu. 29. The electronic device of claim 20 , wherein the audio output is operative to play back the first audio clip in the second manner by playing back the first audio clip at a first volume level, and wherein the audio output is operative to play back the second audio clip by playing back the second audio clip at a second volume level that is higher than the first volume level. | 0.529851 |
9,143,638 | 1 | 2 | 1. A method comprising: capturing, using a mobile phone, information from a rendered document; obtaining, using the mobile phone, a location-stamp indicating a location of the mobile phone at which the information captured from the rendered document was captured; storing, in a memory of the mobile phone, the information captured from the rendered document and the location-stamp; transmitting, from the mobile phone to a search engine, a search query to identify a source document of the rendered document in a set of source documents, wherein the search query includes the information captured from the rendered document and the location-stamp; and receiving, by the mobile device and from the search engine, an electronic version of the source document based on the search engine identifying the source document from a subset of source documents of the set of source documents by the information captured from the rendered document and the location-stamp, wherein the subset of source documents is determined by the location-stamp. | 1. A method comprising: capturing, using a mobile phone, information from a rendered document; obtaining, using the mobile phone, a location-stamp indicating a location of the mobile phone at which the information captured from the rendered document was captured; storing, in a memory of the mobile phone, the information captured from the rendered document and the location-stamp; transmitting, from the mobile phone to a search engine, a search query to identify a source document of the rendered document in a set of source documents, wherein the search query includes the information captured from the rendered document and the location-stamp; and receiving, by the mobile device and from the search engine, an electronic version of the source document based on the search engine identifying the source document from a subset of source documents of the set of source documents by the information captured from the rendered document and the location-stamp, wherein the subset of source documents is determined by the location-stamp. 2. The method of claim 1 , further comprising: the mobile phone constructing the search query, wherein the search query further includes an identifier of the mobile phone. | 0.800234 |
9,128,988 | 1 | 2 | 1. A method for searching, the method comprising: receiving, by a computer system, a query; identifying, by the computer system, a plurality of documents relevant to the query; identifying, by the computer system, a plurality of departments associated with the plurality of documents; selecting, by the computer system, one or more selected departments from the plurality of departments according to confidence scores associated with the plurality of departments; adding, by the computer system, one or more additional departments to the one or more selected departments if the confidence scores of the one or more selected departments do not meet a threshold condition; and transmitting, by the computer system, a representation of the plurality of documents in accordance with the one or more selected departments; wherein adding, by the computer system, the one or more additional departments to the one or more selected departments if the confidence scores of the one or more selected departments do not meet a threshold condition further comprises: receiving a plurality of queries from a plurality of users; grouping the plurality of queries into a plurality of query clusters according to a textual similarity of the plurality of queries to one another based on the textual similarity, a similarity of search, and a co-occurrence within a same browsing session; for each cluster of the plurality of query clusters, identifying an associated department having search results for the plurality of queries of the each cluster belonging thereto with a highest click-through rate as compared to other departments having search results for the plurality of queries of the each cluster; identifying a selected query cluster of the plurality of query clusters corresponding to the query based on the textual similarity of the plurality of queries of the each cluster to the query; and adding the associated department of the selected query cluster to the one or more selected departments. | 1. A method for searching, the method comprising: receiving, by a computer system, a query; identifying, by the computer system, a plurality of documents relevant to the query; identifying, by the computer system, a plurality of departments associated with the plurality of documents; selecting, by the computer system, one or more selected departments from the plurality of departments according to confidence scores associated with the plurality of departments; adding, by the computer system, one or more additional departments to the one or more selected departments if the confidence scores of the one or more selected departments do not meet a threshold condition; and transmitting, by the computer system, a representation of the plurality of documents in accordance with the one or more selected departments; wherein adding, by the computer system, the one or more additional departments to the one or more selected departments if the confidence scores of the one or more selected departments do not meet a threshold condition further comprises: receiving a plurality of queries from a plurality of users; grouping the plurality of queries into a plurality of query clusters according to a textual similarity of the plurality of queries to one another based on the textual similarity, a similarity of search, and a co-occurrence within a same browsing session; for each cluster of the plurality of query clusters, identifying an associated department having search results for the plurality of queries of the each cluster belonging thereto with a highest click-through rate as compared to other departments having search results for the plurality of queries of the each cluster; identifying a selected query cluster of the plurality of query clusters corresponding to the query based on the textual similarity of the plurality of queries of the each cluster to the query; and adding the associated department of the selected query cluster to the one or more selected departments. 2. The method of claim 1 , further comprising, if a number of the one or more selected departments does not exceed a minimum value, adding one or more high-document-count departments to the one or more selected departments, the high-document-count departments having a high number of documents corresponding thereto among the plurality of documents relative to other departments of the plurality of departments. | 0.622243 |
7,536,293 | 2 | 3 | 2. The method of claim 1 , wherein receiving the specialized database comprises receiving the specialized database having translation information that pertains to a particular destination, wherein the translation information includes a translation dictionary customized to represent the particular destination, and wherein the translation dictionary includes words associated with at least one of a hotel, street name, restaurant, and tourist attraction associated with the particular destination. | 2. The method of claim 1 , wherein receiving the specialized database comprises receiving the specialized database having translation information that pertains to a particular destination, wherein the translation information includes a translation dictionary customized to represent the particular destination, and wherein the translation dictionary includes words associated with at least one of a hotel, street name, restaurant, and tourist attraction associated with the particular destination. 3. The method of claim 2 , wherein receiving the specialized database comprises receiving the specialized database having translation information that pertains to a particular city. | 0.5 |
7,580,993 | 21 | 22 | 21. A computer program product, stored on a machine-readable medium, the computer program product comprising instructions operable to cause data processing apparatus to: upload data in a document, wherein the document is adapted to be distributed at scheduled intervals; generate a hashcode for the data; distribute the document; at the next scheduled interval, update the document by uploading the document with updated data; generate a hashcode for the updated data; compare the hashcode for the data with the hashcode for the updated data; and determine whether to distribute the updated document based on the comparison. | 21. A computer program product, stored on a machine-readable medium, the computer program product comprising instructions operable to cause data processing apparatus to: upload data in a document, wherein the document is adapted to be distributed at scheduled intervals; generate a hashcode for the data; distribute the document; at the next scheduled interval, update the document by uploading the document with updated data; generate a hashcode for the updated data; compare the hashcode for the data with the hashcode for the updated data; and determine whether to distribute the updated document based on the comparison. 22. The product in accordance with claim 21 , further comprising instructions to distribute the updated document to one or more receivers if the hashcode for the data and the hashcode for the updated data are different. | 0.517621 |
8,204,739 | 1 | 13 | 1. A method for updating the vocabulary of a speech translation system for translating a first language into a second language, the method comprising: receiving, by at least one microphone of the speech translation system, an utterance from a user of the speech translation system, wherein the speech translation system is for translating the utterance from the first language into the second language and outputting an audible translation of the utterance in the second language from at least one speaker of the speech translation system; after receiving the utterance, receiving, from a user of the speech translation system, via a user interface of the speech translation system, an indication to add a new word in the first language to a first recognition lexicon of the first language of an automatic speech recognition module of the speech translation system, wherein the automatic speech recognition module for the speech translation system comprises the first recognition lexicon, an acoustic model for the first language, and a language model for the first language, and wherein the new word is not contained in the first recognition lexicon, the acoustic module, and the language model of the first language; determining, by the speech translation system, word class information, a pronunciation in the first language, and a translation in the second language for the new word; adding, by the speech translation system, the new word, along with the word class information and the pronunciation in the first language determined by the speech translation system, to the first recognition lexicon of the first language of the speech translation system; adding, by the speech translation system, the new word, along with the word class information and the translation in the second language determined by the speech translation system, to a first machine translation module associated with the first language of the speech translation system, wherein the first machine translation module contains a first tagging module, a first translation model and a first language module, and is configured to translate the new word to a corresponding translated word in the second language. | 1. A method for updating the vocabulary of a speech translation system for translating a first language into a second language, the method comprising: receiving, by at least one microphone of the speech translation system, an utterance from a user of the speech translation system, wherein the speech translation system is for translating the utterance from the first language into the second language and outputting an audible translation of the utterance in the second language from at least one speaker of the speech translation system; after receiving the utterance, receiving, from a user of the speech translation system, via a user interface of the speech translation system, an indication to add a new word in the first language to a first recognition lexicon of the first language of an automatic speech recognition module of the speech translation system, wherein the automatic speech recognition module for the speech translation system comprises the first recognition lexicon, an acoustic model for the first language, and a language model for the first language, and wherein the new word is not contained in the first recognition lexicon, the acoustic module, and the language model of the first language; determining, by the speech translation system, word class information, a pronunciation in the first language, and a translation in the second language for the new word; adding, by the speech translation system, the new word, along with the word class information and the pronunciation in the first language determined by the speech translation system, to the first recognition lexicon of the first language of the speech translation system; adding, by the speech translation system, the new word, along with the word class information and the translation in the second language determined by the speech translation system, to a first machine translation module associated with the first language of the speech translation system, wherein the first machine translation module contains a first tagging module, a first translation model and a first language module, and is configured to translate the new word to a corresponding translated word in the second language. 13. The method of claim 1 , wherein associating the word class information includes accepting word class information provided by the user. | 0.919014 |
9,672,541 | 11 | 19 | 11. A system comprising: a display screen operable to present a user interface displaying a graphical representation of a website that includes a plurality of webpages, the representation including a plurality of graphical webpage snapshots that each depicts a respective webpage associated with the website, the representation further including a plurality of graphical indicators that illustrate links between the plurality of webpages, the representation further including a plurality of active tag indicators that are each associated with a respective one of the webpages, each active tag indicator being associated with a respective portion of computer programming code that is configured to collect data from visitors to the associated webpage and included in the respective webpage with which the active tag indicator is associated, wherein the representation further includes a plurality of webpage analytics indicators that are each associated with a respective one of the webpages and are each associated and selectable with at least one of the associated webpage's active tag indicators, each of the webpage analytics indicators, upon selection, describing one or more characteristics of web traffic associated with the respective webpage and it's at least one active tag indicator; a user input device operable to receive user input indicating an editing action to be performed with respect to a first one of the computer programming code portions associated with a first one of the active tag indicators and its associated webpage and that will present an advertisement when the associated webpage in which the first computer programming code portion is included is loaded in a web browser, the editing action adding the first computer programming code portion to or removing the first computer programming code portion from the webpage, wherein the webpage analytics indicator that is associated with the first active tag indicator is configured to describe one or more characteristics of web traffic associated with the first active tag indicator based on traffic results obtained after the website is updated to reflect the editing action; and a communications interface operable to transmit an update instruction message via a communications interface, the update instruction message including instructions for updating the website to reflect the editing action. | 11. A system comprising: a display screen operable to present a user interface displaying a graphical representation of a website that includes a plurality of webpages, the representation including a plurality of graphical webpage snapshots that each depicts a respective webpage associated with the website, the representation further including a plurality of graphical indicators that illustrate links between the plurality of webpages, the representation further including a plurality of active tag indicators that are each associated with a respective one of the webpages, each active tag indicator being associated with a respective portion of computer programming code that is configured to collect data from visitors to the associated webpage and included in the respective webpage with which the active tag indicator is associated, wherein the representation further includes a plurality of webpage analytics indicators that are each associated with a respective one of the webpages and are each associated and selectable with at least one of the associated webpage's active tag indicators, each of the webpage analytics indicators, upon selection, describing one or more characteristics of web traffic associated with the respective webpage and it's at least one active tag indicator; a user input device operable to receive user input indicating an editing action to be performed with respect to a first one of the computer programming code portions associated with a first one of the active tag indicators and its associated webpage and that will present an advertisement when the associated webpage in which the first computer programming code portion is included is loaded in a web browser, the editing action adding the first computer programming code portion to or removing the first computer programming code portion from the webpage, wherein the webpage analytics indicator that is associated with the first active tag indicator is configured to describe one or more characteristics of web traffic associated with the first active tag indicator based on traffic results obtained after the website is updated to reflect the editing action; and a communications interface operable to transmit an update instruction message via a communications interface, the update instruction message including instructions for updating the website to reflect the editing action. 19. The system recited in claim 11 , wherein each active tag indicator specifies a tag identifier, an event name that triggers execution of the associated computer programming code portion when the associated webpage is rendered, a variable or selector from which to collect data during execution of such associated computer programming code portion when the associated webpage is rendered, and a post-processing procedure, if any, for execution on the collected data. | 0.709677 |
8,612,483 | 3 | 6 | 3. The method claim 1 further comprising determining the recipient user for the request based on a relationship between the user and the recipient user. | 3. The method claim 1 further comprising determining the recipient user for the request based on a relationship between the user and the recipient user. 6. The method of claim 3 , wherein determining the recipient user for the request comprises receiving one or more identifiers of the recipient user from the user and a message from the user. | 0.510309 |
7,930,298 | 1 | 4 | 1. A system for generating a ‘snapshot’ of a learning object, comprising: an interface, receiving: a target object, corresponding to a category, comprising a plurality of sentences and multimedia data, wherein the sentences comprise at least one target object keyword; and a user identification number; a learning object database, comprising: a plurality of learning objects, wherein each of the learning objects corresponds to at least one category and comprises at least one learning object keyword; a user's historical learning record, comprising a track record of learning objects used corresponding to the user identification number; and a user keyword input by a user; a script preview unit, selecting at least one of the sentences of the target object as a preview sentence according to the user's historical learning record corresponding to the user identification number, the script preview unit performing steps of: calculating the amount of information contained in the plurality of sentences of the target object; which includes: calculating a relationship matrix of the plurality of sentences in the target object, wherein the relationship matrix comprises a relationship value for each pair of the plurality of sentences; and calculating a sum of the relationship values of each of the plurality of sentences and other sentences of the plurality of sentences as a value specifying the amount of information thereof; selecting at least one pertinent keyword relating to the target object from the plurality of learning objects according to the user's historical learning record corresponding to the user identification number; and selecting the sentence, among the plurality of sentences, that contains the largest amount of information and the user keyword or the pertinent keyword as the preview sentence; a multimedia preview unit, selecting one of the multimedia data of the target object as a preview multimedia data, wherein the selected multimedia data is highly related to the selected sentence; and a ‘snapshot’ generator, generating a ‘snapshot’ of the target object by combining the preview sentence and the preview multimedia data, and directing a display device to display the ‘snapshot’. | 1. A system for generating a ‘snapshot’ of a learning object, comprising: an interface, receiving: a target object, corresponding to a category, comprising a plurality of sentences and multimedia data, wherein the sentences comprise at least one target object keyword; and a user identification number; a learning object database, comprising: a plurality of learning objects, wherein each of the learning objects corresponds to at least one category and comprises at least one learning object keyword; a user's historical learning record, comprising a track record of learning objects used corresponding to the user identification number; and a user keyword input by a user; a script preview unit, selecting at least one of the sentences of the target object as a preview sentence according to the user's historical learning record corresponding to the user identification number, the script preview unit performing steps of: calculating the amount of information contained in the plurality of sentences of the target object; which includes: calculating a relationship matrix of the plurality of sentences in the target object, wherein the relationship matrix comprises a relationship value for each pair of the plurality of sentences; and calculating a sum of the relationship values of each of the plurality of sentences and other sentences of the plurality of sentences as a value specifying the amount of information thereof; selecting at least one pertinent keyword relating to the target object from the plurality of learning objects according to the user's historical learning record corresponding to the user identification number; and selecting the sentence, among the plurality of sentences, that contains the largest amount of information and the user keyword or the pertinent keyword as the preview sentence; a multimedia preview unit, selecting one of the multimedia data of the target object as a preview multimedia data, wherein the selected multimedia data is highly related to the selected sentence; and a ‘snapshot’ generator, generating a ‘snapshot’ of the target object by combining the preview sentence and the preview multimedia data, and directing a display device to display the ‘snapshot’. 4. The system for generating a ‘snapshot’ of a learning object of claim 1 , wherein the multimedia preview unit further performs steps of: calculating a multimedia distance matrix by calculating a distance between each multimedia data and each of the sentences within the target object; and calculating a multimedia relationship matrix by calculating a relationship between each of the multimedia data and each of the sentences within the target object to locate the multimedia data at the shortest distance from the preview sentence. | 0.686251 |
