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7,877,421 | 4 | 5 | 4. The method of claim 1 wherein the ontology model includes business rules that relate properties of a class. | 4. The method of claim 1 wherein the ontology model includes business rules that relate properties of a class. 5. The method of claim 4 wherein the business rules include conversion rules, for converting among properties of a class. | 0.5 |
9,998,472 | 9 | 10 | 9. A system, comprising: a processor; and a computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: receiving a query from a member of an enterprise; searching an index that includes member information of members of the enterprise and documents of the enterprise, wherein: the documents include data describing entities and entity facts related to the enterprise and relationships among the entities, and each document has a respective access control list specifying access privileges to the document for members of the enterprise; the entity facts are identified from the entities of the documents of the enterprise; each entity fact describes at least one feature of the entity, wherein the feature of the entity is a relationship between the entity and another entity and wherein each entity fact is derived from one or more corresponding documents in which the entity fact is described; and the index includes data defining access privileges to the data describing the entities and the entity facts according to respective entity fact access control lists, wherein each entity fact access control list is different from the access control lists provided for the documents of the enterprise, and each entity fact inherits an access control list of a document from which the entity fact is derived, wherein deriving the entity facts comprises selecting each document from the documents, and for the selected document: determining a first entity identified within the document; determining a second entity identified within the document; determining a relationship between the first entity and the second entity that is described within the document; and generating, as the entity fact, data describing the first entity, the second entity, and the relationship between the first entity and the second entity as described in the document; wherein multiple entity facts are derived from a selected document; determining the entity facts that are accessible to the member according to the entity fact access control lists; determining, based on member information of the member, and entity facts that are accessible to the member, search result data including data describing entities and entity facts relevant to the query; and providing search results, based on the search result data, to the member of the enterprise, the search results including data describing the entities and entity facts determined to be relevant to the query. | 9. A system, comprising: a processor; and a computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: receiving a query from a member of an enterprise; searching an index that includes member information of members of the enterprise and documents of the enterprise, wherein: the documents include data describing entities and entity facts related to the enterprise and relationships among the entities, and each document has a respective access control list specifying access privileges to the document for members of the enterprise; the entity facts are identified from the entities of the documents of the enterprise; each entity fact describes at least one feature of the entity, wherein the feature of the entity is a relationship between the entity and another entity and wherein each entity fact is derived from one or more corresponding documents in which the entity fact is described; and the index includes data defining access privileges to the data describing the entities and the entity facts according to respective entity fact access control lists, wherein each entity fact access control list is different from the access control lists provided for the documents of the enterprise, and each entity fact inherits an access control list of a document from which the entity fact is derived, wherein deriving the entity facts comprises selecting each document from the documents, and for the selected document: determining a first entity identified within the document; determining a second entity identified within the document; determining a relationship between the first entity and the second entity that is described within the document; and generating, as the entity fact, data describing the first entity, the second entity, and the relationship between the first entity and the second entity as described in the document; wherein multiple entity facts are derived from a selected document; determining the entity facts that are accessible to the member according to the entity fact access control lists; determining, based on member information of the member, and entity facts that are accessible to the member, search result data including data describing entities and entity facts relevant to the query; and providing search results, based on the search result data, to the member of the enterprise, the search results including data describing the entities and entity facts determined to be relevant to the query. 10. The system of claim 9 , wherein member information of the member includes at least one of the member's role in the enterprise, an organizational structure of the enterprise, the member's contacts, and the member's relationship with the provided query. | 0.694976 |
7,761,295 | 5 | 7 | 5. A system for transcribing testimonial proceedings, comprising: a transcription system in operative communication with a stenographic recorder, wherein the transcription system is configured to: receive, in real-time, one or more stenographic key-stroke codes from the stenographic recorder, wherein the one or more stenographic key-stroke codes represent words spoken during a testimonial proceeding; transcribe the one or more stenographic key-stroke codes into exact text that represents the words spoken during the testimonial proceeding; and replace the one or more stenographic key-stroke codes with phoneme text that represents the words spoken during the testimonial proceeding in response to failing to transcribe the stenographic key-stroke codes into the exact text; and a display device in operative communication with the transcription system, wherein the display device displays one or more of the exact text or the phoneme text that represents the words spoken during the testimonial proceeding. | 5. A system for transcribing testimonial proceedings, comprising: a transcription system in operative communication with a stenographic recorder, wherein the transcription system is configured to: receive, in real-time, one or more stenographic key-stroke codes from the stenographic recorder, wherein the one or more stenographic key-stroke codes represent words spoken during a testimonial proceeding; transcribe the one or more stenographic key-stroke codes into exact text that represents the words spoken during the testimonial proceeding; and replace the one or more stenographic key-stroke codes with phoneme text that represents the words spoken during the testimonial proceeding in response to failing to transcribe the stenographic key-stroke codes into the exact text; and a display device in operative communication with the transcription system, wherein the display device displays one or more of the exact text or the phoneme text that represents the words spoken during the testimonial proceeding. 7. The system of claim 5 , wherein the transcription system replaces the stenographic key-stroke codes with the phoneme text using a phoneme library that associates a plurality of stenographic key-stroke codes with phoneme text that represents a plurality of pronounceable strings. | 0.597421 |
10,115,041 | 14 | 19 | 14. A system, comprising: a data processing apparatus; and a memory apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving text captured from a rendered document during a text capture operation; receiving supplemental information including information relating to circumstances under which the text capture operation was performed, the information relating to circumstances under which the text capture operation was performed comprising a geographic location at which the text capture operation was performed to capture the text from the rendered document; determining, based on the supplemental information including the geographic location at which the text capture operation was performed to capture the text from the rendered document, an action to be performed on the captured text; and causing the action to be performed on the captured text. | 14. A system, comprising: a data processing apparatus; and a memory apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving text captured from a rendered document during a text capture operation; receiving supplemental information including information relating to circumstances under which the text capture operation was performed, the information relating to circumstances under which the text capture operation was performed comprising a geographic location at which the text capture operation was performed to capture the text from the rendered document; determining, based on the supplemental information including the geographic location at which the text capture operation was performed to capture the text from the rendered document, an action to be performed on the captured text; and causing the action to be performed on the captured text. 19. The system of claim 14 , wherein the information relating to the circumstances under which the text capture operation was performed comprises information describing an environment in which the text capture operation was performed. | 0.504237 |
7,706,016 | 9 | 10 | 9. An article of manufacture for viewing production data for a print job, the production data including (i) an electronic document defined by a page description language (PDL), the electronic document being stored in a PDL image file and having predefined physical dimensions, and (ii) a predetermined area in which the electronic document must fit in a layout of a physical printed document, the article of manufacture comprising a computer-readable medium encoded with computer-executable instructions for performing a method comprising: (a) creating an image display of a still image proxy of the PDL image file; (b) creating a static template that defines the predetermined area, wherein the physical dimensions of the template are dynamically determined based on the area in which the electronic document must fit in the layout of the physical printed document, and the physical dimensions of the image display of the still image proxy are dynamically determined based on the relative size of the predefined physical dimensions of the PDL image file to the predetermined area in which the electronic document must fit; and (c) displaying the image display of the still image proxy in association with the template. | 9. An article of manufacture for viewing production data for a print job, the production data including (i) an electronic document defined by a page description language (PDL), the electronic document being stored in a PDL image file and having predefined physical dimensions, and (ii) a predetermined area in which the electronic document must fit in a layout of a physical printed document, the article of manufacture comprising a computer-readable medium encoded with computer-executable instructions for performing a method comprising: (a) creating an image display of a still image proxy of the PDL image file; (b) creating a static template that defines the predetermined area, wherein the physical dimensions of the template are dynamically determined based on the area in which the electronic document must fit in the layout of the physical printed document, and the physical dimensions of the image display of the still image proxy are dynamically determined based on the relative size of the predefined physical dimensions of the PDL image file to the predetermined area in which the electronic document must fit; and (c) displaying the image display of the still image proxy in association with the template. 10. The article of manufacture of claim 9 wherein the electronic document is an advertisement and the template is the area of purchased advertisement space. | 0.886131 |
7,750,891 | 104 | 105 | 104. The system of claim 90 , further comprising: means for providing feedback to a user. | 104. The system of claim 90 , further comprising: means for providing feedback to a user. 105. The system of claim 104 , wherein the feedback comprises any of visual feedback and audio feedback. | 0.5 |
10,146,773 | 1 | 7 | 1. A method using one or more computer processors, comprising: providing, using the one or more computer processors, a first message in a first language to a first transformation module in a sequence of computer-implemented transformation modules, each transformation module comprising executable instructions configured to be executed by the one or more computer processors for performing message transformation operations, wherein each subsequent transformation module in the sequence accepts, as input, an output of a preceding transformation module in the sequence and provides, as output, a respective transformed message, wherein at least one transformation module in the sequence identifies at least a portion of the output of the at least one transformation module as not to be transformed by subsequent transformation modules in the sequence, and wherein the output of a final transformation module in the sequence comprises a transformed message in the first language; and querying, using the one or more computer processors, a computer data store for a translation of the transformed message in a second language. | 1. A method using one or more computer processors, comprising: providing, using the one or more computer processors, a first message in a first language to a first transformation module in a sequence of computer-implemented transformation modules, each transformation module comprising executable instructions configured to be executed by the one or more computer processors for performing message transformation operations, wherein each subsequent transformation module in the sequence accepts, as input, an output of a preceding transformation module in the sequence and provides, as output, a respective transformed message, wherein at least one transformation module in the sequence identifies at least a portion of the output of the at least one transformation module as not to be transformed by subsequent transformation modules in the sequence, and wherein the output of a final transformation module in the sequence comprises a transformed message in the first language; and querying, using the one or more computer processors, a computer data store for a translation of the transformed message in a second language. 7. The method of claim 1 , wherein one or more transformation modules (i) identify an acronym in the first message and (ii) replace the acronym with a word or a phrase corresponding to the acronym. | 0.599593 |
8,488,774 | 29 | 31 | 29. A system comprising: a real-time decision engine to receive information about a caller and identify a skill that is useful for providing service to the caller, the caller being associated with a plurality of parameters, the decision engine identifying the skill by predicting an action prior to caller input about the action, including generating scores for a plurality of statistical models, each statistical model representing a correlation between a subset of the plurality of parameters and an action that may be performed or requested to be performed by the caller, the score for each statistical model being generated using the statistical model and the subset of the plurality of parameters associated with the statistical model, the score for each statistical model providing information about a probability that the caller will perform an action associated with the statistical model or request the action to be performed, and identifying a skill based on the scores; a storage to store the statistical models; and a call router to route a call from the customer to a representative who has the skill. | 29. A system comprising: a real-time decision engine to receive information about a caller and identify a skill that is useful for providing service to the caller, the caller being associated with a plurality of parameters, the decision engine identifying the skill by predicting an action prior to caller input about the action, including generating scores for a plurality of statistical models, each statistical model representing a correlation between a subset of the plurality of parameters and an action that may be performed or requested to be performed by the caller, the score for each statistical model being generated using the statistical model and the subset of the plurality of parameters associated with the statistical model, the score for each statistical model providing information about a probability that the caller will perform an action associated with the statistical model or request the action to be performed, and identifying a skill based on the scores; a storage to store the statistical models; and a call router to route a call from the customer to a representative who has the skill. 31. The system of claim 29 , further comprising a storage to store a database having information about representatives and skills associated with the representatives. | 0.741433 |
8,776,009 | 8 | 11 | 8. A system for task modeling interactive sequential applications for one or more mobile devices, comprising: a) a central processing unit (CPU) having a software tool for defining a generic meta-model of the target applications, wherein said generic meta-model consists of a static model of application components, and a dynamic model of identifiers of application screens and connections that are based on an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models; b) a passive Task Model database, being in data communication with said CPU, for storing said generic meta-model for future reuse, which further comprises static instances of the generic meta-model specifically generated for a variety of mobile devices; c) a tracker module in said processing unit for: c1) real-time tracking and monitoring user's actions during user-system interactions and creating a screen unique identifier for each application's screen visited by the user of said mobile device by choosing an identifier that matches a signature of each application's screen, wherein created identifiers are used for generating active models of the user's actual usage; and c2) generating a unique identifier for each captured screen that is presented to said user; d) an active Task Model database, being in data communication with said processing unit, for storing said active model, wherein data transferring and storing is minimized to screen unique identifier and; e) an analyzer for comparing said active Task Model to said passive Task Model and for generating usage patterns for said user. | 8. A system for task modeling interactive sequential applications for one or more mobile devices, comprising: a) a central processing unit (CPU) having a software tool for defining a generic meta-model of the target applications, wherein said generic meta-model consists of a static model of application components, and a dynamic model of identifiers of application screens and connections that are based on an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models; b) a passive Task Model database, being in data communication with said CPU, for storing said generic meta-model for future reuse, which further comprises static instances of the generic meta-model specifically generated for a variety of mobile devices; c) a tracker module in said processing unit for: c1) real-time tracking and monitoring user's actions during user-system interactions and creating a screen unique identifier for each application's screen visited by the user of said mobile device by choosing an identifier that matches a signature of each application's screen, wherein created identifiers are used for generating active models of the user's actual usage; and c2) generating a unique identifier for each captured screen that is presented to said user; d) an active Task Model database, being in data communication with said processing unit, for storing said active model, wherein data transferring and storing is minimized to screen unique identifier and; e) an analyzer for comparing said active Task Model to said passive Task Model and for generating usage patterns for said user. 11. The system according to claim 8 , wherein the mobile device further comprises a real-time recommender engine, for offering the client real-time help, marketing and content determined by the provider. | 0.71727 |
9,881,002 | 19 | 24 | 19. One or more computer-readable storage devices for storing computer-executable instructions that, when executed by one or more computer systems, configure the one or more computer systems to perform operations, comprising: receiving an electronic content item including an identifying area; receiving a text string corresponding to the identifying area; receiving metadata indicating parameters of the identifying area; generating an asset identifier associating the electronic content item and the metadata; storing the electronic content item and the metadata in association with the asset identifier; receiving a translation corresponding to the text string, the translation based in part on a language code that comprises a regional identifier and a language identifier, the regional identifier indicating a particular geographic region and the language identifier indicating a particular language supported within the particular geographic region; providing a client device the electronic content item based in part on the asset identifier; and enabling the client device to display the electronic content item in accordance with the parameters, the electronic content item, when displayed, including the translation corresponding to the text string. | 19. One or more computer-readable storage devices for storing computer-executable instructions that, when executed by one or more computer systems, configure the one or more computer systems to perform operations, comprising: receiving an electronic content item including an identifying area; receiving a text string corresponding to the identifying area; receiving metadata indicating parameters of the identifying area; generating an asset identifier associating the electronic content item and the metadata; storing the electronic content item and the metadata in association with the asset identifier; receiving a translation corresponding to the text string, the translation based in part on a language code that comprises a regional identifier and a language identifier, the regional identifier indicating a particular geographic region and the language identifier indicating a particular language supported within the particular geographic region; providing a client device the electronic content item based in part on the asset identifier; and enabling the client device to display the electronic content item in accordance with the parameters, the electronic content item, when displayed, including the translation corresponding to the text string. 24. The one or more computer-readable storage devices of claim 19 , wherein the text string comprises a first language and the translation corresponding to the text string comprises a second language, the first language distinct from the second language. | 0.664908 |
8,671,109 | 7 | 8 | 7. The method defined in claim 4 , wherein the particular video frame in the reference video stream is divided into a plurality of regions and wherein said extracting at least one feature for each of a plurality of regions of the particular video frame in the reference video stream is carried out for less than all of the regions of the particular video frame in the reference video stream. | 7. The method defined in claim 4 , wherein the particular video frame in the reference video stream is divided into a plurality of regions and wherein said extracting at least one feature for each of a plurality of regions of the particular video frame in the reference video stream is carried out for less than all of the regions of the particular video frame in the reference video stream. 8. The method defined in claim 7 , wherein the particular video frame in the query video stream is divided into a plurality of regions and wherein said extracting at least one feature for each of a plurality of regions of the particular video frame in the query video stream is carried out for less than all of the regions of the particular video frame in the query video stream. | 0.5 |