8,396,586 | 27 | 30 | 27. The method of claim 21 , wherein the documents comprise currency bills and substitute currency media. | 27. The method of claim 21 , wherein the documents comprise currency bills and substitute currency media. 30. The method of claim 27 , wherein the at least one criterion comprises a document being a document from the group comprising a document whose value was not determined, a suspect bill, and an invalid substitute currency media. | 0.5 |
7,610,315 | 23 | 24 | 23. The computer program product of claim 21 , the operations further comprising deriving a document control policy for a parent node in the document control policy ontology based on a combination of multiple document control policies associated with child nodes of the parent node in the document control policy ontology; and associating the derived document control policy with the parent node in the document control policy ontology. | 23. The computer program product of claim 21 , the operations further comprising deriving a document control policy for a parent node in the document control policy ontology based on a combination of multiple document control policies associated with child nodes of the parent node in the document control policy ontology; and associating the derived document control policy with the parent node in the document control policy ontology. 24. The computer program product of claim 23 , wherein the derived document control policy comprises a derived security policy and a derived retention policy, and deriving the document control policy comprises: combining Boolean values of security policies associated with the child nodes of the parent node to form the derived security policy; and combining identified separate cases, which depend on variables associated with the multiple document control policies associated with child nodes, to form the derived retention policy. | 0.5 |
8,732,037 | 7 | 9 | 7. The method of claim 4 , wherein: the generating of the summary records generates a map file that organizes the summary records into groups; and the presenting of at least the part of the full item record among the full item records is based on the map file that organizes the summary records into groups. | 7. The method of claim 4 , wherein: the generating of the summary records generates a map file that organizes the summary records into groups; and the presenting of at least the part of the full item record among the full item records is based on the map file that organizes the summary records into groups. 9. The method of claim 7 , wherein: the map file organizes a portion of the summary records into a group that corresponds to a currency used in the geographic region; and the presenting of at least the part of the full item record is based on the group that corresponds to the currency. | 0.548896 |
5,537,590 | 1 | 5 | 1. An apparatus for analyzing an array of data stored in a quantitative database, comprising: a memory for storing said data of said quantitative database as a table in a relational database; a computer coupled to said relational database and having a display and having an input device for receiving user input, said computer for execution of one or more programs so as to process data from said quantitative database; a first program in execution on said computer for controlling said computer to receive user input defining one or more analysis rules to be performed on a subset of data, also specified by said user input, from said array of data stored in said quantitative database and for controlling said computer so as to analyze selected ones of said user specified subset of data items in accordance with selected ones of said one or more user specified analysis rules so as to generate one or more diagnostic records the text of which is also defined by said user input, each diagnostic record corresponding to a possible result of the application of a particular user specified analysis rule to the corresponding user selected subset of items of data from said array of data in said quantitative database, and wherein said first computer program controls said computer so as to automatically generate one or more link pointers for each said diagnostic record, each said link pointer linking a diagnostic record to the corresponding user selected subset of items of data from said quantitative database from which said diagnostic record was generated; and a second program in execution on said computer for controlling said computer so as to store each said diagnostic record in a diagnostic database in said memory and wherein said link pointer associated with each diagnostic record is programmable by said user, and wherein said first program includes one or more routines for controlling said computer to display at least first and second windows on said display, and for controlling said computer to display in said first window at least some of said items of data from said quantitative database and for controlling said computer to display in said second window at least some of said diagnostic records, and further comprising one or more routines in said first computer program for controlling said computer to display a pointer in said second window and to receive and process user data controlling the position in said second window of said pointer such that any diagnostic record displayed in said second window may be selected by said user using said pointer, and when any said displayed diagnostic record in said second window is so selected, for controlling said computer to display in said first window the corresponding subset of data items from said quantitative database associated by one or more of said link pointers with the selected diagnostic record. | 1. An apparatus for analyzing an array of data stored in a quantitative database, comprising: a memory for storing said data of said quantitative database as a table in a relational database; a computer coupled to said relational database and having a display and having an input device for receiving user input, said computer for execution of one or more programs so as to process data from said quantitative database; a first program in execution on said computer for controlling said computer to receive user input defining one or more analysis rules to be performed on a subset of data, also specified by said user input, from said array of data stored in said quantitative database and for controlling said computer so as to analyze selected ones of said user specified subset of data items in accordance with selected ones of said one or more user specified analysis rules so as to generate one or more diagnostic records the text of which is also defined by said user input, each diagnostic record corresponding to a possible result of the application of a particular user specified analysis rule to the corresponding user selected subset of items of data from said array of data in said quantitative database, and wherein said first computer program controls said computer so as to automatically generate one or more link pointers for each said diagnostic record, each said link pointer linking a diagnostic record to the corresponding user selected subset of items of data from said quantitative database from which said diagnostic record was generated; and a second program in execution on said computer for controlling said computer so as to store each said diagnostic record in a diagnostic database in said memory and wherein said link pointer associated with each diagnostic record is programmable by said user, and wherein said first program includes one or more routines for controlling said computer to display at least first and second windows on said display, and for controlling said computer to display in said first window at least some of said items of data from said quantitative database and for controlling said computer to display in said second window at least some of said diagnostic records, and further comprising one or more routines in said first computer program for controlling said computer to display a pointer in said second window and to receive and process user data controlling the position in said second window of said pointer such that any diagnostic record displayed in said second window may be selected by said user using said pointer, and when any said displayed diagnostic record in said second window is so selected, for controlling said computer to display in said first window the corresponding subset of data items from said quantitative database associated by one or more of said link pointers with the selected diagnostic record. 5. The apparatus of claim 1 wherein said first program includes a routine for receiving and processing user input in the form of commands to program each said analysis rule as a conditional branching test wherein a user selected subset of items of data from said quantitative database is compared to one or more test criteria using mathematical or logical operators or both and for receiving and processing commands entered by the user to define at least two transfer control branches for a particular user selected analysis rule to control transfer of processing by said computer to at least two different points in said first program depending upon the result of said comparison performed by said analysis rule, and wherein, for each said branch, a different diagnostic statement is displayed and stored in said memory as a diagnostic record. | 0.669279 |
9,940,672 | 4 | 8 | 4. The computer implemented system according to claim 1 , wherein the language processor includes a sentiment-based repository of frequent lexical items. | 4. The computer implemented system according to claim 1 , wherein the language processor includes a sentiment-based repository of frequent lexical items. 8. The computer implemented system according to claim 4 , wherein the lexical items of the stock-based lexical repository are associated with polarity values and strength values and wherein the lexical items of the sentiment-based lexical repository are associated with polarity values and strength values. | 0.5 |
7,634,546 | 47 | 48 | 47. A method according to claim 46 wherein said current database hierarchy comprises: a top-level hierarchy having at least one top-level subject; at least one mid-level hierarchy, each of said at least one mid-level hierarchy having at least one mid-level subject related to at least one of said at least one top-level subject; and a low-level hierarchy having at least one low-level subject related to at least one of said at least one mid-level subject, wherein said response input becomes an item indexed to at least one of said at least one low-level subject. | 47. A method according to claim 46 wherein said current database hierarchy comprises: a top-level hierarchy having at least one top-level subject; at least one mid-level hierarchy, each of said at least one mid-level hierarchy having at least one mid-level subject related to at least one of said at least one top-level subject; and a low-level hierarchy having at least one low-level subject related to at least one of said at least one mid-level subject, wherein said response input becomes an item indexed to at least one of said at least one low-level subject. 48. A method according to claim 47 wherein said current database hierarchy further comprises: at least one top-level leader assigned to each of said at least one top-level subject; at least one mid-level leader assigned to each of said at least one mid-level subject; and at least one low-level leader assigned to each of said at least one low-level subject. | 0.697635 |
8,886,536 | 16 | 24 | 16. The method of claim 1 , further comprising: identifying, by the one or more physical processors, one or more requests associated with the second natural language utterance, wherein determining the promotional content comprises obtaining the promotional content based on a determination that the promotional content relates to the one or more requests. | 16. The method of claim 1 , further comprising: identifying, by the one or more physical processors, one or more requests associated with the second natural language utterance, wherein determining the promotional content comprises obtaining the promotional content based on a determination that the promotional content relates to the one or more requests. 24. The method of claim 16 , further comprising: determining, by the one or more physical processors, that at least one request of the one or more requests is incomplete or ambiguous; monitoring, by the one or more physical processors, interaction of the user with the promotional content; and interpreting, by the one or more physical processors, the at least one incomplete or ambiguous request based on the interaction. | 0.5 |
5,475,586 | 6 | 7 | 6. An electronic dictionary and retrieval apparatus comprising: means for inputting a sentence in a source language; means for storing a plurality of idiom forms each having a fixed portion and a variable portion, each idiom form representing a defined word phrase with common attributes wherein the variable portion is represented by one:or more variable symbols; and means for retrieving a selected one of said idiom forms stored in said storage means that coincides with an idiom in the inputted sentence. | 6. An electronic dictionary and retrieval apparatus comprising: means for inputting a sentence in a source language; means for storing a plurality of idiom forms each having a fixed portion and a variable portion, each idiom form representing a defined word phrase with common attributes wherein the variable portion is represented by one:or more variable symbols; and means for retrieving a selected one of said idiom forms stored in said storage means that coincides with an idiom in the inputted sentence. 7. An electronic dictionary and retrieval apparatus as recited in claim 6, wherein each variable symbol within each idiom form represents a defined group of words with common attributes. | 0.683673 |
9,031,243 | 1 | 8 | 1. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for multi-stage audio signal analysis, the method comprising: performing a first-stage processing operation on an audio signal, the first stage processing operation including a windowed signal analysis to calculate from the audio signal statistical descriptor features that are stored in a raw feature vector; performing a second stage statistical processing operation on the raw feature vector to derive a reduced feature vector; performing a third stage processing operation on the reduced feature vector to derive at least one sound object label that refers to the original audio signal; and mapping the at least one sound object label into a stream of control events sent to a sound-object-driven, multimedia-aware software application, wherein the sound-object-driven multimedia-aware software application is responsive to the stream of control events to configure processing for the audio signal, and wherein any of the processing operations of the first through third stages are configurable. | 1. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for multi-stage audio signal analysis, the method comprising: performing a first-stage processing operation on an audio signal, the first stage processing operation including a windowed signal analysis to calculate from the audio signal statistical descriptor features that are stored in a raw feature vector; performing a second stage statistical processing operation on the raw feature vector to derive a reduced feature vector; performing a third stage processing operation on the reduced feature vector to derive at least one sound object label that refers to the original audio signal; and mapping the at least one sound object label into a stream of control events sent to a sound-object-driven, multimedia-aware software application, wherein the sound-object-driven multimedia-aware software application is responsive to the stream of control events to configure processing for the audio signal, and wherein any of the processing operations of the first through third stages are configurable. 8. The non-transitory computer-readable storage medium of claim 1 , wherein any of the first through third stages are stored in a database and may be retrieved for use in a subsequent analytical operation. | 0.774725 |
9,978,367 | 1 | 2 | 1. A computer-implemented method, comprising: receiving, at a computing system, audio data that indicates a first voice input that was provided to a computing device; determining that the first voice input is part of a voice dialog that includes a plurality of pre-defined dialog states arranged to receive a series of voice inputs related to a particular task, wherein each dialog state is mapped to: (i) a set of display data characterizing content that is designated for display when voice inputs for the dialog state are received, and (ii) a set of n-grams; receiving, at the computing system, first display data that characterizes content that was displayed on a screen of the computing device when the first voice input was provided to the computing device; selecting, by the computing system, a particular dialog state of the plurality of pre-defined dialog states that corresponds to the first voice input, including determining a match between the first display data and the corresponding set of display data that is mapped to the particular dialog state; biasing a language model by adjusting probability scores that the language model indicates for n-grams in the corresponding set of n-grams that are mapped to the particular dialog state; and transcribing the voice input using the biased language model. | 1. A computer-implemented method, comprising: receiving, at a computing system, audio data that indicates a first voice input that was provided to a computing device; determining that the first voice input is part of a voice dialog that includes a plurality of pre-defined dialog states arranged to receive a series of voice inputs related to a particular task, wherein each dialog state is mapped to: (i) a set of display data characterizing content that is designated for display when voice inputs for the dialog state are received, and (ii) a set of n-grams; receiving, at the computing system, first display data that characterizes content that was displayed on a screen of the computing device when the first voice input was provided to the computing device; selecting, by the computing system, a particular dialog state of the plurality of pre-defined dialog states that corresponds to the first voice input, including determining a match between the first display data and the corresponding set of display data that is mapped to the particular dialog state; biasing a language model by adjusting probability scores that the language model indicates for n-grams in the corresponding set of n-grams that are mapped to the particular dialog state; and transcribing the voice input using the biased language model. 2. The computer-implemented method of claim 1 , further comprising: receiving a second voice input at the computing system; selecting a second particular dialog state, from among the plurality of pre-defined dialog states, that corresponds to the second voice input; and biasing the language model by adjusting probability scores that the language model indicates for n-grams in the corresponding set of n-grams that are mapped to the second particular dialog state, wherein the set of n-grams that are mapped to the second particular dialog state are different than the set of n-grams that are mapped to the particular dialog state that corresponds to the first voice input. | 0.599169 |
7,519,713 | 14 | 18 | 14. A computer program product for use at a computer system, the computer program product for implementing a method of initiating a channel runtime, the computer program product comprising one or more computer-readable storage media have stored thereon computer-executable instructions, that when executed by a processor, cause the computer system to perform the following: access an annotated object oriented representation of a service, the annotated object oriented representation being annotated with service description attributes that map objects included in the object oriented representation to corresponding service oriented elements in a service oriented representation of the service; identify a service description attribute that annotates an object of the annotated object oriented representation; map the object to a corresponding service oriented element in accordance with service description information contained in the identified service description attribute; output a channel object that is configured to implement the behaviors and data formats described in the service oriented representation; initiate a channel that is compatible with behaviors and data formats of the service using the outputted channel object such that the service offered is accessible through the channel; provide the service on the initiated channel, the service utilizing a first programming model for implementing distributed messaging functionality, such that interfaces, methods, parameters and values of the first programming model are compatible with the behaviors and data formats of the service; and provide a second, different service on the initiated channel, the second, different service utilizing a second, different programming model for implementing the distributed messaging functionality, such that interfaces, methods, parameters and values of the second programming model are compatible with the behaviors and data formats of the second service. | 14. A computer program product for use at a computer system, the computer program product for implementing a method of initiating a channel runtime, the computer program product comprising one or more computer-readable storage media have stored thereon computer-executable instructions, that when executed by a processor, cause the computer system to perform the following: access an annotated object oriented representation of a service, the annotated object oriented representation being annotated with service description attributes that map objects included in the object oriented representation to corresponding service oriented elements in a service oriented representation of the service; identify a service description attribute that annotates an object of the annotated object oriented representation; map the object to a corresponding service oriented element in accordance with service description information contained in the identified service description attribute; output a channel object that is configured to implement the behaviors and data formats described in the service oriented representation; initiate a channel that is compatible with behaviors and data formats of the service using the outputted channel object such that the service offered is accessible through the channel; provide the service on the initiated channel, the service utilizing a first programming model for implementing distributed messaging functionality, such that interfaces, methods, parameters and values of the first programming model are compatible with the behaviors and data formats of the service; and provide a second, different service on the initiated channel, the second, different service utilizing a second, different programming model for implementing the distributed messaging functionality, such that interfaces, methods, parameters and values of the second programming model are compatible with the behaviors and data formats of the second service. 18. The computer-program product as recited in claim 14 , wherein computer-executable instructions, that when executed, cause the computer system to initiate a channel that is compatible with behaviors and data formats of the service comprise computer- executable instructions that when executed cause the computer system to configure the channel to convert between common language runtime parameters and SOAP messages. | 0.591618 |