9,489,944 | 1 | 2 | 1. An information processing device comprising: a memory controller to store in a memory: a plurality of character strings included in a voice text obtained by performing a voice recognition on voice data; a node index indicating start position information and end position information of each of the character strings in the voice text; a voice recognition score obtained by performing the voice recognition; and a voice index of voice position information indicating a position of each of the character strings in the voice data; a detector to detect reproduction section information which indicates a reproduced section of the voice data; an obtainer to obtain reading information, which represents at least a part of a character string representing reading of a phrase in a text written down from the voice data that has been reproduced, and obtain insertion position information, which indicates a character insertion position in the written text; a searcher to specify, as a target character string for searching, a character string that, from among the plurality of character strings stored in the memory, has the corresponding voice position information included in the reproduction section information, and search the specified character string for a character string that includes reading indicated by the reading information; a determiner to, when a value of the voice recognition score corresponding to the character string obtained by the searcher is equal to or greater than a display threshold value, determine to display the character string obtained by the searcher; a display controller to display the character string, which is determined by the determiner, on a display unit; a history updater to perform storage control to store, in a candidate history memory, candidate history data in which the character string obtained by the searcher, the voice recognition score, and the character insertion position are associated, and to update the candidate history data according to a change in a text; a selector to, when the character string displayed by the display controller is subjected to a selection operation, select the character string; and a threshold value updater to decide on the display threshold value, which is used in comparison with a voice recognition score by the determiner, using at least one of a voice recognition score of the candidate history data and a voice recognition score of the character string selected by the selector. | 1. An information processing device comprising: a memory controller to store in a memory: a plurality of character strings included in a voice text obtained by performing a voice recognition on voice data; a node index indicating start position information and end position information of each of the character strings in the voice text; a voice recognition score obtained by performing the voice recognition; and a voice index of voice position information indicating a position of each of the character strings in the voice data; a detector to detect reproduction section information which indicates a reproduced section of the voice data; an obtainer to obtain reading information, which represents at least a part of a character string representing reading of a phrase in a text written down from the voice data that has been reproduced, and obtain insertion position information, which indicates a character insertion position in the written text; a searcher to specify, as a target character string for searching, a character string that, from among the plurality of character strings stored in the memory, has the corresponding voice position information included in the reproduction section information, and search the specified character string for a character string that includes reading indicated by the reading information; a determiner to, when a value of the voice recognition score corresponding to the character string obtained by the searcher is equal to or greater than a display threshold value, determine to display the character string obtained by the searcher; a display controller to display the character string, which is determined by the determiner, on a display unit; a history updater to perform storage control to store, in a candidate history memory, candidate history data in which the character string obtained by the searcher, the voice recognition score, and the character insertion position are associated, and to update the candidate history data according to a change in a text; a selector to, when the character string displayed by the display controller is subjected to a selection operation, select the character string; and a threshold value updater to decide on the display threshold value, which is used in comparison with a voice recognition score by the determiner, using at least one of a voice recognition score of the candidate history data and a voice recognition score of the character string selected by the selector. 2. The device according to claim 1 , further comprising a follow-on searcher to search for a character string which, as a node index of a start position thereof, has a node index of an end position of the character string selected by the selector, wherein the display controller displays, on the display unit, the character string which is retrieved by the follow-on searcher. | 0.700159 |
6,151,570 | 2 | 22 | 2. A translating apparatus, comprising: input means for inputting a range to be translated in an original text; display means for displaying the original text; context process range setting means for setting a context process range in the original text; context processing means for performing a context process for the original text; and translation processing means for translating an original text in the range to be translated into translated text, based on a context in the context process range. | 2. A translating apparatus, comprising: input means for inputting a range to be translated in an original text; display means for displaying the original text; context process range setting means for setting a context process range in the original text; context processing means for performing a context process for the original text; and translation processing means for translating an original text in the range to be translated into translated text, based on a context in the context process range. 22. The translating apparatus according to claim 2, wherein: said context process range setting means comprises: boundary detecting means for detecting a boundary of context; and terminating means for terminating an extension of the context process range at the boundary, when said boundary detecting means detects the boundary of context. | 0.5 |
8,880,620 | 12 | 15 | 12. A computer-implemented data delivery method, comprising: tagging message contacts of a recipient with social relationship tags according to types of social relationships; categorizing and adding the tagged message contacts and the types of the social relationships into a social graph, for the recipient, of social relationship categories; the social graph comprising an entry for each added tagged message contact, each entry comprising a link to the added tagged message contact and at least one social relationship tag; accessing external sources of information related to the tagged message contacts using delegated authentication codes or password authorization; importing the information related to the tagged message contacts from the external sources to augment the social graph; receiving messages from the message contacts; accessing the social graph; managing, by a processor, a flow of the messages received from the message contacts by the recipient based on respective social relationship categories of the social graph; blocking, at a perimeter of an email deployment, messages from unwanted senders from passing into internal message servers; and passing, from the perimeter of the email deployment to the internal message servers for routing, messages from acceptable users in accordance with the social graph. | 12. A computer-implemented data delivery method, comprising: tagging message contacts of a recipient with social relationship tags according to types of social relationships; categorizing and adding the tagged message contacts and the types of the social relationships into a social graph, for the recipient, of social relationship categories; the social graph comprising an entry for each added tagged message contact, each entry comprising a link to the added tagged message contact and at least one social relationship tag; accessing external sources of information related to the tagged message contacts using delegated authentication codes or password authorization; importing the information related to the tagged message contacts from the external sources to augment the social graph; receiving messages from the message contacts; accessing the social graph; managing, by a processor, a flow of the messages received from the message contacts by the recipient based on respective social relationship categories of the social graph; blocking, at a perimeter of an email deployment, messages from unwanted senders from passing into internal message servers; and passing, from the perimeter of the email deployment to the internal message servers for routing, messages from acceptable users in accordance with the social graph. 15. The method of claim 12 , further comprising enabling a third party to manage the social graph. | 0.727778 |
8,903,802 | 1 | 10 | 1. A method for managing a new continuous query that includes folding a new continuous query into a shared continuous query plan (SCP) associated with a global range table, the method comprising: receiving via a computer readable storage medium a new continuous query; compiling the new continuous query to generate an iterator model plan (IMP) and an associated local range table that includes a list of range variables, each of which uniquely identifies an object in the new continuous query, and wherein the IMP corresponds to an execution plan generated for the new continuous query and comprises one or more IMP operators, each of which includes one or more expressions whose variables are associated with the local range table; analyzing the one or more IMP operators of the IMP and one or more SCP operators of the SCP to produce one or more variable transforms and one or more plan items; wherein the one or more variable transforms modify the one or more expressions of the one or more IMP operators by associating the one or more IMP operators with variables of a global range table; wherein the one or more plan items comprise one or more groups of the one or more IMP operators; applying the variable transforms to modify the variables of the one or more iterator model plan IMP operators; generating a continuous query operator based on each plan item included in the one or more plan items; and providing the generated continuous query operator to a shared continuous query plan. | 1. A method for managing a new continuous query that includes folding a new continuous query into a shared continuous query plan (SCP) associated with a global range table, the method comprising: receiving via a computer readable storage medium a new continuous query; compiling the new continuous query to generate an iterator model plan (IMP) and an associated local range table that includes a list of range variables, each of which uniquely identifies an object in the new continuous query, and wherein the IMP corresponds to an execution plan generated for the new continuous query and comprises one or more IMP operators, each of which includes one or more expressions whose variables are associated with the local range table; analyzing the one or more IMP operators of the IMP and one or more SCP operators of the SCP to produce one or more variable transforms and one or more plan items; wherein the one or more variable transforms modify the one or more expressions of the one or more IMP operators by associating the one or more IMP operators with variables of a global range table; wherein the one or more plan items comprise one or more groups of the one or more IMP operators; applying the variable transforms to modify the variables of the one or more iterator model plan IMP operators; generating a continuous query operator based on each plan item included in the one or more plan items; and providing the generated continuous query operator to a shared continuous query plan. 10. The method according to claim 1 , further comprising applying each variable transform to operators in an iterator model plan sub-plan by evaluating the produced instructions. | 0.600897 |
8,290,777 | 1 | 10 | 1. A method for synchronizing the playing and displaying of digital content in an electronic device, comprising: inserting bookmarks into a segment of digital content that is to be played by a text-to-speech engine, wherein each bookmark is associated with a particular position in the digital content; rendering a first portion of digital content for display on the electronic device; displaying the rendered first portion of digital content on the electronic device; determining a position of a last word in the rendered first portion of digital content; playing the segment of digital content as audio using the text-to-speech engine; processing the bookmarks as the segment of digital content is being played; comparing a current bookmark with the position of the last word in the rendered first portion of digital content; and rendering a second portion of digital content for display when the current bookmark is greater than the position of the last word in the rendered first portion of digital content. | 1. A method for synchronizing the playing and displaying of digital content in an electronic device, comprising: inserting bookmarks into a segment of digital content that is to be played by a text-to-speech engine, wherein each bookmark is associated with a particular position in the digital content; rendering a first portion of digital content for display on the electronic device; displaying the rendered first portion of digital content on the electronic device; determining a position of a last word in the rendered first portion of digital content; playing the segment of digital content as audio using the text-to-speech engine; processing the bookmarks as the segment of digital content is being played; comparing a current bookmark with the position of the last word in the rendered first portion of digital content; and rendering a second portion of digital content for display when the current bookmark is greater than the position of the last word in the rendered first portion of digital content. 10. The method of claim 1 , wherein the electronic device comprises an electronic book (eBook) reader, and wherein the digital content comprises an eBook. | 0.809877 |
10,007,882 | 2 | 6 | 2. The system of claim 1 , wherein said query document and said plurality of additional documents are each associated with a maximum number of most relevant concept vectors M such that the proximity of each document belonging to said plurality of additional documents to said query document is determined by the degree of overlapping of said maximum number of most relevant concept vectors M such that said output module enables displaying said at least a subset of said plurality of said additional documents based, at least in part, on said degree of overlapping. | 2. The system of claim 1 , wherein said query document and said plurality of additional documents are each associated with a maximum number of most relevant concept vectors M such that the proximity of each document belonging to said plurality of additional documents to said query document is determined by the degree of overlapping of said maximum number of most relevant concept vectors M such that said output module enables displaying said at least a subset of said plurality of said additional documents based, at least in part, on said degree of overlapping. 6. The system of claim 2 , wherein said predetermined threshold C is dependant from said technology class of documents. | 0.816923 |
8,682,832 | 17 | 18 | 17. A programmable device comprising: a processing unit; a computer readable memory in communication with the processing unit; a tangible computer-readable storage medium in communication with the processing unit; and a network interface in communication with the processing unit and a virtual universe environment; wherein the processing unit, when executing program instructions stored on the tangible computer-readable storage medium via the computer readable memory, is caused to: monitor a behavior of a collective plurality of avatars within a virtual universe environment for compliance with a violation threshold of an avatar behavior rule for the virtual universe environment, and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment; determine an amount of compliance of the monitored collective plurality behavior with the rule; compare the determined compliance amount with the violation threshold; if the determined compliance amount does not exceed the violation threshold and any of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment, revise the violation threshold downward, wherein a lower level of the determined compliance amount is required to exceed the violation threshold; and repetitively monitor the behavior of the collective plurality of avatars within the virtual universe environment for compliance with the rule and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment, determine an amount of compliance of the monitored collective plurality behavior with the rule, compare the determined compliance amount with the revised violation threshold, and revise the violation threshold downward, until the monitored compliance amount exceeds the revised violation threshold or none of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment. | 17. A programmable device comprising: a processing unit; a computer readable memory in communication with the processing unit; a tangible computer-readable storage medium in communication with the processing unit; and a network interface in communication with the processing unit and a virtual universe environment; wherein the processing unit, when executing program instructions stored on the tangible computer-readable storage medium via the computer readable memory, is caused to: monitor a behavior of a collective plurality of avatars within a virtual universe environment for compliance with a violation threshold of an avatar behavior rule for the virtual universe environment, and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment; determine an amount of compliance of the monitored collective plurality behavior with the rule; compare the determined compliance amount with the violation threshold; if the determined compliance amount does not exceed the violation threshold and any of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment, revise the violation threshold downward, wherein a lower level of the determined compliance amount is required to exceed the violation threshold; and repetitively monitor the behavior of the collective plurality of avatars within the virtual universe environment for compliance with the rule and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment, determine an amount of compliance of the monitored collective plurality behavior with the rule, compare the determined compliance amount with the revised violation threshold, and revise the violation threshold downward, until the monitored compliance amount exceeds the revised violation threshold or none of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment. 18. The programmable device of claim 17 , wherein the processing unit, when executing the program instructions stored on the tangible computer-readable storage medium via the computer readable memory, is further caused to: determine an average level of compliance of the collective plurality of avatars from determined amounts of compliance of each of the collective plurality of avatars; and define the violation threshold of the avatar behavior rule as the determined average level of compliance. | 0.5 |
7,657,544 | 4 | 5 | 4. A method for presenting information of document files, the document files being stored on a document database where the document files are categorized and stored into any of predefined category bins, the method comprising: selecting at least some of document files stored on the document database and categorized in object category bins as representative document files for each of the object category bins, the document files being selected as representative document files based on similarity to a document file to be categorized, the object category bins being at least part of the category bins, the representative document files comprising a proper subset of the document files categorized in each respective object category bin associated with the representative document files; presenting information extracted from the selected representative document files to a user when the user queries contents of an object category bin of the object category bins without entering the object category bin; presenting a guide caption describing keywords extracted from a file and obtained by a document summarizing process; and increasing a highlight contrast to a background for guide captions of files having greater weights regarding access histories. | 4. A method for presenting information of document files, the document files being stored on a document database where the document files are categorized and stored into any of predefined category bins, the method comprising: selecting at least some of document files stored on the document database and categorized in object category bins as representative document files for each of the object category bins, the document files being selected as representative document files based on similarity to a document file to be categorized, the object category bins being at least part of the category bins, the representative document files comprising a proper subset of the document files categorized in each respective object category bin associated with the representative document files; presenting information extracted from the selected representative document files to a user when the user queries contents of an object category bin of the object category bins without entering the object category bin; presenting a guide caption describing keywords extracted from a file and obtained by a document summarizing process; and increasing a highlight contrast to a background for guide captions of files having greater weights regarding access histories. 5. The method for presenting information of a document file according to claim 4 , wherein the representative document files for each of the object category bins are selected based on access histories of the document files categorized in the object category bins. | 0.5 |
7,536,475 | 15 | 21 | 15. The ACM system in accordance with claim 14 wherein said web server configured to receive SOAP/XML requests from said network and transfer the SOAP/XML requests to said SOAP/XML server. | 15. The ACM system in accordance with claim 14 wherein said web server configured to receive SOAP/XML requests from said network and transfer the SOAP/XML requests to said SOAP/XML server. 21. The ACM system in accordance with claim 15 wherein said SOAP/XML and web server system further comprises a network interface electrically coupled to said network and said web server, said network interface configured to facilitate communication between said web server and said network. | 0.5 |
9,286,886 | 11 | 13 | 11. The method of claim 10 , wherein the comparing further comprises: analyzing the input text to identify a sequence of markers in the input text; and selecting the sequence of corresponding text fragments from one or more candidate sequences matching the sequence of markers. | 11. The method of claim 10 , wherein the comparing further comprises: analyzing the input text to identify a sequence of markers in the input text; and selecting the sequence of corresponding text fragments from one or more candidate sequences matching the sequence of markers. 13. The method of claim 11 , wherein the comparing further comprises: computing a join cost for each of the one or more candidate sequences; and selecting the sequence of corresponding text fragments from the one or more candidate sequences based at least in part on the join cost. | 0.5 |
9,639,630 | 7 | 9 | 7. A method for business intelligence data integration, comprising the steps of: (a) receiving an SQL query from a client device at a query transformation server comprising at least a plurality of programming instructions stored in a memory and operating on a processor of a network-connected computing device and configured to connect to a plurality of business intelligence engine web services via a network; (b) applying a plurality of transformations to the SQL query including at least removal of a visualization-specific column from the SQL query; embedding the SQL query into an XML web services request using the query transformation server; (c) providing at least a portion of the XML web services request to a business intelligence engine web service; (d) receiving an XML response from the business intelligence engine web service to the query transformation server; (e) applying a plurality of modifications to at least a portion of the XML response including extracting SQL from the XML and reattaching the visualization-specific column to generate a complete SQL response using the query transformation server and providing the SQL response to the client device; (f) applying a plurality of transformations to at least a portion of the query; (g) transmitting at least a portion of the transformed query to a business intelligence engine web service; (h) receiving a response from the business intelligence engine; and (i) providing at least a portion of the response to the client device. | 7. A method for business intelligence data integration, comprising the steps of: (a) receiving an SQL query from a client device at a query transformation server comprising at least a plurality of programming instructions stored in a memory and operating on a processor of a network-connected computing device and configured to connect to a plurality of business intelligence engine web services via a network; (b) applying a plurality of transformations to the SQL query including at least removal of a visualization-specific column from the SQL query; embedding the SQL query into an XML web services request using the query transformation server; (c) providing at least a portion of the XML web services request to a business intelligence engine web service; (d) receiving an XML response from the business intelligence engine web service to the query transformation server; (e) applying a plurality of modifications to at least a portion of the XML response including extracting SQL from the XML and reattaching the visualization-specific column to generate a complete SQL response using the query transformation server and providing the SQL response to the client device; (f) applying a plurality of transformations to at least a portion of the query; (g) transmitting at least a portion of the transformed query to a business intelligence engine web service; (h) receiving a response from the business intelligence engine; and (i) providing at least a portion of the response to the client device. 9. The method of claim 7 , wherein the plurality of transformations comprises at least dividing the query into portions. | 0.736842 |