9,336,116 | 21 | 22 | 21. The computer-readable medium of claim 20 , further comprising: causing the system to execute the first recording of the base script to generate the first response file; causing the system to execute the second recording of the base script again to generate the second response file; and storing a dynamic value list that comprises the first dynamic value data and the second dynamic value data. | 21. The computer-readable medium of claim 20 , further comprising: causing the system to execute the first recording of the base script to generate the first response file; causing the system to execute the second recording of the base script again to generate the second response file; and storing a dynamic value list that comprises the first dynamic value data and the second dynamic value data. 22. The computer-readable medium of claim 21 , wherein the first recording is identical to the second recording and the first recording and the second recording are for testing a business flow on the system. | 0.544053 |
8,364,486 | 3 | 7 | 3. The mobile device of claim 1 wherein the controller determines whether the audible speech has a high recognition uncertainty. | 3. The mobile device of claim 1 wherein the controller determines whether the audible speech has a high recognition uncertainty. 7. The mobile device of claim 3 wherein the mobile device processes the phonemes based upon a determination that the audible speech does not have high recognition uncertainty, and sends the phonemes based upon the determination that the audible speech has high recognition uncertainty. | 0.5 |
8,341,195 | 8 | 9 | 8. The method of claim 7 , wherein each of the plurality of license prices within a value tier corresponds to a different usage restriction, selected from a category of usage restrictions, wherein a usage restriction is a condition that is included in a license to use the designated content asset. | 8. The method of claim 7 , wherein each of the plurality of license prices within a value tier corresponds to a different usage restriction, selected from a category of usage restrictions, wherein a usage restriction is a condition that is included in a license to use the designated content asset. 9. The method of claim 8 , wherein the category of usage restrictions is the resolution of the content asset to be provided to the user upon licensing the content asset. | 0.568878 |
7,580,946 | 1 | 12 | 1. A method for automatically generating data-service-execution flows, based on metadata objects, for executing data services from heterogeneous data sources, the method comprising the steps of: (a) providing a smart integration engine, having at least one smart integration server with a solution resolver residing therein, configured to receive dynamic service schema (DSS) requests, said DSS requests each having a DSS metadata input and a DSS metadata output, for executing the data services from the heterogeneous data sources, wherein said solution resolver has access to data assets stored in a metadata repository; and (b) generating solution flows of said DSS requests based on metadata criteria and on said data assets, each said solution flow utilizes a plurality of nodes that are inter-related such that a node output of a preceding node serves as a node input of a subsequent node for producing said DSS metadata output, a portion of said plurality of nodes to be executed subsequent to said step of generating said solution flows according to an optimized node sequence determined by said solution resolver solely during said step of generating said solution flows. | 1. A method for automatically generating data-service-execution flows, based on metadata objects, for executing data services from heterogeneous data sources, the method comprising the steps of: (a) providing a smart integration engine, having at least one smart integration server with a solution resolver residing therein, configured to receive dynamic service schema (DSS) requests, said DSS requests each having a DSS metadata input and a DSS metadata output, for executing the data services from the heterogeneous data sources, wherein said solution resolver has access to data assets stored in a metadata repository; and (b) generating solution flows of said DSS requests based on metadata criteria and on said data assets, each said solution flow utilizes a plurality of nodes that are inter-related such that a node output of a preceding node serves as a node input of a subsequent node for producing said DSS metadata output, a portion of said plurality of nodes to be executed subsequent to said step of generating said solution flows according to an optimized node sequence determined by said solution resolver solely during said step of generating said solution flows. 12. The method of claim 1 , the method further comprising the step of: (c) storing said DSS requests and user-defined requests and previously executed requests in a schema store for faster execution via alias calls and/or web services. | 0.702532 |
8,577,908 | 26 | 32 | 26. A tangible computer-readable storage medium containing a program which, when executed by a processor, performs an operation of preventing alterations of physical entities of data in a database when a query is executed against the database, the operation comprising: providing a logical representation of the data defining a multiplicity of logical fields, each logical field abstractly describing a manner of accessing and exposing, via a user interface, an associated physical entity of the data; wherein each of the multiplicity of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entity of the data; and wherein at least a portion of the multiplicity of logical fields include lock attributes referenced in order to lock the respective logical field; providing a lock object for each logical field of a plurality of logical fields forming a subset of the multiplicity of logical fields, the respective lock object being identified by the respective lock attributes of the respective logical field; receiving an abstract query from a requesting entity comprising at least one logical field of the multiplicity of logical fields; and upon determining that executing the abstract query against the database requires the lock on the at least one logical field: determining the lock object of the at least one logical field; locking the lock object for the requesting entity for locking the at least one logical field before executing the abstract query; and unlocking the lock object after executing the abstract query. | 26. A tangible computer-readable storage medium containing a program which, when executed by a processor, performs an operation of preventing alterations of physical entities of data in a database when a query is executed against the database, the operation comprising: providing a logical representation of the data defining a multiplicity of logical fields, each logical field abstractly describing a manner of accessing and exposing, via a user interface, an associated physical entity of the data; wherein each of the multiplicity of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entity of the data; and wherein at least a portion of the multiplicity of logical fields include lock attributes referenced in order to lock the respective logical field; providing a lock object for each logical field of a plurality of logical fields forming a subset of the multiplicity of logical fields, the respective lock object being identified by the respective lock attributes of the respective logical field; receiving an abstract query from a requesting entity comprising at least one logical field of the multiplicity of logical fields; and upon determining that executing the abstract query against the database requires the lock on the at least one logical field: determining the lock object of the at least one logical field; locking the lock object for the requesting entity for locking the at least one logical field before executing the abstract query; and unlocking the lock object after executing the abstract query. 32. The computer-readable storage medium of claim 26 , wherein the lock attributes of the at least one logical field comprises a synchronization indication of whether a lock on the logical field is required or not, and wherein locking the lock object for the requesting entity comprises: determining, from the synchronization indication, whether executing the abstract query against the database requires a lock on the at least one logical field; and only if executing the abstract query requires the lock on the at least one logical field, locking the lock object. | 0.668427 |
4,638,445 | 1 | 2 | 1. In a mobile robot of the type having (a) a vision system, (b) memory means for storing data derived from the robot vision system, and (c) a computer for processing data derived from the robot's vision system, the improvement wherein the robot's vision system comprises (i) a first array of ranging transducers for obtaining data on the position and distance of far objects in a volume of space, the transducers of the first array being symmetrically disposed on the mobile robot with respect to an axis of symmetry within the mobile robot, each transducer of the first array being fixed in position with respect to that axis of symmetry and seeing a portion of the volume of space seen by its entire array; (ii) a second array of ranging transducers for obtaining data of the position and distance of near objects in the same or an overlapping volume of space, the transducers of the second array being symmetrically disposed on the mobile robot with respect to said axis of symmetry, each transducer of the second array being fixed in position with respect to said axis of symmetry and seeing a portion of the volume of space seen by its entire array, the angle of view of the transducers of the second array being different from the angle of view of the transducers of the first array with respect to the same object in space; and (iii) means for polling said ranging transducers in sequences determined by the computer. | 1. In a mobile robot of the type having (a) a vision system, (b) memory means for storing data derived from the robot vision system, and (c) a computer for processing data derived from the robot's vision system, the improvement wherein the robot's vision system comprises (i) a first array of ranging transducers for obtaining data on the position and distance of far objects in a volume of space, the transducers of the first array being symmetrically disposed on the mobile robot with respect to an axis of symmetry within the mobile robot, each transducer of the first array being fixed in position with respect to that axis of symmetry and seeing a portion of the volume of space seen by its entire array; (ii) a second array of ranging transducers for obtaining data of the position and distance of near objects in the same or an overlapping volume of space, the transducers of the second array being symmetrically disposed on the mobile robot with respect to said axis of symmetry, each transducer of the second array being fixed in position with respect to said axis of symmetry and seeing a portion of the volume of space seen by its entire array, the angle of view of the transducers of the second array being different from the angle of view of the transducers of the first array with respect to the same object in space; and (iii) means for polling said ranging transducers in sequences determined by the computer. 2. The improvement according to claim 1, further comprising (iv) at least one additional ranging transducer on the mobile robot for obtaining data relative to said axis of symmetry on the position and distance of objects outside the field of view of the first and second transducer arrays. | 0.5 |
9,544,381 | 8 | 11 | 8. The computer program product of claim 7 , wherein the first behavioral pattern is one of a first plurality of behavioral patterns, and wherein the second behavioral pattern is one of a second plurality of behavioral patterns. | 8. The computer program product of claim 7 , wherein the first behavioral pattern is one of a first plurality of behavioral patterns, and wherein the second behavioral pattern is one of a second plurality of behavioral patterns. 11. The computer program product of claim 8 , wherein the prior user information data comprises user information data on a plurality of websites, and the first plurality of behavioral patterns are identified based on the user information data on the plurality of websites. | 0.790123 |
8,856,946 | 16 | 20 | 16. The computer program product of claim 9 , further comprising program code that is readable and executable by said one or more hardware processors to: determine an age of each of the multiple parsed security-enabled synthetic context-based objects that have been pulled into the particular security-enabled context-based data gravity well; and remove from the particular security-enabled context-based data gravity well any parsed security-enabled synthetic context-based object that is older than a predetermined age. | 16. The computer program product of claim 9 , further comprising program code that is readable and executable by said one or more hardware processors to: determine an age of each of the multiple parsed security-enabled synthetic context-based objects that have been pulled into the particular security-enabled context-based data gravity well; and remove from the particular security-enabled context-based data gravity well any parsed security-enabled synthetic context-based object that is older than a predetermined age. 20. The computer system of claim 16 , further comprising: tenth program instructions to determine a likelihood that a particular security-enabled synthetic context-based object is pulled into an appropriate security-enabled context-based data gravity well according to a Bayesian probability formula of: P ( A ❘ B ) = P ( B ❘ A ) P ( A ) P ( B ) where: P(A|B) is the probability that a security-enabled synthetic context object will be an appropriate populator of a particular security-enabled context-based data gravity well (A) given that (|) a predefined amount of confirmed context objects are applied to the non-contextual data object in a security-enabled synthetic context-based object (B); P(B|A) is the probability that the predefined amount of confirmed context-based objects are applied to the non-contextual data object in the security-enabled synthetic context-based object (B) given that (|) the security-enabled synthetic context-based object is assigned to the particular security-enabled context-based data gravity well (A); P(A) is the probability that the particular security-enabled synthetic context-based object will be the appropriate populator of the particular security-enabled context-based data gravity well regardless of any other information; and P(B) is the probability that the particular security-enabled synthetic context-based object will have the predefined amount of confirmed context objects regardless of any other information; and wherein the tenth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 0.5 |
9,679,027 | 15 | 20 | 15. One or more non-transitory storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: generating a question graph that includes a respective node for each of a plurality of questions; connecting, with links in the question graph, nodes for questions that are equivalent, comprising: identifying selected resources for each of the plurality of questions based on user selections of search results in response to previous submissions of the question as a search query to a search engine; identifying pairs of questions from the plurality of questions, wherein the questions in each identified pair of questions have at least a first threshold number of common identified selected resources; and for each identified pair, connecting the nodes for the questions in the identified pair with a link in the question graph; receiving a new search query from a user device; obtaining an initial ranking of questions that are related to the new search query; generating a modified ranking of questions that are related to the new search query, comprising, for each question in the initial ranking: determining whether the question is equivalent to any higher-ranked questions in the initial ranking by determining whether a node for the question is connected by a link to any of the nodes for any of the higher-ranked questions in the question graph; and when the question is equivalent to any of the higher-ranked questions, removing the question from the modified ranking; selecting one or more questions from the modified ranking; and transmitting data identifying the selected questions to the user device as part of a response to the new search query. | 15. One or more non-transitory storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: generating a question graph that includes a respective node for each of a plurality of questions; connecting, with links in the question graph, nodes for questions that are equivalent, comprising: identifying selected resources for each of the plurality of questions based on user selections of search results in response to previous submissions of the question as a search query to a search engine; identifying pairs of questions from the plurality of questions, wherein the questions in each identified pair of questions have at least a first threshold number of common identified selected resources; and for each identified pair, connecting the nodes for the questions in the identified pair with a link in the question graph; receiving a new search query from a user device; obtaining an initial ranking of questions that are related to the new search query; generating a modified ranking of questions that are related to the new search query, comprising, for each question in the initial ranking: determining whether the question is equivalent to any higher-ranked questions in the initial ranking by determining whether a node for the question is connected by a link to any of the nodes for any of the higher-ranked questions in the question graph; and when the question is equivalent to any of the higher-ranked questions, removing the question from the modified ranking; selecting one or more questions from the modified ranking; and transmitting data identifying the selected questions to the user device as part of a response to the new search query. 20. The storage media of claim 15 , the operations further comprising: obtaining search results for each question of the plurality of questions by submitting the question as a search query to the search engine; identifying pairs of questions for which at least a third threshold number of search results among a predetermined number of highest-ranked search results for one question in the pair identify resources that are among resources identified by the predetermined number of highest-ranked search results for the other question in the pair; and for each identified pair, connecting the nodes for the questions in the pair with a link in the question graph. | 0.5 |
7,930,166 | 11 | 12 | 11. A translation supporting method for supporting a process of a computer translating an original sentence, the translation supporting method comprising: setting a first character string contained in the original sentence in a first language as a first original sentence partial expression; setting, as a first original sentence dummy head in the first language, a second character string that is in the first language, that is shorter than the first original sentence partial expression, and that semantically or syntactically represents the first original sentence partial expression; generating a first original skeleton sentence by replacing the first original sentence partial expression in the original sentence with the first original sentence dummy head; obtaining a first translated skeleton sentence which is a translation of the first original skeleton sentence translated from the first language into a second language; obtaining a first translated partial expression which is a translation of the first original sentence partial expression translated from the first language into the second language; generating a translation in the second language of the original sentence by replacing a first translation dummy head which is a translation in the second language of the first original sentence dummy head and which is contained in the first translated skeleton sentence with the first translated partial expression; outputting the generated translation in the second language of the original sentence to a translated sentence storage unit; and controlling an output device to enable the original sentence partial expression to be output to a first window different from a second window in which the original sentence is displayed. | 11. A translation supporting method for supporting a process of a computer translating an original sentence, the translation supporting method comprising: setting a first character string contained in the original sentence in a first language as a first original sentence partial expression; setting, as a first original sentence dummy head in the first language, a second character string that is in the first language, that is shorter than the first original sentence partial expression, and that semantically or syntactically represents the first original sentence partial expression; generating a first original skeleton sentence by replacing the first original sentence partial expression in the original sentence with the first original sentence dummy head; obtaining a first translated skeleton sentence which is a translation of the first original skeleton sentence translated from the first language into a second language; obtaining a first translated partial expression which is a translation of the first original sentence partial expression translated from the first language into the second language; generating a translation in the second language of the original sentence by replacing a first translation dummy head which is a translation in the second language of the first original sentence dummy head and which is contained in the first translated skeleton sentence with the first translated partial expression; outputting the generated translation in the second language of the original sentence to a translated sentence storage unit; and controlling an output device to enable the original sentence partial expression to be output to a first window different from a second window in which the original sentence is displayed. 12. The translation supporting method according to claim 11 , further comprising setting a third character string contained in the first original sentence partial expression as a second original sentence partial expression; setting, as a second original sentence dummy head, a fourth character string that is in the first language, that is shorter than the second original sentence partial expression, and that semantically or syntactically represents the second original sentence partial expression; generating a second original skeleton sentence by replacing the second original sentence partial expression in the first original sentence partial expression with the second original sentence dummy head; obtaining a second translated skeleton sentence which is a translation of the second original skeleton sentence, translated from the first language into the second language; and obtaining a second translated partial expression which is a translation of the second original sentence partial expression translated from the first language into the second language, wherein the first translated partial expression is generated by replacing a second translated sentence dummy head which is a translation in the second language of the second original sentence dummy head and which is contained in the second translated skeleton sentence with the second translated partial expression. | 0.5 |