9,472,207 | 14 | 17 | 14. The apparatus of claim 13 , wherein the wearable device is worn by the second person having an autism spectrum disorder. | 14. The apparatus of claim 13 , wherein the wearable device is worn by the second person having an autism spectrum disorder. 17. The apparatus of claim 14 , wherein the outputting comprises an output on a display of the wearable device. | 0.716837 |
7,756,256 | 17 | 19 | 17. A computer readable medium including at least computer program code for providing unified messaging services in a computing environment that includes a plurality of message types, said method comprising: computer program code for providing a unified message that can represent a plurality of message types; computer program code for providing one or more features associated with said unified message; computer program code for receiving a selection that identifies a first selected feature of said one or more features; computer program code for determining, based on said first selected feature, if each one of said plurality of message types should be used for said unified message; and computer program code for transforming said unified message into a first message type of said plurality of message types when said determining determines that said first message type can be used. | 17. A computer readable medium including at least computer program code for providing unified messaging services in a computing environment that includes a plurality of message types, said method comprising: computer program code for providing a unified message that can represent a plurality of message types; computer program code for providing one or more features associated with said unified message; computer program code for receiving a selection that identifies a first selected feature of said one or more features; computer program code for determining, based on said first selected feature, if each one of said plurality of message types should be used for said unified message; and computer program code for transforming said unified message into a first message type of said plurality of message types when said determining determines that said first message type can be used. 19. A computer readable medium as recited in claim 17 , wherein said computer readable medium further comprises: providing one or more states for each one of said one or more features associated with said unified message. | 0.762876 |
9,036,701 | 8 | 9 | 8. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: determine a frequency of occurrence threshold based on an expected frequency of occurrence of syntax elements in a bit stream; categorize a plurality of syntax elements of video content into first and second categories based on the frequency of occurrence threshold, wherein syntax elements which occur greater than the frequency of occurrence threshold are categorized into the first category and syntax elements which occur less than the frequency of occurrence are categorized into the second category; entropy code symbols that correspond to the first category of syntax elements and that have been subjected to a context update; and entropy code symbols that correspond to the second category of syntax elements and that have bypassed context updating. | 8. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: determine a frequency of occurrence threshold based on an expected frequency of occurrence of syntax elements in a bit stream; categorize a plurality of syntax elements of video content into first and second categories based on the frequency of occurrence threshold, wherein syntax elements which occur greater than the frequency of occurrence threshold are categorized into the first category and syntax elements which occur less than the frequency of occurrence are categorized into the second category; entropy code symbols that correspond to the first category of syntax elements and that have been subjected to a context update; and entropy code symbols that correspond to the second category of syntax elements and that have bypassed context updating. 9. An apparatus according to claim 8 wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to cause a categorization of the syntax elements to be signaled at a block, slice, picture or sequence level. | 0.616992 |
9,152,678 | 11 | 19 | 11. A system comprising at least one: data processing apparatus programmed to perform operations comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; receiving the query from a user during a second time period that chronologically follows the plurality of time periods; obtaining search results responsive to the query; adjusting a ranking of the first search result in the obtained search results during the second time period; and providing the search results including the adjusted ranking of the first search result to the user. | 11. A system comprising at least one: data processing apparatus programmed to perform operations comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; receiving the query from a user during a second time period that chronologically follows the plurality of time periods; obtaining search results responsive to the query; adjusting a ranking of the first search result in the obtained search results during the second time period; and providing the search results including the adjusted ranking of the first search result to the user. 19. The system of claim 11 , wherein the minimum change threshold is a standard deviation of the calculated click-fractions. | 0.804416 |
8,503,715 | 14 | 15 | 14. A system comprising: a script detection service implemented by at least one computing device, the script detection service configured to: identify values representing individual text characters in a string of one or more text characters to determine which human writing system is associated with the individual text characters; compare the values to a table that associates subsets of values with individual human writing systems; determine that the values representing the individual text characters are within a particular subset of values in the table that correspond to a particular said human writing system; and designate that the particular said human writing system is associated with the string based on the values associated with the individual text characters being within the particular subset of values that corresponds with the particular said human writing system. | 14. A system comprising: a script detection service implemented by at least one computing device, the script detection service configured to: identify values representing individual text characters in a string of one or more text characters to determine which human writing system is associated with the individual text characters; compare the values to a table that associates subsets of values with individual human writing systems; determine that the values representing the individual text characters are within a particular subset of values in the table that correspond to a particular said human writing system; and designate that the particular said human writing system is associated with the string based on the values associated with the individual text characters being within the particular subset of values that corresponds with the particular said human writing system. 15. The system of claim 14 , wherein the script detection service is further configured to: indicate a range of positions in a text for the one or more text characters; and form a communication that associates the particular said human writing system with the range of positions. | 0.5 |
9,251,246 | 1 | 2 | 1. A processor-implemented method of defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the processor-implemented method comprising: receiving, by a processor, a data stream of non-contextual data objects, wherein each of the non-contextual data objects is a numerical value that ambiguously relates to multiple subject-matters; associating, by the processor, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving, by the processor, a data stream of non-dimensional data objects; applying, by the processor, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing, by the processor, the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects and a probability that one of the non-dimensional data objects has been associated with a correct dimensional label; parsing, by the processor, the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects and a probability that a non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating, by the processor, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting, by the processor, multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining, by the processor, multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. | 1. A processor-implemented method of defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the processor-implemented method comprising: receiving, by a processor, a data stream of non-contextual data objects, wherein each of the non-contextual data objects is a numerical value that ambiguously relates to multiple subject-matters; associating, by the processor, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving, by the processor, a data stream of non-dimensional data objects; applying, by the processor, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing, by the processor, the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects and a probability that one of the non-dimensional data objects has been associated with a correct dimensional label; parsing, by the processor, the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects and a probability that a non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating, by the processor, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting, by the processor, multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining, by the processor, multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. 2. The processor-implemented method of claim 1 , further comprising: graphically displaying the multiple context-based conformed dimensional data gravity wells according to a combined virtual mass of the multiple parsed synthetic context-based objects and the multiple parsed conformed dimensional objects, wherein a first context-based conformed dimensional data gravity well holds a more virtually massive combination of parsed data objects than a second context-based conformed dimensional data gravity well, and wherein the first context-based conformed dimensional data gravity well extends farther away from the context-based conformed dimensional data gravity wells membrane than the second context-based conformed dimensional data gravity well. | 0.758355 |
9,520,126 | 11 | 12 | 11. The system of claim 10 , wherein the mobile terminal includes: a general domain search space database storing a general domain search space based on general knowledge information of which a category is not specified; a specific domain search space database storing a specific domain search space based on knowledge information in a specific category; and a voice recognition engine performing the voice recognition of the voice recognition target word through linkage of the general domain search space database and the specific domain search space database. | 11. The system of claim 10 , wherein the mobile terminal includes: a general domain search space database storing a general domain search space based on general knowledge information of which a category is not specified; a specific domain search space database storing a specific domain search space based on knowledge information in a specific category; and a voice recognition engine performing the voice recognition of the voice recognition target word through linkage of the general domain search space database and the specific domain search space database. 12. The system of claim 11 , wherein the voice recognition server includes: a general domain search space creation unit creating the general domain search space; and a specific domain search space creation unit creating the specific domain search space. | 0.5 |