9,230,356 | 7 | 20 | 7. A non-transitory computer-readable medium including one or more sequences of instructions which, when executed by one or more processors, causes: presenting a document in a graphical user interface of a document editing application on a display of a first device to a first user; receiving, at the first device, information describing a first modification to the document at the first device by the first user; in response to receiving information describing the first modification to the document at the first device by the first user, changing the presentation of the document on the first device to reflect the first modification to the document at the first device by the first user without presenting an animation associated with the first modification made to the document at the first device by the first user; receiving, at the first device, information describing a second modification to the document at a second device by a second user; in response to receiving information describing the second modification to the document at the second device by the second user, changing the presentation of the document on the first device to reflect the second modification to the document at the second device by the second user and presenting an animation associated with the second modification to the document receiving a message at the first device; identifying one or more keywords in text of the message, the one or more keywords associated with at least one of an attribute of the document and a feature or function of the document editing application; and presenting, on the first device, the message, wherein a portion of the text of the message associated with the identified one or more keywords is displayed as a selectable link, wherein the message is presented in a chat window displayed automatically when a new message is received or displayed in response to receiving input at an affordance. | 7. A non-transitory computer-readable medium including one or more sequences of instructions which, when executed by one or more processors, causes: presenting a document in a graphical user interface of a document editing application on a display of a first device to a first user; receiving, at the first device, information describing a first modification to the document at the first device by the first user; in response to receiving information describing the first modification to the document at the first device by the first user, changing the presentation of the document on the first device to reflect the first modification to the document at the first device by the first user without presenting an animation associated with the first modification made to the document at the first device by the first user; receiving, at the first device, information describing a second modification to the document at a second device by a second user; in response to receiving information describing the second modification to the document at the second device by the second user, changing the presentation of the document on the first device to reflect the second modification to the document at the second device by the second user and presenting an animation associated with the second modification to the document receiving a message at the first device; identifying one or more keywords in text of the message, the one or more keywords associated with at least one of an attribute of the document and a feature or function of the document editing application; and presenting, on the first device, the message, wherein a portion of the text of the message associated with the identified one or more keywords is displayed as a selectable link, wherein the message is presented in a chat window displayed automatically when a new message is received or displayed in response to receiving input at an affordance. 20. The non-transitory computer-readable medium of claim 7 , wherein the attribute of the document includes at least one of a page number, a paragraph, a chapter, and a section of the document. | 0.659011 |
10,049,105 | 5 | 8 | 5. A word alignment score computing apparatus for computing a score of word alignment of a bilingual sentence pair of first and second languages, comprising a processor configured to: responsive to said bilingual sentence pair and a word alignment for the bilingual sentence pair, successively select words of a sentence in said first language of said bilingual sentence pair in a prescribed order; and compute, for every word of the sentence in said first language of said bilingual sentence pair, a score representing a probability of the selected word and a word in said second language aligned with said word by said word alignment forming a correct word pair, and based on this score, for computing a score of said word alignment; wherein: in computing a score of a certain word pair, said processor computes the score of the certain word pair based on all alignments of selected words preceding that word in said first language which forms the certain word pair; compute a score representing a probability of a word pair consisting of the selected word and a word in a sentence in said second language of said bilingual sentence pair aligned with said word by said word alignment being a correct word pair; compute, based on scores of all words of the sentence in said first language of said bilingual sentence pair, the score of said word alignment; utilize a recurrent neural network having a first input receiving the selected word and a second input receiving a word in said second language aligned with said word by said word alignment, and apply the selected word and the word aligned with the word by said word alignment to said first and second inputs, respectively; wherein said recurrent neural network includes: an input layer having said first and second inputs, and computing and outputting word embedding vectors from words respectively applied to said first and second inputs, a hidden layer connected to receive outputs of said input layer, for generating, by a predetermined non-linear operation, a vector representing a relation between two outputs from said input layer, and an output layer computing and outputting said score based on the output of said hidden layer; and wherein the output of said hidden layer is applied as an input to said hidden layer when a next word pair is given to said word alignment score computing apparatus. | 5. A word alignment score computing apparatus for computing a score of word alignment of a bilingual sentence pair of first and second languages, comprising a processor configured to: responsive to said bilingual sentence pair and a word alignment for the bilingual sentence pair, successively select words of a sentence in said first language of said bilingual sentence pair in a prescribed order; and compute, for every word of the sentence in said first language of said bilingual sentence pair, a score representing a probability of the selected word and a word in said second language aligned with said word by said word alignment forming a correct word pair, and based on this score, for computing a score of said word alignment; wherein: in computing a score of a certain word pair, said processor computes the score of the certain word pair based on all alignments of selected words preceding that word in said first language which forms the certain word pair; compute a score representing a probability of a word pair consisting of the selected word and a word in a sentence in said second language of said bilingual sentence pair aligned with said word by said word alignment being a correct word pair; compute, based on scores of all words of the sentence in said first language of said bilingual sentence pair, the score of said word alignment; utilize a recurrent neural network having a first input receiving the selected word and a second input receiving a word in said second language aligned with said word by said word alignment, and apply the selected word and the word aligned with the word by said word alignment to said first and second inputs, respectively; wherein said recurrent neural network includes: an input layer having said first and second inputs, and computing and outputting word embedding vectors from words respectively applied to said first and second inputs, a hidden layer connected to receive outputs of said input layer, for generating, by a predetermined non-linear operation, a vector representing a relation between two outputs from said input layer, and an output layer computing and outputting said score based on the output of said hidden layer; and wherein the output of said hidden layer is applied as an input to said hidden layer when a next word pair is given to said word alignment score computing apparatus. 8. The word alignment apparatus according to claim 5 , wherein the processor is further configured: generate a plurality of word alignment candidates for said bilingual sentence pair; compute, for each of said plurality of generated word alignment candidates, a word alignment score for said bilingual sentence pair using said word alignment score computing apparatus; and determine and output as the word alignment for said bilingual sentence pair, that one of the computed word alignment candidates for said plurality of word alignment candidates which corresponds to a highest score. | 0.5 |
7,646,868 | 19 | 27 | 19. A steganographic cryptography system to encrypt a clear text message into an obscured, encrypted message using a key phrase comprising: a key processing module to partition the key phrase into separate words, and to determine an index value for each word of the key phrase; a message processing module to partition the clear text message into separate words, and to determine an index value for each word of the clear text message; a concatenator, coupled to the key processing module and the message processing module, to concatenate the index values of the key phrase words to form a key string, and to concatenate the index values of the clear text message words to form a message string; and a steganography module coupled to the concatenator, a word matrix, and a template file, to partition the key string into sections of a first predetermined length, to partition the message string into sections of a second predetermined length, for each key section and message section pair to concatenate the key section to the message section to form a cipher text section, and to add the cipher text section to a cipher text string, and for each section of the cipher text string to locate a row of the word matrix indexed by the cipher text section, to randomly select a template from the template file, the template including a plurality of tags, to obtain one or more words from the word matrix row according to columns selected by the tags, and to replace the cipher text section with the obtained words according to the randomly selected template to form the obscured, encrypted message. | 19. A steganographic cryptography system to encrypt a clear text message into an obscured, encrypted message using a key phrase comprising: a key processing module to partition the key phrase into separate words, and to determine an index value for each word of the key phrase; a message processing module to partition the clear text message into separate words, and to determine an index value for each word of the clear text message; a concatenator, coupled to the key processing module and the message processing module, to concatenate the index values of the key phrase words to form a key string, and to concatenate the index values of the clear text message words to form a message string; and a steganography module coupled to the concatenator, a word matrix, and a template file, to partition the key string into sections of a first predetermined length, to partition the message string into sections of a second predetermined length, for each key section and message section pair to concatenate the key section to the message section to form a cipher text section, and to add the cipher text section to a cipher text string, and for each section of the cipher text string to locate a row of the word matrix indexed by the cipher text section, to randomly select a template from the template file, the template including a plurality of tags, to obtain one or more words from the word matrix row according to columns selected by the tags, and to replace the cipher text section with the obtained words according to the randomly selected template to form the obscured, encrypted message. 27. The system of claim 19 , wherein the steganorgraphy module reuses key sections during concatenation of key sections to message sections when the size the message is greater than the size of the key phrase. | 0.504739 |
6,167,117 | 21 | 22 | 21. The method of claim 20, further comprising the step of: at a predetermined time, modifying the model of the user's calling behavior in accordance with the training set. | 21. The method of claim 20, further comprising the step of: at a predetermined time, modifying the model of the user's calling behavior in accordance with the training set. 22. The method of claim 21, wherein the model of the user's calling behavior includes weights determined from previous calls by the user to at least one of the telephone numbers, and wherein the modifying step includes the substep of: altering the weights of the user's calling beavior model to reflect the information related to the previous call. | 0.5 |
8,386,478 | 11 | 12 | 11. A system for improving the relevancy of electronic search results over a plurality of searches comprising: an adaptive search engine communicatively coupled to a plurality of data items from one or more data sources stored in at least one database, said data sources searchable using a first search query entered by a user wherein said first search query comprises at least one keyword, said adaptive search engine configured to generate a ranked search result listing, the ranked search result listing comprising one or more file identifiers, wherein each of the one or more file identifiers corresponds to one of the plurality of data items; a processor; and a user interface configured to: display to the user the ranked search result listing of file identifiers in a first display area, receive, from the user, a selection of one of the file identifiers, wherein the data item corresponding to the selected file identifier is ranked with a first ranking in the search result listing, facilitate opening the data item that corresponds to the selected file identifier, display a content of the data item to the user, receive, from the user, a selection of at least a portion of the content of the data item for adding to a note panel associated with said first search query as a note, wherein the selection is received via copying and pasting or dragging and dropping the portion of the content into the note panel by the user, wherein the portion of the content is determined by the user to be relevant to said first search query; increase, via the processor, a relevancy ranking of the data item with respect to the at least one keyword as the note is added to the note panel, and wherein the increased relevancy ranking causes the data item to be ranked with a second ranking higher than the first ranking in a future search result listing generated using the same at least one keyword; store the portion of the content in the note panel associated with said first search query such that the note panel is accessible at a future time by at least one of the user and a second user; and provide the at least one of the user and the second user with the portion of the content when responding to a second search query similar to said first search query by locating and accessing the note panel associated with said first search query. | 11. A system for improving the relevancy of electronic search results over a plurality of searches comprising: an adaptive search engine communicatively coupled to a plurality of data items from one or more data sources stored in at least one database, said data sources searchable using a first search query entered by a user wherein said first search query comprises at least one keyword, said adaptive search engine configured to generate a ranked search result listing, the ranked search result listing comprising one or more file identifiers, wherein each of the one or more file identifiers corresponds to one of the plurality of data items; a processor; and a user interface configured to: display to the user the ranked search result listing of file identifiers in a first display area, receive, from the user, a selection of one of the file identifiers, wherein the data item corresponding to the selected file identifier is ranked with a first ranking in the search result listing, facilitate opening the data item that corresponds to the selected file identifier, display a content of the data item to the user, receive, from the user, a selection of at least a portion of the content of the data item for adding to a note panel associated with said first search query as a note, wherein the selection is received via copying and pasting or dragging and dropping the portion of the content into the note panel by the user, wherein the portion of the content is determined by the user to be relevant to said first search query; increase, via the processor, a relevancy ranking of the data item with respect to the at least one keyword as the note is added to the note panel, and wherein the increased relevancy ranking causes the data item to be ranked with a second ranking higher than the first ranking in a future search result listing generated using the same at least one keyword; store the portion of the content in the note panel associated with said first search query such that the note panel is accessible at a future time by at least one of the user and a second user; and provide the at least one of the user and the second user with the portion of the content when responding to a second search query similar to said first search query by locating and accessing the note panel associated with said first search query. 12. A system in accordance with claim 11 wherein when a note generated in said note panel is selected and copied to a data repository a relevance of the note with respect to the at least one keyword is increased. | 0.5 |
9,971,746 | 1 | 9 | 1. A computer-implemented method, comprising: accessing a first resource belonging to a particular domain; selecting an anchor in the first resource linking to a second resource belonging to the particular domain to which the first resource belongs; identifying particular text content in the first resource that is subordinate to and proximate to the anchor; determining, by one or more computers, whether the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain; in response to determining that the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain, generating a domain template for the particular domain to which the first resource and the second resource belong and that specifies, a location of the particular text content in the second resource; determining one or more resources belonging to the particular domain that have a structure matching the domain template; determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content that is subordinate to the anchor for the respective resource; determining that a particular one of the respective resources is responsive to a search query; and in response to determining that the particular one of the respective resources is responsive to a search query, providing the respective text content that is subordinate to the anchor for the respective resource in response to the search query in a form of a snippet for the particular one of the respective resources in a search results page. | 1. A computer-implemented method, comprising: accessing a first resource belonging to a particular domain; selecting an anchor in the first resource linking to a second resource belonging to the particular domain to which the first resource belongs; identifying particular text content in the first resource that is subordinate to and proximate to the anchor; determining, by one or more computers, whether the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain; in response to determining that the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain, generating a domain template for the particular domain to which the first resource and the second resource belong and that specifies, a location of the particular text content in the second resource; determining one or more resources belonging to the particular domain that have a structure matching the domain template; determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content that is subordinate to the anchor for the respective resource; determining that a particular one of the respective resources is responsive to a search query; and in response to determining that the particular one of the respective resources is responsive to a search query, providing the respective text content that is subordinate to the anchor for the respective resource in response to the search query in a form of a snippet for the particular one of the respective resources in a search results page. 9. The method of claim 1 , wherein the particular text content includes anchor-text of the anchor. | 0.945251 |
9,110,971 | 5 | 6 | 5. The computer-based system of claim 1 , wherein the set of patent features includes IPC-overlap, representing the number of the overlapping IPC codes between the IPC codes of a patent in the first set of candidate patent documents and the IPC codes of an initial high-ranking set of patent documents in the first set of candidate patent documents, the re-ranking module further adapted to compute IPC-overlap including code adapted to define an overlap score between two IPC codes, divide each IPC code to a plurality of levels based on IPC code structure, and wherein a first level overlap between two IPC codes results in a first score and a second level overlap between two IPC codes results in a second score. | 5. The computer-based system of claim 1 , wherein the set of patent features includes IPC-overlap, representing the number of the overlapping IPC codes between the IPC codes of a patent in the first set of candidate patent documents and the IPC codes of an initial high-ranking set of patent documents in the first set of candidate patent documents, the re-ranking module further adapted to compute IPC-overlap including code adapted to define an overlap score between two IPC codes, divide each IPC code to a plurality of levels based on IPC code structure, and wherein a first level overlap between two IPC codes results in a first score and a second level overlap between two IPC codes results in a second score. 6. The computer-based system of claim 5 , wherein the IPC-overlap of a given patent document is an average of the IPC-overlap scores between the IPC codes of that patent document and all the IPC codes of the initial high-ranking set of patent documents. | 0.5 |
10,162,812 | 11 | 12 | 11. A method comprising: at a computing platform comprising at least one processor, memory, and a communication interface: receiving, by the at least one processor, via the communication interface, and from a first user device, mobile application feedback information comprising text feedback associated with feedback of a mobile application; identifying, by the at least one processor, based on the text feedback, one or more nouns associated with the text feedback; identifying, by the at least one processor and based on a comparison between the one or more nouns with a plurality of mobile application topics associated with the mobile application, one or more text feedback topics; generating, by the at least one processor and based on the one or more text feedback topics, one or more commands directing a sentiment analysis server to determine one or more sentiments for the one or more text feedback topics, wherein the generating the one or more commands directing the sentiment analysis server to determine the text feedback topics comprises: determining, by the at least one processor and based on performing sentiment analysis on a part of the text feedback associated with the one or more text feedback topics, the one or more sentiments for the one or more text feedback topics, wherein determining the one or more sentiments comprises: receiving, by the at least one processor, a sentiment analysis model comprising past recorded user feedback data, and determining, by the at least one processor and based on a comparison between the sentiment analysis model and the part of the text feedback associated with the one or more text feedback topics, the one or more sentiments and one or more score probabilities associated with the one or more sentiments, and transmitting the one or more sentiments for the one or more text feedback topics; transmitting, by the at least one processor, via the communication interface, and to the sentiment analysis server, the one or more commands directing the sentiment analysis server to determine the one or more sentiments; receiving, by the at least one processor, via the communication interface, and from the sentiment analysis server, the one or more sentiments; and transmitting, by the at least one processor, via the communication interface, and to a summarization server, the one or more text feedback topics and the one or more sentiments. | 11. A method comprising: at a computing platform comprising at least one processor, memory, and a communication interface: receiving, by the at least one processor, via the communication interface, and from a first user device, mobile application feedback information comprising text feedback associated with feedback of a mobile application; identifying, by the at least one processor, based on the text feedback, one or more nouns associated with the text feedback; identifying, by the at least one processor and based on a comparison between the one or more nouns with a plurality of mobile application topics associated with the mobile application, one or more text feedback topics; generating, by the at least one processor and based on the one or more text feedback topics, one or more commands directing a sentiment analysis server to determine one or more sentiments for the one or more text feedback topics, wherein the generating the one or more commands directing the sentiment analysis server to determine the text feedback topics comprises: determining, by the at least one processor and based on performing sentiment analysis on a part of the text feedback associated with the one or more text feedback topics, the one or more sentiments for the one or more text feedback topics, wherein determining the one or more sentiments comprises: receiving, by the at least one processor, a sentiment analysis model comprising past recorded user feedback data, and determining, by the at least one processor and based on a comparison between the sentiment analysis model and the part of the text feedback associated with the one or more text feedback topics, the one or more sentiments and one or more score probabilities associated with the one or more sentiments, and transmitting the one or more sentiments for the one or more text feedback topics; transmitting, by the at least one processor, via the communication interface, and to the sentiment analysis server, the one or more commands directing the sentiment analysis server to determine the one or more sentiments; receiving, by the at least one processor, via the communication interface, and from the sentiment analysis server, the one or more sentiments; and transmitting, by the at least one processor, via the communication interface, and to a summarization server, the one or more text feedback topics and the one or more sentiments. 12. The method of claim 11 , further comprising: modifying, by the at least one processor and using a lemmatization analysis technique, the text feedback to generate cleansed text feedback; and wherein the one or more nouns associated with the text feedback is identified based on the cleansed text feedback. | 0.660793 |
8,023,298 | 8 | 9 | 8. The CAM device of claim 1 , further comprising: a search key encoder circuit having an input to receive a search key and configured to generate an encoded search key. | 8. The CAM device of claim 1 , further comprising: a search key encoder circuit having an input to receive a search key and configured to generate an encoded search key. 9. The CAM device of claim 8 , wherein the encoded search key comprises a balanced data word that has an equal number of logic high bits and logic low bits. | 0.617647 |
8,423,471 | 1 | 6 | 1. A method for computer security, comprising: displaying, by a programmable computing device executing instructions, an electronic document; detecting, by the computing device, a request to traverse a link, wherein the link is associated with an element of the document; evaluating, by the computing device, an attribute, wherein the attribute is associated with the element of the document and wherein evaluating the attribute includes determining whether a destination associated with the link was enumerated; and determining, by the computing device, whether to traverse the link based on the evaluation. | 1. A method for computer security, comprising: displaying, by a programmable computing device executing instructions, an electronic document; detecting, by the computing device, a request to traverse a link, wherein the link is associated with an element of the document; evaluating, by the computing device, an attribute, wherein the attribute is associated with the element of the document and wherein evaluating the attribute includes determining whether a destination associated with the link was enumerated; and determining, by the computing device, whether to traverse the link based on the evaluation. 6. The method of claim 1 , wherein the link is associated with submitting a form. | 0.854317 |
9,886,625 | 1 | 18 | 1. A activity recognition robot device comprising: a memory storing known activity data objects, wherein each known activity data object represents a known activity and includes similarity scoring techniques and clustered temporal features; and an activity recognition device coupled with the memory having a processor, wherein, upon execution of software instructions stored on a non-transitory computer readable medium, the processor is configurable to: generate a plurality of temporal features from a digital representation of an observed action involving at least one recognized object using at least one feature detection algorithm; establish an observed activity data object comprising one or more observed temporal feature clusters generated from the plurality of temporal features; calculate a similarity activity score for the observed activity data object relative to at least one of the known activity data objects as a function of the similarity scoring techniques that are contextually relevant to the activity recognition device, the clustered temporal features, and the observed temporal feature clusters; access an activity recognition results set as a function of the similarity activity score; and cause the robot to take action based on the activity recognition results set. | 1. A activity recognition robot device comprising: a memory storing known activity data objects, wherein each known activity data object represents a known activity and includes similarity scoring techniques and clustered temporal features; and an activity recognition device coupled with the memory having a processor, wherein, upon execution of software instructions stored on a non-transitory computer readable medium, the processor is configurable to: generate a plurality of temporal features from a digital representation of an observed action involving at least one recognized object using at least one feature detection algorithm; establish an observed activity data object comprising one or more observed temporal feature clusters generated from the plurality of temporal features; calculate a similarity activity score for the observed activity data object relative to at least one of the known activity data objects as a function of the similarity scoring techniques that are contextually relevant to the activity recognition device, the clustered temporal features, and the observed temporal feature clusters; access an activity recognition results set as a function of the similarity activity score; and cause the robot to take action based on the activity recognition results set. 18. The robot device of claim 1 , wherein the digital representation comprises one or more of image data, audio data, tactile data, kinesthetic data, temperature data, kinematic data, and radio signal data. | 0.843703 |
9,020,880 | 1 | 7 | 1. A method for using computer assisted configuration technology to solve product configuration problems using configuration sub-models, the method comprising: performing with the computer system: dividing one or more configuration queries into multiple configuration sub queries, wherein the one or more configuration queries represent one or more questions involving parts and part relationships in a configuration of a configurable product, the multiple configuration sub-queries represent the one or more configuration queries, and the parts represent a composition of matter of the configurable product; processing each sub-query using at least one configuration sub-model per sub-query, wherein the configuration sub-models collectively model a configurable product; generating a response to the one or more configuration queries based upon the processing of each sub-query using at least one configuration sub-model per sub-query; and providing the response to the one or more configuration queries as data for display by a display device. | 1. A method for using computer assisted configuration technology to solve product configuration problems using configuration sub-models, the method comprising: performing with the computer system: dividing one or more configuration queries into multiple configuration sub queries, wherein the one or more configuration queries represent one or more questions involving parts and part relationships in a configuration of a configurable product, the multiple configuration sub-queries represent the one or more configuration queries, and the parts represent a composition of matter of the configurable product; processing each sub-query using at least one configuration sub-model per sub-query, wherein the configuration sub-models collectively model a configurable product; generating a response to the one or more configuration queries based upon the processing of each sub-query using at least one configuration sub-model per sub-query; and providing the response to the one or more configuration queries as data for display by a display device. 7. The method of claim 1 wherein at least two sub-queries include overlapping information. | 0.894366 |
9,135,240 | 1 | 3 | 1. A method for estimating similarity between concepts, the method comprising: receiving a set of concepts related to a corpus of text documents; creating a representative graph structure having graph nodes each representing a latent semantic analysis (LSA) vector associated with a concept, and a node having one or more graph edges, each graph edge representing a strength of a relation between concepts based on an ontology; and deriving, for a concept, a new or modified vector represented by a node in the graph by propagating the LSA vectors against said graph structure, said new or modified vector representing a modified estimated similarity between concepts, wherein a programmed processor device is configured to perform said receiving, creating and deriving. | 1. A method for estimating similarity between concepts, the method comprising: receiving a set of concepts related to a corpus of text documents; creating a representative graph structure having graph nodes each representing a latent semantic analysis (LSA) vector associated with a concept, and a node having one or more graph edges, each graph edge representing a strength of a relation between concepts based on an ontology; and deriving, for a concept, a new or modified vector represented by a node in the graph by propagating the LSA vectors against said graph structure, said new or modified vector representing a modified estimated similarity between concepts, wherein a programmed processor device is configured to perform said receiving, creating and deriving. 3. The method as claimed in claim 1 , wherein said corpus of text documents includes a knowledgebase (KB), said representative graph structure being generated from ontologies found in the KB. | 0.5 |
8,515,786 | 1 | 2 | 1. A rule generation system to generate rules for a computer program, the system comprising: a processor; a memory storage device comprising a computer program, the computer program comprising instructions executable with the processor, the instructions comprising: an evaluative expression parameter module configured to generate a graphical user interface for creation of a navigation rule, the navigation rule being indicative of whether to navigate from a first page of the computer program to a second page of the computer program; the evaluative expression parameter module further configured to receive an expression parameter, a logical operator, and at least one expression parameter value from the graphical user interface in response to user input via the graphical user interface at runtime, the expression parameter identifying a question displayed on the first page of the computer program, the at least one expression parameter value including at least one potential answer to the question, wherein the expression parameter and the at least one expression parameter value are operands of the logical operator; an evaluative expression generator configured to generate the navigation rule, the navigation rule including a combination of a first evaluative expression and a second evaluative expression, the first evaluative expression comprising the expression parameter, the operator, and the at least one expression parameter value; instructions executable with the processor to store the first and second evaluative expressions in a database; instructions executable with the processor to receive an answer to the question displayed on the first page from user input at runtime; instructions executable with the processor to evaluate the first and second evaluative expressions retrieved from the database at runtime, the expression parameter set to the answer in the evaluation of the first evaluative expression; and instructions executable with the processor to navigate to the second page from the first page at runtime based on the evaluation of the first and second evaluative expressions retrieved from the database. | 1. A rule generation system to generate rules for a computer program, the system comprising: a processor; a memory storage device comprising a computer program, the computer program comprising instructions executable with the processor, the instructions comprising: an evaluative expression parameter module configured to generate a graphical user interface for creation of a navigation rule, the navigation rule being indicative of whether to navigate from a first page of the computer program to a second page of the computer program; the evaluative expression parameter module further configured to receive an expression parameter, a logical operator, and at least one expression parameter value from the graphical user interface in response to user input via the graphical user interface at runtime, the expression parameter identifying a question displayed on the first page of the computer program, the at least one expression parameter value including at least one potential answer to the question, wherein the expression parameter and the at least one expression parameter value are operands of the logical operator; an evaluative expression generator configured to generate the navigation rule, the navigation rule including a combination of a first evaluative expression and a second evaluative expression, the first evaluative expression comprising the expression parameter, the operator, and the at least one expression parameter value; instructions executable with the processor to store the first and second evaluative expressions in a database; instructions executable with the processor to receive an answer to the question displayed on the first page from user input at runtime; instructions executable with the processor to evaluate the first and second evaluative expressions retrieved from the database at runtime, the expression parameter set to the answer in the evaluation of the first evaluative expression; and instructions executable with the processor to navigate to the second page from the first page at runtime based on the evaluation of the first and second evaluative expressions retrieved from the database. 2. The rule generation system of claim 1 , wherein the instructions further comprise a common evaluative expression module configured to receive names of common rules from the graphical user interface in response to user input, the evaluative expression generator further configured to include the names of the common rules as operands in the evaluative expression, the evaluation of the evaluative expression depending on an evaluation of the common rules. | 0.645736 |
9,613,098 | 5 | 15 | 5. The method as set forth in claim 1 wherein the accessing of a first cluster model further comprises: receiving by a processor meta-data modeling the first work of literature, the meta-data comprising one or more literary element categories, one or more instances within each literary element categories, and an index value and significance value for each instance, wherein the index value corresponds to a position for an instance between a beginning and an ending of the work of literature, and wherein the significance value corresponds to a significance, weight or strength of an instance relative to other instances in the meta-data; for each literary element category and for each instance within each literary element category of the first work of literature, invoking by a processor a cluster finding process using a first control parameter limiting the range of index value variation and a second control parameter limiting the range of significance value variation in a found cluster; receiving by a processor from the cluster finding process one or more clusters found around one or more instances of one or more literary element categories; and storing by the processor the one or more clusters into the first cluster model for the first work of literature. | 5. The method as set forth in claim 1 wherein the accessing of a first cluster model further comprises: receiving by a processor meta-data modeling the first work of literature, the meta-data comprising one or more literary element categories, one or more instances within each literary element categories, and an index value and significance value for each instance, wherein the index value corresponds to a position for an instance between a beginning and an ending of the work of literature, and wherein the significance value corresponds to a significance, weight or strength of an instance relative to other instances in the meta-data; for each literary element category and for each instance within each literary element category of the first work of literature, invoking by a processor a cluster finding process using a first control parameter limiting the range of index value variation and a second control parameter limiting the range of significance value variation in a found cluster; receiving by a processor from the cluster finding process one or more clusters found around one or more instances of one or more literary element categories; and storing by the processor the one or more clusters into the first cluster model for the first work of literature. 15. The method as set forth in claim 5 further comprising outputting by the processor the cluster model to a digital image file. | 0.73444 |
8,977,555 | 7 | 8 | 7. The computer-implemented method of claim 6 , wherein the marker data comprises the second marker, the computer-implemented method further comprising: determining an amount of time between a first time that presentation of the second portion was initiated, and a second time that the user utterance was initiated. | 7. The computer-implemented method of claim 6 , wherein the marker data comprises the second marker, the computer-implemented method further comprising: determining an amount of time between a first time that presentation of the second portion was initiated, and a second time that the user utterance was initiated. 8. The computer-implemented method of claim 7 , where the amount of time is less than a predetermined threshold, and wherein identifying the related portion comprises identifying the first portion based at least partly on the amount of time. | 0.5 |