10,163,144 | 6 | 11 | 6. A computer-implemented method, comprising: receiving, by a computing device, unstructured item information associated with a plurality of items; providing a network page for displaying at least some of the unstructured item information associated with the plurality of items, the network page configured to be displayed by the computing device; converting the unstructured item information to an attribute, comprising: parsing the unstructured item information to determine a textual description, comparing the textual description with a dictionary of values and units of measurements, and determining the attribute based at least in part on matching the textual description with at least one entry of the dictionary, the attribute identified based at least in part on unit information included in the dictionary; determining a grouping, by the computing device, of the plurality of items by the attribute to form a first cluster and a second cluster; storing the attribute as structured data in a data store; determining a number of clusters that correspond with different measurement values of the unit of measurement, the clusters for an item including at least the first cluster and the second cluster; comparing the number of clusters for the item with an exclusion rate, the exclusion rate configured to enable confirmation of a second number of common attributes in the plurality of items; merging the first cluster and the second cluster that correspond with the unit of measurement into a merged cluster; and providing, on the network page enabled to be displayed by the computing device, an identifying user interface element of the merged cluster that includes at least the unit of measurement of the merged cluster, wherein the merged cluster includes at least one item associated with the first cluster and the second cluster. | 6. A computer-implemented method, comprising: receiving, by a computing device, unstructured item information associated with a plurality of items; providing a network page for displaying at least some of the unstructured item information associated with the plurality of items, the network page configured to be displayed by the computing device; converting the unstructured item information to an attribute, comprising: parsing the unstructured item information to determine a textual description, comparing the textual description with a dictionary of values and units of measurements, and determining the attribute based at least in part on matching the textual description with at least one entry of the dictionary, the attribute identified based at least in part on unit information included in the dictionary; determining a grouping, by the computing device, of the plurality of items by the attribute to form a first cluster and a second cluster; storing the attribute as structured data in a data store; determining a number of clusters that correspond with different measurement values of the unit of measurement, the clusters for an item including at least the first cluster and the second cluster; comparing the number of clusters for the item with an exclusion rate, the exclusion rate configured to enable confirmation of a second number of common attributes in the plurality of items; merging the first cluster and the second cluster that correspond with the unit of measurement into a merged cluster; and providing, on the network page enabled to be displayed by the computing device, an identifying user interface element of the merged cluster that includes at least the unit of measurement of the merged cluster, wherein the merged cluster includes at least one item associated with the first cluster and the second cluster. 11. The computer-implemented method of claim 6 , further comprising: comparing one or more clusters with a distribution kernel distance; and removing the one or more clusters from the network page in response to the comparison. | 0.624172 |
8,422,787 | 2 | 7 | 2. The text segmentation apparatus according to claim 1 , wherein the model base topic segmentation section outputs a segmentation confidence representing the degree of certainty of the segmentation of the text to at least one interval obtained on segmentation of the text in association with a topic, the parameter estimation section estimating the parameter used by the change point detection topic segmentation section, in an interval of a higher segmentation confidence, using the result of segmentation by the model base topic segmentation section as training data. | 2. The text segmentation apparatus according to claim 1 , wherein the model base topic segmentation section outputs a segmentation confidence representing the degree of certainty of the segmentation of the text to at least one interval obtained on segmentation of the text in association with a topic, the parameter estimation section estimating the parameter used by the change point detection topic segmentation section, in an interval of a higher segmentation confidence, using the result of segmentation by the model base topic segmentation section as training data. 7. The text segmentation apparatus according to claim 2 , wherein the model base topic segmentation section computes the segmentation confidence for at least one interval obtained on segmenting the text in association with the topic by a likelihood of the topic model or an entropy of an a posteriori probability of the topic model. | 0.664646 |
9,087,236 | 17 | 18 | 17. A computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code configured to: receive one or more documents that contain a first flow diagram in one or more diagram formats supported by the documents; automatically extract from the first flow diagram one or more flow graphs comprising extracted nodes and edges; automatically extract from the first flow diagram relational, geometric and textual features for the extracted nodes and edges; automatically learning rules to recognize process semantics based on the relational, geometric and textual features of the extracted nodes and edges, the rules configured as a decision tree; and automatically generate, based on the learned rules, process modeling recognition code to recognize and decide process semantics in a second flow diagram. | 17. A computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code configured to: receive one or more documents that contain a first flow diagram in one or more diagram formats supported by the documents; automatically extract from the first flow diagram one or more flow graphs comprising extracted nodes and edges; automatically extract from the first flow diagram relational, geometric and textual features for the extracted nodes and edges; automatically learning rules to recognize process semantics based on the relational, geometric and textual features of the extracted nodes and edges, the rules configured as a decision tree; and automatically generate, based on the learned rules, process modeling recognition code to recognize and decide process semantics in a second flow diagram. 18. The computer program product of claim 17 , wherein recognition of process semantics is further based on a measured similarity of the relational, geometric and textual features of the extracted nodes and edges. | 0.789109 |
6,047,300 | 19 | 22 | 19. A computer-readable medium having computer executable instructions for automatically detecting and correcting a spelling error using a plurality of difference criteria comprising the steps of: receiving a word; determining whether the word is misspelled; if the word is misspelled, then receiving a plurality of selected alternate words; for each of the difference criteria, repeating the steps of: (i) comparing the word and the selected alternate words; (ii) for each selected alternate word, if the word and the selected alternate word differ according to the difference criterion then (a) identifying the selected alternate word as a replacement candidate word for the difference criterion; and (b) setting one of a plurality of replacement indicators indicating that the difference criterion has identified the replacement candidate word; if the replacement indicators satisfy a set of selection criteria then selecting one of the replacement candidate words as a replacement word; and replacing the word with the replacement word. | 19. A computer-readable medium having computer executable instructions for automatically detecting and correcting a spelling error using a plurality of difference criteria comprising the steps of: receiving a word; determining whether the word is misspelled; if the word is misspelled, then receiving a plurality of selected alternate words; for each of the difference criteria, repeating the steps of: (i) comparing the word and the selected alternate words; (ii) for each selected alternate word, if the word and the selected alternate word differ according to the difference criterion then (a) identifying the selected alternate word as a replacement candidate word for the difference criterion; and (b) setting one of a plurality of replacement indicators indicating that the difference criterion has identified the replacement candidate word; if the replacement indicators satisfy a set of selection criteria then selecting one of the replacement candidate words as a replacement word; and replacing the word with the replacement word. 22. The computer-readable medium of claim 19, further comprising: maintaining a correction list comprising a plurality of corrected word pairs by adding the word and the replacement word to the correction list as a corrected word pair if the word is replaced by the replacement word. | 0.613388 |
6,115,709 | 1 | 29 | 1. A computer-implemented method of constructing a user knowledge profile, the method including: automatically assigning a confidence level to content within an electronic document associated with a first user, the content being potentially indicative of a user knowledge base of the first user; and storing the content in either a first or a second portion of a user knowledge profile of the first user according to the assigned confidence level, wherein the first and the second portions of the user knowledge profile of the first user have different access restrictions with respect to a second user. | 1. A computer-implemented method of constructing a user knowledge profile, the method including: automatically assigning a confidence level to content within an electronic document associated with a first user, the content being potentially indicative of a user knowledge base of the first user; and storing the content in either a first or a second portion of a user knowledge profile of the first user according to the assigned confidence level, wherein the first and the second portions of the user knowledge profile of the first user have different access restrictions with respect to a second user. 29. The method of claim 1 wherein the electronic document comprises an electronic mail message generated by the first user. | 0.75498 |
8,010,526 | 12 | 17 | 12. A method comprising: monitoring entity instances during a first interval, each entity instance being one of a plurality of types of entity instances; determining from the entity instances monitored during the first interval a first ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval, the first ranked list having a first cardinality of types of entity instances; monitoring entity instances during a second interval, each entity instance being one of the plurality of types of entity instances; determining from the entity instances monitored during the second interval a second ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the second interval, the second ranked list having the first cardinality of types of entity instances; and merging the first ranked list and the second ranked list into a third ranked list of entities instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval and the second interval; wherein monitoring entity instances during a first interval comprises: entering monitored entity instances in a first table; determining if an entity instance in the first table has a count that is greater than a threshold count; entering the entity instance in a second table if the entity instance in the first table has a count that is greater than the threshold count; determining if the second table has the first cardinality of entries; and ending the first interval if the second table has the first cardinality of entries. | 12. A method comprising: monitoring entity instances during a first interval, each entity instance being one of a plurality of types of entity instances; determining from the entity instances monitored during the first interval a first ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval, the first ranked list having a first cardinality of types of entity instances; monitoring entity instances during a second interval, each entity instance being one of the plurality of types of entity instances; determining from the entity instances monitored during the second interval a second ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the second interval, the second ranked list having the first cardinality of types of entity instances; and merging the first ranked list and the second ranked list into a third ranked list of entities instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval and the second interval; wherein monitoring entity instances during a first interval comprises: entering monitored entity instances in a first table; determining if an entity instance in the first table has a count that is greater than a threshold count; entering the entity instance in a second table if the entity instance in the first table has a count that is greater than the threshold count; determining if the second table has the first cardinality of entries; and ending the first interval if the second table has the first cardinality of entries. 17. The method of claim 12 , wherein the third ranked list has a second cardinality that is less than or equal to the first cardinality. | 0.895223 |
7,974,974 | 13 | 16 | 13. An apparatus, comprising: at least one processor for executing computer readable instructions; at least one computer readable storage medium storing the computer readable instructions that when executed by the at least one processor provide: an enhanced search component operative to receive a search query and provide a ranked search results responsive to the search query, the enhanced search component comprising: a resource search module operative to search for resources using a number of search terms from the search query, and output a set of resources having some or all of the search terms; a proximity generation module communicatively coupled to the resource search module, the proximity generation module operative to receive the set of resources, retrieve search term position information for each resource, and generate a proximity feature value based on the search term position information using an unordered cost function, wherein the unordered cost function does not require search terms to be in the same order as in the search query and wherein the unordered cost function is proportional to a number of different search terms in a chunk of the resource and inversely proportional to a length of the chunk and the number of search terms in the search query; and a resource ranking module communicatively coupled to the resource search module and the proximity generation module, the resource ranking module to receive the proximity feature values, and rank the resources based in part on the proximity feature values. | 13. An apparatus, comprising: at least one processor for executing computer readable instructions; at least one computer readable storage medium storing the computer readable instructions that when executed by the at least one processor provide: an enhanced search component operative to receive a search query and provide a ranked search results responsive to the search query, the enhanced search component comprising: a resource search module operative to search for resources using a number of search terms from the search query, and output a set of resources having some or all of the search terms; a proximity generation module communicatively coupled to the resource search module, the proximity generation module operative to receive the set of resources, retrieve search term position information for each resource, and generate a proximity feature value based on the search term position information using an unordered cost function, wherein the unordered cost function does not require search terms to be in the same order as in the search query and wherein the unordered cost function is proportional to a number of different search terms in a chunk of the resource and inversely proportional to a length of the chunk and the number of search terms in the search query; and a resource ranking module communicatively coupled to the resource search module and the proximity generation module, the resource ranking module to receive the proximity feature values, and rank the resources based in part on the proximity feature values. 16. The apparatus of claim 13 , the resource ranking module operative to rank the resources using multiple ranking algorithms, the first ranking algorithm to rank the resources using a first set of ranking criteria to form a first set of ranked resources, and the second ranking algorithm to rank a subset of the first set of ranked resources using a second set of ranking criteria including the proximity feature values to form a second set of ranked resources. | 0.5 |
10,067,876 | 23 | 24 | 23. A non-transitory computer-readable medium comprising instructions, execution of which in a computer system causes the computer system to: in response to a search query, copy a first bucket from remote storage to a cache, the first bucket including first data associated with the search query; identify a first file type associated with a first file in the first bucket, wherein the first file is associated with a first usage status; access, based on the search query, a second bucket from the remote storage, the second bucket including second data associated with the search query; identify a second file in the second bucket having the first file type; and copy, in response to the first usage status indicating that the first file was used in processing the search query, the second file from the remote storage to the cache. | 23. A non-transitory computer-readable medium comprising instructions, execution of which in a computer system causes the computer system to: in response to a search query, copy a first bucket from remote storage to a cache, the first bucket including first data associated with the search query; identify a first file type associated with a first file in the first bucket, wherein the first file is associated with a first usage status; access, based on the search query, a second bucket from the remote storage, the second bucket including second data associated with the search query; identify a second file in the second bucket having the first file type; and copy, in response to the first usage status indicating that the first file was used in processing the search query, the second file from the remote storage to the cache. 24. The non-transitory computer-readable medium of claim 23 , wherein the instructions, upon execution, further cause the computer system to: identify a second file type associated with a third file in the first bucket; identify a fourth file in the second bucket having the second file type; and make a first determination whether to copy the fourth file based on a second usage status of the third file, wherein the second usage status indicates whether the third file was used during the processing of the search query. | 0.754468 |
7,680,764 | 10 | 13 | 10. The method of claim 6 , further comprising: calling a first index entry generation function with first information utilizing a first cursor instance; and calling a second index entry generation function with second information utilizes a second cursor instance. | 10. The method of claim 6 , further comprising: calling a first index entry generation function with first information utilizing a first cursor instance; and calling a second index entry generation function with second information utilizes a second cursor instance. 13. The method of claim 10 , wherein calling said index entry generation function includes calling said index entry generation function using a cursor type of interface with said first XML document and said index entry generation function. | 0.512245 |
7,840,905 | 29 | 31 | 29. A system comprising: at least one processor; and a storage storing: a menu theme library comprising a menu theme template that includes a set of objects for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein properties for the set of objects are defined in a menu theme description file; a set of modules identified by a set of paths for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; and a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu. | 29. A system comprising: at least one processor; and a storage storing: a menu theme library comprising a menu theme template that includes a set of objects for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein properties for the set of objects are defined in a menu theme description file; a set of modules identified by a set of paths for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; and a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu. 31. The system of claim 29 , wherein the rendered drop zone area object in the menu theme template comprises an area for displaying the content that is dropped into the drop zone area object. | 0.577434 |
8,938,403 | 8 | 11 | 8. A system configured to compute token-dependent affective response baseline levels for a user, comprising: a database comprising first, second, and third affective response annotations corresponding to first, second, and third temporal windows of token instances, respectively; wherein, the user was exposed to the first, second, and third, temporal windows of token instances during first, second, and third time periods, respectively; and wherein the first time period precedes the second time period, and the second time period precedes the third time period; and a baseline calculator, implemented utilizing a processor, configured to receive a certain temporal window of token instances and to compute, using a distance function, a first metric, a second metric, and a third metric between the certain temporal window of token instances and of the first temporal window of token instances, the second temporal window of token instances, and the third temporal window of token instances respectively; wherein the first and third metrics are below a predefined threshold, while the second metric is not below the predefined threshold; the baseline calculator is further configured to receive, from the database, the first and third affective response annotations and to compute a first affective response baseline level, associated with the certain temporal window of token instances, based on data comprising the first and third affective response annotations; the baseline calculator is further configured to receive an additional temporal window of token instances; the baseline calculator is further configured to receive, from the database, the second affective response annotation; wherein a fourth metric between the additional temporal windows of token instances and the second temporal windows of token instances is below the predefined threshold; the baseline calculator is further configured to compute a second affective response baseline level associated with the additional temporal window of token instances based on data comprising the second affective response annotation; wherein the computed first affective response baseline level is different from the computed second affective response baseline level; wherein the first and second affective response baseline levels each represent a value comprising at least one of: an emotional response, and a value of a user measurement channel. | 8. A system configured to compute token-dependent affective response baseline levels for a user, comprising: a database comprising first, second, and third affective response annotations corresponding to first, second, and third temporal windows of token instances, respectively; wherein, the user was exposed to the first, second, and third, temporal windows of token instances during first, second, and third time periods, respectively; and wherein the first time period precedes the second time period, and the second time period precedes the third time period; and a baseline calculator, implemented utilizing a processor, configured to receive a certain temporal window of token instances and to compute, using a distance function, a first metric, a second metric, and a third metric between the certain temporal window of token instances and of the first temporal window of token instances, the second temporal window of token instances, and the third temporal window of token instances respectively; wherein the first and third metrics are below a predefined threshold, while the second metric is not below the predefined threshold; the baseline calculator is further configured to receive, from the database, the first and third affective response annotations and to compute a first affective response baseline level, associated with the certain temporal window of token instances, based on data comprising the first and third affective response annotations; the baseline calculator is further configured to receive an additional temporal window of token instances; the baseline calculator is further configured to receive, from the database, the second affective response annotation; wherein a fourth metric between the additional temporal windows of token instances and the second temporal windows of token instances is below the predefined threshold; the baseline calculator is further configured to compute a second affective response baseline level associated with the additional temporal window of token instances based on data comprising the second affective response annotation; wherein the computed first affective response baseline level is different from the computed second affective response baseline level; wherein the first and second affective response baseline levels each represent a value comprising at least one of: an emotional response, and a value of a user measurement channel. 11. The system of claim 8 , wherein the first, second, and third temporal windows of token instances comprise first, second, and third situation identifiers, respectively; and wherein the first and third situation identifiers correspond to a first situation, and the second situation identifier corresponds to a second situation that is different than the first situation. | 0.553957 |