6,012,633 | 4 | 6 | 4. An automatic transaction apparatus according to claim 1, wherein said guidance means has a width smaller than a width of said depository inlet. | 4. An automatic transaction apparatus according to claim 1, wherein said guidance means has a width smaller than a width of said depository inlet. 6. An automatic transaction apparatus according to claim 4, wherein said depository inlet has a width for receiving an envelope enclosing a deposit, further comprising: envelope feeding means for feeding the envelope to said storage means; selecting means operable by the user, for selecting either a financial document settling mode to settle the financial document or an envelope processing mode to process said envelope; and gate means responsive to selection of said envelope processing mode by the user through said selecting means, for delivering the envelope inserted into said depository inlet to said envelope feeding means, and also responsive to selection of said financial document settling mode by the user through said selecting means, for delivering the financial document inserted into said depository inlet to said document feed means. | 0.5 |
8,515,985 | 8 | 11 | 8. A non-transitory computer readable storage medium storing computer instructions which, when executed by a processor, cause the processor to: identify one or more candidate query refinements for a query based on one or more previous queries submitted by one or more users; generate, based on the one or more candidate query refinements, one or more term occurrence scores associated with one or more respective terms in the one or more candidate query refinements, the one or more term occurrence scores indicating a frequency of the one or more respective terms in the one or more candidate query refinements; calculate, based on the one or more term occurrence scores, a respective query refinement score for each of the one or more candidate query refinements; generate, for a particular candidate query refinement of the one or more candidate query refinements, a first refinement count, the first refinement count being based on a frequency of occurrence of the particular candidate query refinement in a log; generate, for the particular candidate query refinement, a second refinement count, the second refinement count being based on a frequency of occurrence of another candidate query refinement, of the one or more candidate query refinements, in the log; generate, based on the first refinement count and the second refinement count, a query refinement popularity score for the particular candidate query refinement; and store information associating the respective query refinement score with each of the one or more candidate query refinements and the query refinement popularity score with the particular candidate query refinement for use in selecting among the one or more candidate query refinements for the query. | 8. A non-transitory computer readable storage medium storing computer instructions which, when executed by a processor, cause the processor to: identify one or more candidate query refinements for a query based on one or more previous queries submitted by one or more users; generate, based on the one or more candidate query refinements, one or more term occurrence scores associated with one or more respective terms in the one or more candidate query refinements, the one or more term occurrence scores indicating a frequency of the one or more respective terms in the one or more candidate query refinements; calculate, based on the one or more term occurrence scores, a respective query refinement score for each of the one or more candidate query refinements; generate, for a particular candidate query refinement of the one or more candidate query refinements, a first refinement count, the first refinement count being based on a frequency of occurrence of the particular candidate query refinement in a log; generate, for the particular candidate query refinement, a second refinement count, the second refinement count being based on a frequency of occurrence of another candidate query refinement, of the one or more candidate query refinements, in the log; generate, based on the first refinement count and the second refinement count, a query refinement popularity score for the particular candidate query refinement; and store information associating the respective query refinement score with each of the one or more candidate query refinements and the query refinement popularity score with the particular candidate query refinement for use in selecting among the one or more candidate query refinements for the query. 11. The non-transitory computer readable storage medium of claim 8 , where the one or more instructions further include: one or more instructions to generate, for the particular candidate query refinement, the respective query refinement score using: a sum of term occurrence scores of individual terms within the particular candidate query refinement, and a number of individual terms within the particular candidate query refinement. | 0.509029 |
7,613,687 | 15 | 16 | 15. An information gathering system for optimizing searching as in claim 1 further including a search process that locates websites of business entities that have not been categorized in the SIC predefined taxonomy of SIC business activities. | 15. An information gathering system for optimizing searching as in claim 1 further including a search process that locates websites of business entities that have not been categorized in the SIC predefined taxonomy of SIC business activities. 16. An information gathering system for optimizing searching as in claim 15 wherein the data extraction tool extracts content from the websites that have not been categorized in the SIC predefined taxonomy of SIC business activities. | 0.5 |
9,542,165 | 11 | 12 | 11. The method of claim 1 , wherein the simulation model comprises a behavior analysis model (BEAM) provided as a modular Petri-Net (PN) model comprising extensions. | 11. The method of claim 1 , wherein the simulation model comprises a behavior analysis model (BEAM) provided as a modular Petri-Net (PN) model comprising extensions. 12. The method of claim 11 , wherein the extensions support model transformation and model tracing. | 0.5 |
8,099,663 | 10 | 11 | 10. A method for implementation by one or more data processors comprising: accepting a selection of a destination document on a client device; converting the destination document into a destination document tree hierarchy; flattening the destination document tree hierarchy into a destination document hash table, comprising a set of destination document keys and a set of destination document values; retrieving the set of destination document keys from the client device; retrieving a source document, wherein the source document is a second version of the destination document, from a server device; converting the source document into a source document tree hierarchy; flattening the source document tree hierarchy into a source document hash table, comprising a set of source document key-value pairs; identifying a source document key-value pair, comprising a key and a value, wherein the key is not in the set of destination document keys; adding the source document key-value to a changelist; identifying a destination document key, wherein the destination document key is not a key in a key-value pair in the set of source document key-value pairs; and adding the destination document key to the changelist; and sending the changelist to the client device. | 10. A method for implementation by one or more data processors comprising: accepting a selection of a destination document on a client device; converting the destination document into a destination document tree hierarchy; flattening the destination document tree hierarchy into a destination document hash table, comprising a set of destination document keys and a set of destination document values; retrieving the set of destination document keys from the client device; retrieving a source document, wherein the source document is a second version of the destination document, from a server device; converting the source document into a source document tree hierarchy; flattening the source document tree hierarchy into a source document hash table, comprising a set of source document key-value pairs; identifying a source document key-value pair, comprising a key and a value, wherein the key is not in the set of destination document keys; adding the source document key-value to a changelist; identifying a destination document key, wherein the destination document key is not a key in a key-value pair in the set of source document key-value pairs; and adding the destination document key to the changelist; and sending the changelist to the client device. 11. The method of claim 10 , wherein a key is generated using a cryptographic hash function on document object content selected from two or more of value, location within a document, formatting, data source, language specification, and data context. | 0.583612 |
8,429,627 | 1 | 14 | 1. A non-transitory computer readable memory medium that stores program instructions for analyzing a graphical program, wherein the program instructions are executable by a processor to: display the graphical program on a display, wherein the graphical program comprises a plurality of interconnected nodes that visually indicate functionality of the graphical program; perform a semantic edit operation on the graphical program in response to user input, wherein the semantic edit operation is performed by a first process; perform semantic analysis of the graphical program in response to said performing the semantic edit operation, wherein the semantic analysis is performed by a second process, and wherein the second process is asynchronous with respect to the first process; display results from the semantic analysis of the graphical program in response to completion of the semantic analysis; and perform one or more times: during said performing the semantic analysis, perform another semantic edit operation on the graphical program in response to next user input, wherein the other semantic edit operation is performed by the first process; and in response to said performing the other semantic edit operation, preemptively terminate and re-initiate performing the semantic analysis with respect to the graphical program in the second process; wherein to display results from the semantic analysis of the graphical program in response to completion of the semantic analysis, the program instructions are executable to: display results from the re-initiated semantic analysis of the graphical program in response to completion of the re-initiated semantic analysis. | 1. A non-transitory computer readable memory medium that stores program instructions for analyzing a graphical program, wherein the program instructions are executable by a processor to: display the graphical program on a display, wherein the graphical program comprises a plurality of interconnected nodes that visually indicate functionality of the graphical program; perform a semantic edit operation on the graphical program in response to user input, wherein the semantic edit operation is performed by a first process; perform semantic analysis of the graphical program in response to said performing the semantic edit operation, wherein the semantic analysis is performed by a second process, and wherein the second process is asynchronous with respect to the first process; display results from the semantic analysis of the graphical program in response to completion of the semantic analysis; and perform one or more times: during said performing the semantic analysis, perform another semantic edit operation on the graphical program in response to next user input, wherein the other semantic edit operation is performed by the first process; and in response to said performing the other semantic edit operation, preemptively terminate and re-initiate performing the semantic analysis with respect to the graphical program in the second process; wherein to display results from the semantic analysis of the graphical program in response to completion of the semantic analysis, the program instructions are executable to: display results from the re-initiated semantic analysis of the graphical program in response to completion of the re-initiated semantic analysis. 14. The non-transitory computer readable memory medium of claim 1 , wherein the graphical program comprises a graphical data flow program. | 0.898678 |
8,935,252 | 11 | 12 | 11. A system for rule generation, the system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive a plurality of classification rules; for a set of documents in a corpus, perform repeatedly for each document in the set: applying a plurality of rules from the plurality of classification rules applicable to the document by a) applying an applicable rule of the plurality of rules to the document to obtain a rule outcome, b) selecting another applicable rule of the plurality of rules according to the rule outcome, c) repeating a) and b) one or more times until a final rule outcome is reached; presenting the final rule outcome and the document to a rater; receiving a rating of the final rule outcome; and updating, for one or more of the applicable rules, quality metrics corresponding to the one or more of the applicable rules in accordance with the received rating, wherein updating the quality metrics of the one or more applicable rules comprises, for each applicable rule, adjusting the quality metric corresponding to the each applicable rule by an amount that decreases with a number of intervening rules from the applicable rule that produced the final rule outcome; compare the quality metrics of the plurality of rules to a rule threshold; determine that a first portion of the plurality of rules have quality metrics above the threshold; determine that a second portion of the plurality of rules have quality metrics above the threshold; add the first portion to a production rule set and discarding the second portion; and perform production document classification in accordance with the production rule set. | 11. A system for rule generation, the system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive a plurality of classification rules; for a set of documents in a corpus, perform repeatedly for each document in the set: applying a plurality of rules from the plurality of classification rules applicable to the document by a) applying an applicable rule of the plurality of rules to the document to obtain a rule outcome, b) selecting another applicable rule of the plurality of rules according to the rule outcome, c) repeating a) and b) one or more times until a final rule outcome is reached; presenting the final rule outcome and the document to a rater; receiving a rating of the final rule outcome; and updating, for one or more of the applicable rules, quality metrics corresponding to the one or more of the applicable rules in accordance with the received rating, wherein updating the quality metrics of the one or more applicable rules comprises, for each applicable rule, adjusting the quality metric corresponding to the each applicable rule by an amount that decreases with a number of intervening rules from the applicable rule that produced the final rule outcome; compare the quality metrics of the plurality of rules to a rule threshold; determine that a first portion of the plurality of rules have quality metrics above the threshold; determine that a second portion of the plurality of rules have quality metrics above the threshold; add the first portion to a production rule set and discarding the second portion; and perform production document classification in accordance with the production rule set. 12. The system of claim 11 , wherein the executable and operational data are further effective to cause the one or more processors to receive the plurality of classification rules by: selecting an element of the corpus; transmitting a rule request with the selected element to a rule generator; receiving a rule from the rule generator; and adding the received rule to the plurality of classification rules. | 0.5 |
8,185,567 | 2 | 3 | 2. The method of tying a geospacial location to Extensible Markup Language (XML) content on a network according to claim 1 , wherein: said XML content and its associated said geospacial location information is inserted in an “entity=” list in said <presence . . . > section of said PIDF-LO compliant document. | 2. The method of tying a geospacial location to Extensible Markup Language (XML) content on a network according to claim 1 , wherein: said XML content and its associated said geospacial location information is inserted in an “entity=” list in said <presence . . . > section of said PIDF-LO compliant document. 3. The method of tying a geospacial location to Extensible Markup Language (XML) content on a network according to claim 2 , wherein: said XML content and its associated said geospacial location information is also inserted in a “src=” list in said <presence . . . > section of said PIDF-LO compliant document. | 0.5 |
7,583,762 | 11 | 12 | 11. The invention as recited in claim 1 , wherein the apparatus is embodied in an integrated circuit (IC). | 11. The invention as recited in claim 1 , wherein the apparatus is embodied in an integrated circuit (IC). 12. The invention as recited in claim 11 , wherein the IC is embodied in a receiver operating in accordance with an IEEE 802.11 a/b/g standard for orthogonal frequency division multiplex (OFDM) wireless local area networks. | 0.5 |
9,171,326 | 3 | 4 | 3. The method of claim 1 , wherein the first, second, third, and fourth threshold conditions are identical. | 3. The method of claim 1 , wherein the first, second, third, and fourth threshold conditions are identical. 4. The method of claim 3 , further comprising: selecting products corresponding to the interest profile; and transmitting a gift recommendation including the selected products to a second user. | 0.5 |
10,140,320 | 13 | 14 | 13. The method according to claim 1 , further comprising: aggregating a plurality of audit trails on the client device when the client device is offline; and providing the plurality of audit trails to a publishing server when the client device communicatively connects to the one or more publishing servers. | 13. The method according to claim 1 , further comprising: aggregating a plurality of audit trails on the client device when the client device is offline; and providing the plurality of audit trails to a publishing server when the client device communicatively connects to the one or more publishing servers. 14. The method according to claim 13 , further comprising validating the client device via the one or more publishing servers utilizing an API key. | 0.5 |
7,552,385 | 2 | 3 | 2. The method of claim 1 , further comprising: developing a third vector for said entire document corpus, said third vector comprising a sequential listing of floating point multipliers, each said floating point multiplier representing a document normalization factor. | 2. The method of claim 1 , further comprising: developing a third vector for said entire document corpus, said third vector comprising a sequential listing of floating point multipliers, each said floating point multiplier representing a document normalization factor. 3. The method of claim 2 , wherein said normalization factor is calculated as: NF =1/(S x i 2 ) 1/2 , where x i is the number of occurrences of a specific term in said document, so that NF represents the reciprocal of the square root of the sum of squares of all term occurrences in said document. | 0.5 |
8,032,838 | 15 | 18 | 15. A data processor readable medium storing data processor code executable by a processor to: receive a block of markup language code for rendering a section of a markup language based e-mail on a display; identify in the block of markup language code any style rules interleaved therein for rendering the section of the markup language based e-mail on the display; process the interleaved style rules identified in the block of markup language code; render the section of the markup language based e-mail on the display based on the processed style rules; receive a subsequent block of markup language code for rendering a subsequent section of the markup language based e-mail on a display; identify, in the subsequent block of markup language code any style rules interleaved therein for rendering the subsequent section of the markup language based e-mail on the display; process the interleaved style rules identified in the subsequent block of markup language code; and render the subsequent section of the markup language based e-mail on the display based on the processed style rules. | 15. A data processor readable medium storing data processor code executable by a processor to: receive a block of markup language code for rendering a section of a markup language based e-mail on a display; identify in the block of markup language code any style rules interleaved therein for rendering the section of the markup language based e-mail on the display; process the interleaved style rules identified in the block of markup language code; render the section of the markup language based e-mail on the display based on the processed style rules; receive a subsequent block of markup language code for rendering a subsequent section of the markup language based e-mail on a display; identify, in the subsequent block of markup language code any style rules interleaved therein for rendering the subsequent section of the markup language based e-mail on the display; process the interleaved style rules identified in the subsequent block of markup language code; and render the subsequent section of the markup language based e-mail on the display based on the processed style rules. 18. The data processor readable medium of claim 15 , wherein the data processor code is executable by the processor to process global style rules interleaved in the first block of markup language code, and applying the global style rules to all subsequent blocks of markup language code. | 0.548742 |
8,754,860 | 15 | 16 | 15. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display and a touch-sensitive surface, cause the device to: display an unsplit keyboard; replace display of the unsplit keyboard with display of an integrated input area in response to detecting a gesture on the touch-sensitive surface; concurrently display a first text entry area and the integrated input area, the integrated input area including: a left portion with a left side of a split keyboard; a right portion with a right side of the split keyboard, wherein the left side of the split keyboard and the right side of the split keyboard maintain fixed positions relative to each other within the integrated input area during movement of the integrated input area; and a center portion with a second text entry area, the center portion in between the left portion and the right portion; detect a gesture at a location on the touch-sensitive surface that corresponds to a location of a character key in the split keyboard; and, in response to detecting the gesture at the location on the touch-sensitive surface that corresponds to the location of the character key in the split keyboard, input and concurrently display the corresponding character in the first text entry area and the second text entry area on the display. | 15. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display and a touch-sensitive surface, cause the device to: display an unsplit keyboard; replace display of the unsplit keyboard with display of an integrated input area in response to detecting a gesture on the touch-sensitive surface; concurrently display a first text entry area and the integrated input area, the integrated input area including: a left portion with a left side of a split keyboard; a right portion with a right side of the split keyboard, wherein the left side of the split keyboard and the right side of the split keyboard maintain fixed positions relative to each other within the integrated input area during movement of the integrated input area; and a center portion with a second text entry area, the center portion in between the left portion and the right portion; detect a gesture at a location on the touch-sensitive surface that corresponds to a location of a character key in the split keyboard; and, in response to detecting the gesture at the location on the touch-sensitive surface that corresponds to the location of the character key in the split keyboard, input and concurrently display the corresponding character in the first text entry area and the second text entry area on the display. 16. The computer readable storage medium of claim 15 , wherein the width of the integrated input area is the same as the width of the display. | 0.88854 |
9,613,618 | 12 | 17 | 12. An apparatus that recognizes a voice input signal involving multiple languages, the apparatus comprising: a microphone configured to receive a voice input signal which is input by a user; a storage unit configured to store a voice recognition algorithm for a primary language and a voice recognition algorithm for a non-primary language; a controller configured to recognize the voice input signal by using the voice recognition algorithm for the primary language, identify a segment of the voice input signal, which is in the non- primary language, in the voice input signal based on the recognition for the primary language, determine a language of the segment of the voice input signal based on context information, and recognize the segment of the voice input signal by using a voice recognition algorithm for the determined language; and a display unit configured to output a recognition result of the voice input signal which is based on the recognition for the primary language and the recognition for the determined language. | 12. An apparatus that recognizes a voice input signal involving multiple languages, the apparatus comprising: a microphone configured to receive a voice input signal which is input by a user; a storage unit configured to store a voice recognition algorithm for a primary language and a voice recognition algorithm for a non-primary language; a controller configured to recognize the voice input signal by using the voice recognition algorithm for the primary language, identify a segment of the voice input signal, which is in the non- primary language, in the voice input signal based on the recognition for the primary language, determine a language of the segment of the voice input signal based on context information, and recognize the segment of the voice input signal by using a voice recognition algorithm for the determined language; and a display unit configured to output a recognition result of the voice input signal which is based on the recognition for the primary language and the recognition for the determined language. 17. The apparatus as claimed in claim 12 , wherein the storage unit is configured to store a database of phonemes in the primary language, and the controller is configured to segment the voice input signal in a unit of phoneme, determine a similarity between at least one segmented phoneme and a word in the primary language by matching the at least one segmented phoneme with the database of the phonemes in the primary language, and identify that the at least one segmented phoneme having the determined similarity less than a preset threshold belongs to the segment of the voice input signal. | 0.794118 |
8,051,109 | 1 | 6 | 1. A document system comprising: a web server computer adapted to receive a document collection in a first format, the document collection including a plurality of documents in the first format, each document including an indication of a corresponding classification code; a database server computer coupled to the web server computer and including a document store adapted to store the documents; and wherein the web server computer is adapted to transform each document by substituting the classification code corresponding to that document with a keyword associated with the corresponding classification code, wherein the web server computer is adapted to convert each document, including its keyword, from the first format into a second format different from the first format, wherein the web server computer is adapted to transmit each converted document to the database server computer and the database server computer is adapted to store the converted document in the document store, and wherein the web server computer is adapted to provide converted documents corresponding to a request received from another system, different from the document system. | 1. A document system comprising: a web server computer adapted to receive a document collection in a first format, the document collection including a plurality of documents in the first format, each document including an indication of a corresponding classification code; a database server computer coupled to the web server computer and including a document store adapted to store the documents; and wherein the web server computer is adapted to transform each document by substituting the classification code corresponding to that document with a keyword associated with the corresponding classification code, wherein the web server computer is adapted to convert each document, including its keyword, from the first format into a second format different from the first format, wherein the web server computer is adapted to transmit each converted document to the database server computer and the database server computer is adapted to store the converted document in the document store, and wherein the web server computer is adapted to provide converted documents corresponding to a request received from another system, different from the document system. 6. The document system of claim 1 , wherein each keyword is based on a definition of the corresponding classification code. | 0.672872 |
8,731,954 | 1 | 4 | 1. A method performed by a computer of evaluating coded medical documents, the method comprising: receiving, by a computer, audit parameters comprising an expected coder error level, and receiving an empirically established expected auditor error level of an auditor based on an assessment of the auditor; selecting, by the computer, a sample batch of coded medical documents for auditing by the auditor, the sample batch of coded medical documents selected from a universe of coded medical documents stored on one or more storage devices, the selection based at least in part on the received audit parameters; receiving, by the computer, audited medical documents corresponding to the selected sample batch of coded medical documents, wherein the audited medical documents include corrections by the auditor; calculating, by the computer, a medical document score for each of the audited medical documents based on medical document corrections received from the auditor and applying weighted factors, wherein the weighted factors comprise predefined weights assigned to diagnosis and procedure codes in each of the audited medical documents; calculating, by the computer, a sample score for the audited medical documents based on a function of the calculated medical document scores; designating, by the computer, at least one of an upper control limit and a lower control limit based on the expected auditor error level; and comparing, by the computer, the sample score against the at least one of the upper and lower control limits to determine an acceptability of the sample score. | 1. A method performed by a computer of evaluating coded medical documents, the method comprising: receiving, by a computer, audit parameters comprising an expected coder error level, and receiving an empirically established expected auditor error level of an auditor based on an assessment of the auditor; selecting, by the computer, a sample batch of coded medical documents for auditing by the auditor, the sample batch of coded medical documents selected from a universe of coded medical documents stored on one or more storage devices, the selection based at least in part on the received audit parameters; receiving, by the computer, audited medical documents corresponding to the selected sample batch of coded medical documents, wherein the audited medical documents include corrections by the auditor; calculating, by the computer, a medical document score for each of the audited medical documents based on medical document corrections received from the auditor and applying weighted factors, wherein the weighted factors comprise predefined weights assigned to diagnosis and procedure codes in each of the audited medical documents; calculating, by the computer, a sample score for the audited medical documents based on a function of the calculated medical document scores; designating, by the computer, at least one of an upper control limit and a lower control limit based on the expected auditor error level; and comparing, by the computer, the sample score against the at least one of the upper and lower control limits to determine an acceptability of the sample score. 4. The method of claim 1 , further comprising: repeating the evaluation over a period of time to compile a plurality of sample scores; and tracking a measure of variance in the compiled sample scores across the period of time. | 0.517094 |
7,831,910 | 1 | 4 | 1. A method for computer aided authoring, comprising: while a writer is writing an electronic document, generating one or more topic based on said electronic document, each topic generated having one or more topic terms; generating two or more topic summaries for each topic, generating, for each summary, including: selecting a predetermined number of sentences from the electronic document based on calculated relevance and importance of each sentence; from the neighboring sentences of said selected sentences, selecting one or more sentences having high relevance with said selected sentences to incorporate into the summary of said topic; presenting the two or more summaries for each topic to the writer; receiving a verified summary formed at least in part by one of the two or more summaries; evaluating the accuracy of said verified summary; and saving said topic summary information in correspondence with said electronic document, wherein said step of saving said topic summary further comprises saving information about the accuracy of said summary. | 1. A method for computer aided authoring, comprising: while a writer is writing an electronic document, generating one or more topic based on said electronic document, each topic generated having one or more topic terms; generating two or more topic summaries for each topic, generating, for each summary, including: selecting a predetermined number of sentences from the electronic document based on calculated relevance and importance of each sentence; from the neighboring sentences of said selected sentences, selecting one or more sentences having high relevance with said selected sentences to incorporate into the summary of said topic; presenting the two or more summaries for each topic to the writer; receiving a verified summary formed at least in part by one of the two or more summaries; evaluating the accuracy of said verified summary; and saving said topic summary information in correspondence with said electronic document, wherein said step of saving said topic summary further comprises saving information about the accuracy of said summary. 4. An article of manufacture comprising a computer usable medium having computer readable program code means embodied therein for causing the subscribing and publishing of electronic documents, the computer readable program code means in said article of manufacture comprising computer readable program code means for causing a computer to effect the steps of claim 1 . | 0.5 |
8,498,974 | 11 | 12 | 11. A system comprising: one or more processors programmed operable to perform operations comprising: obtaining a plurality of search results responsive to a search query submitted by a user, wherein each search result refers to a respective document that is associated with a respective plurality of click measures, each click measure relating to a different respective natural language and representing, at least, a measure of behavior of users associated with the respective language in regards to the document when the document was referred to in a search result previously provided in response to the search query; for each of a first plurality of the search results, reducing the click measure associated with the document referred to by the search result, wherein the click measure relates to a respective natural language that is incompatible with a natural language of the user; calculating a respective scoring factor for each of the first plurality of search results based on the respective click measures associated with the document referred to by the first search result; and ranking the search results based upon, at least, the calculated scoring factors. | 11. A system comprising: one or more processors programmed operable to perform operations comprising: obtaining a plurality of search results responsive to a search query submitted by a user, wherein each search result refers to a respective document that is associated with a respective plurality of click measures, each click measure relating to a different respective natural language and representing, at least, a measure of behavior of users associated with the respective language in regards to the document when the document was referred to in a search result previously provided in response to the search query; for each of a first plurality of the search results, reducing the click measure associated with the document referred to by the search result, wherein the click measure relates to a respective natural language that is incompatible with a natural language of the user; calculating a respective scoring factor for each of the first plurality of search results based on the respective click measures associated with the document referred to by the first search result; and ranking the search results based upon, at least, the calculated scoring factors. 12. The system of claim 11 wherein calculating the scoring factor further comprises weighting a combination of the respective click measures for the document by a weight that represents the user's ability to understand the document. | 0.560606 |
9,699,142 | 14 | 18 | 14. A non-transitory computer-readable storage medium having stored thereon instructions that, when executed by one or more processors of a computer system, cause the computer system to: obtain information representative of web content, the web content including webpage content from multiple pages of a website that are identified with different domain names; analyze the information to identify commonalities among the multiple pages of the website identified with different domain names; generate, based at least in part on the identified commonalities between the multiple pages of the website, a document object model template specifying a structure of permissible web content; and provide the document object model template to a user device for use in evaluating further web content. | 14. A non-transitory computer-readable storage medium having stored thereon instructions that, when executed by one or more processors of a computer system, cause the computer system to: obtain information representative of web content, the web content including webpage content from multiple pages of a website that are identified with different domain names; analyze the information to identify commonalities among the multiple pages of the website identified with different domain names; generate, based at least in part on the identified commonalities between the multiple pages of the website, a document object model template specifying a structure of permissible web content; and provide the document object model template to a user device for use in evaluating further web content. 18. The non-transitory computer-readable storage medium of claim 14 , wherein the document object model template specifies a target property of a node element. | 0.849432 |
9,323,826 | 6 | 7 | 6. The method of claim 5 , wherein the examining step further includes identifying metadata associated with each micro-blog message contained in the plurality of received micro-blog messages. | 6. The method of claim 5 , wherein the examining step further includes identifying metadata associated with each micro-blog message contained in the plurality of received micro-blog messages. 7. The method of claim 6 , wherein the metadata associated with each received micro-blog message includes at least one of geographic information about the micro-blog message, information about user generating the micro-blog message, and information specifying the time the user generated the micro-blog message. | 0.5 |
8,510,315 | 1 | 8 | 1. A computer-based method, comprising: receiving an itinerary query comprising a starting location, an ending location and a duration; identifying a set of trip candidates, from a location-interest graph, comprising: performing a first comparison of the starting location of the itinerary query with at least one of a first starting location of a first trip candidate, a second starting location of a second trip candidate, a third starting location of a third trip candidate or a fourth starting location of a fourth trip candidate; performing a second comparison of the ending location of the itinerary query with at least one of a first ending location of the first trip candidate, a second ending location of the second trip candidate, a third ending location of the third trip candidate or a fourth ending location of the fourth trip candidate; performing a third comparison of the duration of the itinerary query with at least one of: a combination of at least a first travel time associated with the first trip candidate and a first stay time associated with one or more locations associated with the first trip candidate; a combination of at least a second travel time associated with the second trip candidate and a second stay time associated with one or more locations associated with the second trip candidate; a combination of at least a third travel time associated with the third trip candidate and a third stay time associated with one or more locations associated with the third trip candidate; or a combination of at least a fourth travel time associated with the fourth trip candidate and a fourth stay time associated with one or more locations associated with the fourth trip candidate; and including the first trip candidate, the second trip candidate and the third trip candidate, but not the fourth trip candidate, within the set of trip candidates based on the first comparison, the second comparison and the third comparison; identifying: a first threshold difference for the first trip candidate, the first threshold difference comprising a first difference between a desired threshold value and a first value for the first trip candidate; a second threshold difference for the second trip candidate, the second threshold difference comprising a second difference between the desired threshold value and a second value for the second trip candidate; and a third threshold difference for the third trip candidate, the third threshold difference comprising a third difference between the desired threshold value and a third value for the third trip candidate, at least one of the desired threshold value, the first value, the second value or the third threshold value based on one or more trip factors; selecting the first trip candidate and the second trip candidate, but not the third trip candidate, from the set of trip candidates based on the first threshold difference and the second threshold difference corresponding to a desired range of identified threshold differences, and the third threshold difference not corresponding to the desired range of identified threshold differences; ranking the first trip candidate and the second trip candidate based on one or more ranking factors; re-ranking the first trip candidate and the second trip candidate based on one or more historical travel sequences; and providing the re-ranked trip candidates in response to receiving the itinerary query. | 1. A computer-based method, comprising: receiving an itinerary query comprising a starting location, an ending location and a duration; identifying a set of trip candidates, from a location-interest graph, comprising: performing a first comparison of the starting location of the itinerary query with at least one of a first starting location of a first trip candidate, a second starting location of a second trip candidate, a third starting location of a third trip candidate or a fourth starting location of a fourth trip candidate; performing a second comparison of the ending location of the itinerary query with at least one of a first ending location of the first trip candidate, a second ending location of the second trip candidate, a third ending location of the third trip candidate or a fourth ending location of the fourth trip candidate; performing a third comparison of the duration of the itinerary query with at least one of: a combination of at least a first travel time associated with the first trip candidate and a first stay time associated with one or more locations associated with the first trip candidate; a combination of at least a second travel time associated with the second trip candidate and a second stay time associated with one or more locations associated with the second trip candidate; a combination of at least a third travel time associated with the third trip candidate and a third stay time associated with one or more locations associated with the third trip candidate; or a combination of at least a fourth travel time associated with the fourth trip candidate and a fourth stay time associated with one or more locations associated with the fourth trip candidate; and including the first trip candidate, the second trip candidate and the third trip candidate, but not the fourth trip candidate, within the set of trip candidates based on the first comparison, the second comparison and the third comparison; identifying: a first threshold difference for the first trip candidate, the first threshold difference comprising a first difference between a desired threshold value and a first value for the first trip candidate; a second threshold difference for the second trip candidate, the second threshold difference comprising a second difference between the desired threshold value and a second value for the second trip candidate; and a third threshold difference for the third trip candidate, the third threshold difference comprising a third difference between the desired threshold value and a third value for the third trip candidate, at least one of the desired threshold value, the first value, the second value or the third threshold value based on one or more trip factors; selecting the first trip candidate and the second trip candidate, but not the third trip candidate, from the set of trip candidates based on the first threshold difference and the second threshold difference corresponding to a desired range of identified threshold differences, and the third threshold difference not corresponding to the desired range of identified threshold differences; ranking the first trip candidate and the second trip candidate based on one or more ranking factors; re-ranking the first trip candidate and the second trip candidate based on one or more historical travel sequences; and providing the re-ranked trip candidates in response to receiving the itinerary query. 8. The method of claim 1 , ranking comprising ranking a trip candidate based on a location interest factor for the trip candidate. | 0.841076 |
9,965,259 | 9 | 10 | 9. The system according to claim 1 wherein said translation module generates a tagged element inserted in the second computer language source code indicative of a type of data manipulation the first computer language source code performs. | 9. The system according to claim 1 wherein said translation module generates a tagged element inserted in the second computer language source code indicative of a type of data manipulation the first computer language source code performs. 10. The system according to claim 9 wherein the tagged element comprises information including: formatting, translation data, and first computer language source code. | 0.5 |
8,032,518 | 25 | 33 | 25. A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: web crawl control instructions for controlling crawling of each website of a multiplicity of websites, each website having a corresponding current crawl rate limit, the web crawl control instructions including: instructions for crawling a respective website of the multiplicity of websites, in accordance with the current crawl rate limit corresponding to the respective website, to download documents from the respective website for inclusion in a database; instructions for storing crawl data associated with the crawling of the respective website; and instructions for providing, for display, a crawl rate control mechanism to a respective owner of the respective website, including providing, for display to the respective owner, at least a portion of the crawl data, and enabling selection, by the respective owner, of a new crawl rate limit corresponding to the respective website. | 25. A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: web crawl control instructions for controlling crawling of each website of a multiplicity of websites, each website having a corresponding current crawl rate limit, the web crawl control instructions including: instructions for crawling a respective website of the multiplicity of websites, in accordance with the current crawl rate limit corresponding to the respective website, to download documents from the respective website for inclusion in a database; instructions for storing crawl data associated with the crawling of the respective website; and instructions for providing, for display, a crawl rate control mechanism to a respective owner of the respective website, including providing, for display to the respective owner, at least a portion of the crawl data, and enabling selection, by the respective owner, of a new crawl rate limit corresponding to the respective website. 33. The computer program product of claim 25 , including instructions for providing, for display, resource usage statistics corresponding to resources of the respective website used during a plurality of prior crawl visits of the website. | 0.790123 |
7,805,704 | 1 | 6 | 1. A computer-implemented voice user interface system, comprising: an application program interface that supports configuration of a voice user interface that mixes different types of audible dialog prompts, and wherein the application program interface comprises: a first dialog container that includes information for activating, in a predetermined sequence, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the first dialog container, the predetermined sequence being at least partially determined by semantics-driven audible dialog functionality applied by the first dialog container to said collection of audible dialog elements assigned to the first dialog container; a second dialog container that includes information for activating, in a predetermined order, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the second dialog container, the predetermined order being at least partially determined by state-driven audible dialog functionality applied by the second dialog container to said collection of audible dialog elements assigned to the second dialog container; a particular audible dialog element that corresponds to a particular audible dialog prompt, wherein the particular audible dialog element having different property setting requirements depending upon whether included in the collection of audible dialog elements assigned to the first dialog container or the set of audible dialog elements assigned to the second dialog container; and a computer processor that is a component of a computing device, wherein the computer processor processes an implementation of the application program interface and provides a corresponding implementation of the voice user interface by outputting, to a user of the voice user interface system, said audible dialog prompts that correspond to the collection of audible dialog elements assigned to the first dialog container and said audible dialog prompts that correspond to the collection of audible dialog elements assigned to the second dialog container. | 1. A computer-implemented voice user interface system, comprising: an application program interface that supports configuration of a voice user interface that mixes different types of audible dialog prompts, and wherein the application program interface comprises: a first dialog container that includes information for activating, in a predetermined sequence, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the first dialog container, the predetermined sequence being at least partially determined by semantics-driven audible dialog functionality applied by the first dialog container to said collection of audible dialog elements assigned to the first dialog container; a second dialog container that includes information for activating, in a predetermined order, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the second dialog container, the predetermined order being at least partially determined by state-driven audible dialog functionality applied by the second dialog container to said collection of audible dialog elements assigned to the second dialog container; a particular audible dialog element that corresponds to a particular audible dialog prompt, wherein the particular audible dialog element having different property setting requirements depending upon whether included in the collection of audible dialog elements assigned to the first dialog container or the set of audible dialog elements assigned to the second dialog container; and a computer processor that is a component of a computing device, wherein the computer processor processes an implementation of the application program interface and provides a corresponding implementation of the voice user interface by outputting, to a user of the voice user interface system, said audible dialog prompts that correspond to the collection of audible dialog elements assigned to the first dialog container and said audible dialog prompts that correspond to the collection of audible dialog elements assigned to the second dialog container. 6. The system of claim 1 , wherein the particular audible dialog element is a QuestionAnswer element. | 0.858939 |
7,949,533 | 1 | 6 | 1. A method for assessing a performance of a speech recognition system, comprising: using at least one processor, determining a grade, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words, wherein the grade indicates a level of the performance of the system; and the grade is based on a recognition rate determined from a plurality of recognition observations and at least one recognition factor. | 1. A method for assessing a performance of a speech recognition system, comprising: using at least one processor, determining a grade, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words, wherein the grade indicates a level of the performance of the system; and the grade is based on a recognition rate determined from a plurality of recognition observations and at least one recognition factor. 6. The method of claim 1 , wherein the recognition rate is an accuracy rate based on estimated correct observations by the system estimated from evaluating system behavior. | 0.782278 |
9,772,981 | 22 | 24 | 22. The apparatus of claim 21 wherein the semantic unit is a word in a human language. | 22. The apparatus of claim 21 wherein the semantic unit is a word in a human language. 24. The apparatus of claim 22 wherein the processor selects files for processing by filtering files based on likelihood of retrieval. | 0.6675 |
8,495,156 | 1 | 11 | 1. A method comprising: determining that a user of a first instant messaging service is associated with a second instant messaging service different from the first instant messaging service; identifying user identities for user other than the user, wherein the user identities are associated with the first instant messaging service and the user identities are stored in a first list associated with the user; determining if at least one of the user identities from the first list of user identities has a matching user identity associated with the second instant messaging service by identifying if a unique portion of the at least one of the user identities from the first list of user identities has at least one common feature with a unique portion of a user identity associated with the second instant messaging service; determining a degree of uniqueness of an identified user identity; adjusting the required amount of common features between the unique portion of the identified user identity and the unique portion of a matching user identity associated with the second instant messaging service based on the determined degree of uniqueness of the identified user identity; and modifying, by a hardware processor, a second list associated with the second instant messaging service to include the matching user identities. | 1. A method comprising: determining that a user of a first instant messaging service is associated with a second instant messaging service different from the first instant messaging service; identifying user identities for user other than the user, wherein the user identities are associated with the first instant messaging service and the user identities are stored in a first list associated with the user; determining if at least one of the user identities from the first list of user identities has a matching user identity associated with the second instant messaging service by identifying if a unique portion of the at least one of the user identities from the first list of user identities has at least one common feature with a unique portion of a user identity associated with the second instant messaging service; determining a degree of uniqueness of an identified user identity; adjusting the required amount of common features between the unique portion of the identified user identity and the unique portion of a matching user identity associated with the second instant messaging service based on the determined degree of uniqueness of the identified user identity; and modifying, by a hardware processor, a second list associated with the second instant messaging service to include the matching user identities. 11. The method of claim 1 , wherein at least one of the matching user identities and the identified user identities comprise electronic mail addresses. | 0.853682 |
9,098,570 | 1 | 2 | 1. A method of searching a collection of electronic documents comprising: using a synonym ring to generate a set of standardized paragraph terms for paragraphs in electronic documents in the collection, wherein each set of standardized paragraph terms is associated with an individual paragraph; replacing a set of synonymous terms within a paragraph with the set of standardized paragraph terms; associating term weight values with paragraph terms in the sets of standardized paragraph terms, wherein each term weight value is associated with an individual paragraph term; generating a set of search terms in response to receipt of a search query, wherein the search terms are based at least in part on a query string of the search query; replacing the search query with the set of standardized paragraph terms; comparing the set of search terms with the sets of paragraph terms; generating a paragraph score for the paragraphs using the term weight values of the standardized paragraph terms that match one or more of the search terms, wherein each paragraph score is associated with an individual paragraph; generating an overall document score for the electronic documents by combining the paragraph scores of the paragraphs in the electronic documents, wherein each overall document score is associated with an individual electronic document; determining, by a processor, a set of matching documents from the electronic documents associated with the collection based at least in part on the generated overall document scores, wherein the electronic documents within the set of matching documents are sorted by overall document score; and providing the set of matching documents for display. | 1. A method of searching a collection of electronic documents comprising: using a synonym ring to generate a set of standardized paragraph terms for paragraphs in electronic documents in the collection, wherein each set of standardized paragraph terms is associated with an individual paragraph; replacing a set of synonymous terms within a paragraph with the set of standardized paragraph terms; associating term weight values with paragraph terms in the sets of standardized paragraph terms, wherein each term weight value is associated with an individual paragraph term; generating a set of search terms in response to receipt of a search query, wherein the search terms are based at least in part on a query string of the search query; replacing the search query with the set of standardized paragraph terms; comparing the set of search terms with the sets of paragraph terms; generating a paragraph score for the paragraphs using the term weight values of the standardized paragraph terms that match one or more of the search terms, wherein each paragraph score is associated with an individual paragraph; generating an overall document score for the electronic documents by combining the paragraph scores of the paragraphs in the electronic documents, wherein each overall document score is associated with an individual electronic document; determining, by a processor, a set of matching documents from the electronic documents associated with the collection based at least in part on the generated overall document scores, wherein the electronic documents within the set of matching documents are sorted by overall document score; and providing the set of matching documents for display. 2. The method of claim 1 , wherein the term weight values are generated using inverse frequency scores. | 0.700581 |
8,433,237 | 1 | 10 | 1. A method implemented on a computing device having a processor for designing an academic course, comprising: using the computing device having the processor to perform the following: selecting a natural interaction forum; attaching a rubric to the selected natural interaction forum, wherein the rubric is a template used for assessing the learner's knowledge of the topic; assigning to the learner a natural interaction assignment in the selected natural interaction forum to assess the learner's knowledge of the topic; creating tags for the learner's posts in the natural interaction forum that matches information in the learner's posts to topics in the rubric; assessing the learner's knowledge of the topic with the natural interaction assignment to generate assessment results based at least in part on the created tags for the learner's posts; and computing a final score of the learner on the natural interaction assignment from the assessment results. | 1. A method implemented on a computing device having a processor for designing an academic course, comprising: using the computing device having the processor to perform the following: selecting a natural interaction forum; attaching a rubric to the selected natural interaction forum, wherein the rubric is a template used for assessing the learner's knowledge of the topic; assigning to the learner a natural interaction assignment in the selected natural interaction forum to assess the learner's knowledge of the topic; creating tags for the learner's posts in the natural interaction forum that matches information in the learner's posts to topics in the rubric; assessing the learner's knowledge of the topic with the natural interaction assignment to generate assessment results based at least in part on the created tags for the learner's posts; and computing a final score of the learner on the natural interaction assignment from the assessment results. 10. The method of claim 1 , further comprising: using a natural language technique to examine the learner's posts in the natural interaction forum for specific topics and keywords contained in the rubric; and defining results of the examination with the natural language technique as the natural language metric. | 0.5 |
7,769,751 | 19 | 20 | 19. A computer system that automatically classifies documents based on user inputs, comprising: a processor; a memory; a document-receiving mechanism configured to receive a set of documents which are classified as relating to a specific topic; a feature-vector producing mechanism configured to produce an initial feature vector that corresponds to frequency of a term's occurrence in the set of documents; a classifying mechanism configured to use the initial feature vector to classify another set of documents to produce an initial classified set of documents; a query-receiving mechanism configured to receive click information associated with a set of queries related to the specific topic, wherein the q click information includes a click-through rate at which a query result is selected after being presented and a click duration indicating an amount of time during which the query result is accessed; a removing mechanism configured to use the click information to remove off-topic documents in the set of documents to obtain an updated set of documents, wherein a document is off-topic if the click-through rate or the click duration associated with the document indicates that the document is off-topic; a determination mechanism configured to determine an updated feature vector using the updated set of documents; and a re-classification mechanism configured to re-classifying the classified set of documents using the updated feature vector when the percentage of documents identified as off-topic exceeds a threshold which is greater than 0, otherwise retaining the initial classified set of documents. | 19. A computer system that automatically classifies documents based on user inputs, comprising: a processor; a memory; a document-receiving mechanism configured to receive a set of documents which are classified as relating to a specific topic; a feature-vector producing mechanism configured to produce an initial feature vector that corresponds to frequency of a term's occurrence in the set of documents; a classifying mechanism configured to use the initial feature vector to classify another set of documents to produce an initial classified set of documents; a query-receiving mechanism configured to receive click information associated with a set of queries related to the specific topic, wherein the q click information includes a click-through rate at which a query result is selected after being presented and a click duration indicating an amount of time during which the query result is accessed; a removing mechanism configured to use the click information to remove off-topic documents in the set of documents to obtain an updated set of documents, wherein a document is off-topic if the click-through rate or the click duration associated with the document indicates that the document is off-topic; a determination mechanism configured to determine an updated feature vector using the updated set of documents; and a re-classification mechanism configured to re-classifying the classified set of documents using the updated feature vector when the percentage of documents identified as off-topic exceeds a threshold which is greater than 0, otherwise retaining the initial classified set of documents. 20. The computer system of claim 19 , wherein the apparatus further comprises a query-processing mechanism, wherein the query-processing mechanism is configured to: receive a new query; determine whether the new query is related to the specific topic; and to process the new query to produce query results, wherein if the new query is related to the specific topic, processing the new query involves adjusting relevancy scores for documents based on annotations associated with the documents, wherein the annotations indicate whether the documents are related to the specific topic. | 0.5 |
10,089,386 | 1 | 2 | 1. A method of providing an answer keyword, by a device having a processor, to a user terminal, the method comprising: obtaining at least one of a search word history comprising a first inquiry search word of a certain domain pre-received from first user terminals, and webpage information selected by the first user terminals from a search result according to the search word history; extracting answer candidate keywords regarding the first inquiry search word from at least one of the search word history and the webpage information based on keyword lists of the certain domain; calculating a relation value between the first inquiry search word and each of the extracted answer candidate keywords; and when the first inquiry search word is received from a second user terminal, transmitting answer keywords for the first inquiry search word, which are selected from the answer candidate keywords based on the relation value, to the second user terminal. | 1. A method of providing an answer keyword, by a device having a processor, to a user terminal, the method comprising: obtaining at least one of a search word history comprising a first inquiry search word of a certain domain pre-received from first user terminals, and webpage information selected by the first user terminals from a search result according to the search word history; extracting answer candidate keywords regarding the first inquiry search word from at least one of the search word history and the webpage information based on keyword lists of the certain domain; calculating a relation value between the first inquiry search word and each of the extracted answer candidate keywords; and when the first inquiry search word is received from a second user terminal, transmitting answer keywords for the first inquiry search word, which are selected from the answer candidate keywords based on the relation value, to the second user terminal. 2. The method of claim 1 , wherein the calculating of the relation value comprises selecting a certain number of the answer keywords from the answer candidate keywords in an order from high to low relation value. | 0.895567 |
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