9,141,906 | 4 | 5 | 4. The system of claim 3 , the operations further comprising: selecting one or more of the concept terms as advertising keywords to be used in selecting candidate advertisements for participation in the online advertisement auction based on the relevance scores. | 4. The system of claim 3 , the operations further comprising: selecting one or more of the concept terms as advertising keywords to be used in selecting candidate advertisements for participation in the online advertisement auction based on the relevance scores. 5. The system of claim 4 , the operations further comprising: filtering out concept terms that are not in the same language as the resource. | 0.631579 |
8,433,708 | 1 | 13 | 1. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, wherein the citation location comprises one or more of: i) an internal citation page number; ii) an internal citation column number; iii) an internal citation line number; iv) an internal citation paragraph number; and v) an internal citation sentence number, and f) creating a data structure storing data determined in the correlating step. | 1. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, wherein the citation location comprises one or more of: i) an internal citation page number; ii) an internal citation column number; iii) an internal citation line number; iv) an internal citation paragraph number; and v) an internal citation sentence number, and f) creating a data structure storing data determined in the correlating step. 13. The computer readable medium of claim 1 wherein the formatted document is a patent related publication, and wherein the correlating step further includes at least one of the group of: a) determining claim numbers, and b) determining clause numbers. | 0.734177 |
7,886,286 | 1 | 5 | 1. A component-based system on at least one computer system, wherein the component-based system allows legacy components to locate necessary artifacts, the component-based system comprising: a processor; a context finder that is installed as a context classloader, wherein the context finder analyzes an execution stack to identify a classloader of a legacy component that initiated a context classloader call during runtime; and a buddy loading system that determines whether the legacy component requires loading at least one buddy to locate an artifact that cannot be found with a normal delegation model, and the buddy loading system locates and loads the at least one buddy using a predefined policy, wherein the at least one buddy comprises a class or a resource component for locating the artifact for the legacy component, and wherein a requirement of buddy loading is determined by examining a mark-up comprising a descriptor that indicates the legacy component requires at least one buddy, and indicates the predefined policy used to locate the at least one buddy, and wherein the predefined policy includes one of the following: a dependent policy, a named policy, a global policy, and an execution stack policy. | 1. A component-based system on at least one computer system, wherein the component-based system allows legacy components to locate necessary artifacts, the component-based system comprising: a processor; a context finder that is installed as a context classloader, wherein the context finder analyzes an execution stack to identify a classloader of a legacy component that initiated a context classloader call during runtime; and a buddy loading system that determines whether the legacy component requires loading at least one buddy to locate an artifact that cannot be found with a normal delegation model, and the buddy loading system locates and loads the at least one buddy using a predefined policy, wherein the at least one buddy comprises a class or a resource component for locating the artifact for the legacy component, and wherein a requirement of buddy loading is determined by examining a mark-up comprising a descriptor that indicates the legacy component requires at least one buddy, and indicates the predefined policy used to locate the at least one buddy, and wherein the predefined policy includes one of the following: a dependent policy, a named policy, a global policy, and an execution stack policy. 5. The component-based system of claim 1 , wherein the named policy requires a set of other components to include mark-ups comprising descriptors indicating that they are available as buddies for the legacy component. | 0.589015 |
9,449,110 | 15 | 16 | 15. The system of claim 13 , further comprising computer-readable instructions that when executed by the processor cause the system to: identify a plurality of relevant geotiles that correspond to the location associated with the query. | 15. The system of claim 13 , further comprising computer-readable instructions that when executed by the processor cause the system to: identify a plurality of relevant geotiles that correspond to the location associated with the query. 16. The system of claim 15 , further comprising computer-readable instructions that when executed by the processor cause the system to: identify a plurality of relevant points of interest that map to each of the plurality of relevant geotiles that correspond to the location associated with the query; and return the search result that includes the plurality of relevant points of interest that map to each of the plurality of relevant geotiles. | 0.5 |
6,052,516 | 4 | 7 | 4. A layout method for an automatic layout apparatus, comprising: the connection information storage step of receiving connection information and storing the information in a connection information storage means; the selection/layout step of selecting/laying out an arbitrary transistor on the basis of the input connection information or information stored in said connection information storage means; the element extraction step of extracting an element to be connected; the first conditioning step of performing extraction of the connection information, condition determination of a connection strength, and layout candidate ordering on the basis of information about said element extracted and information stored in layout condition storage means, and storing results in a first extracted-element storage means; the first automatic selection step of automatically selecting a layout candidate on the basis of information in the first conditioning step or the information stored in said first extracted-element storage means; the first determination step of determining whether automatic selection has been performed in the first automatic selection step; the first selection step of selecting whether automatic selection or arbitrary selection is performed when a determination result in the first determination step indicates that automatic selection has not been performed; the step of returning a flow to the first automatic selection step of automatically selecting said layout candidate when a selection result in the first selection step indicates automatic selection; the step of returning the flow to the selection/layout step when the selection result in the first selection step indicates arbitrary selection; the first layout step of executing layout when automatic selection is determined in the first determination step to have been performed; the first layout determination step of determining whether all elements have been laid out; the second conditioning step of ending the layout when the determined result in the first layout determination step indicates that all said elements have been laid out, and performing extraction of connection information, condition determination of the connection strength, and layout candidate ordering, and storing results in second extracted-element storage means when the determination result in the first layout determination step indicates that all said elements have not been laid out; the second automatic selection step of automatically selecting a layout candidate on the basis of information in the second conditioning step and the information stored in said first extracted-element storage means; the second determination step of determining whether automatic selection has been performed in the second automatic selection step; the second selection step of selecting whether automatic selection or arbitrary selection is performed when a determination result in the second determination step indicates that automatic selection has not been performed; the step of returning the flow to the selection/layout step when arbitrary selection is selected in the second selection step; the layout candidate selection step of selecting whether the information stored in said first extracted-element storage means or the information stored in said second extracted-element storage means is used when automatic selection is selected in the second selection step; the step of returning the flow to the second automatic selection step when a selection result in the layout candidate selection step indicates that the information stored in said first extracted-element storage means is used; the third automatic selection step of automatically selecting a layout candidate on the basis of the information stored in said second extracted-element storage means when the information stored in said second extracted-element storage means is selected to be used in the layout candidate selection step; the third determination step of determining whether automatic selection has been performed in the third automatic selection step; the third selection step of selecting whether automatic selection or arbitrary selection is performed when determination in the third determination step indicates that automatic selection has not been performed; the step of returning the flow to the third automatic selection step when automatic selection is selected to be performed in the third selection step; the step of returning the flow to the selection/layout step when arbitrary selection is selected to be performed in the third selection step; the second layout step of executing layout when automatic selection is determined in the third determination step to have been performed, or when automatic selection is determined in the second determination step to have been performed; the second layout determination step of determining whether all elements have been laid out in the second layout step; the step of returning the flow to the second conditioning step when all said elements are determined in the second layout determination step not to have been laid out; and the step of ending layout when all said elements are determined in the second layout determination step to have been laid out. | 4. A layout method for an automatic layout apparatus, comprising: the connection information storage step of receiving connection information and storing the information in a connection information storage means; the selection/layout step of selecting/laying out an arbitrary transistor on the basis of the input connection information or information stored in said connection information storage means; the element extraction step of extracting an element to be connected; the first conditioning step of performing extraction of the connection information, condition determination of a connection strength, and layout candidate ordering on the basis of information about said element extracted and information stored in layout condition storage means, and storing results in a first extracted-element storage means; the first automatic selection step of automatically selecting a layout candidate on the basis of information in the first conditioning step or the information stored in said first extracted-element storage means; the first determination step of determining whether automatic selection has been performed in the first automatic selection step; the first selection step of selecting whether automatic selection or arbitrary selection is performed when a determination result in the first determination step indicates that automatic selection has not been performed; the step of returning a flow to the first automatic selection step of automatically selecting said layout candidate when a selection result in the first selection step indicates automatic selection; the step of returning the flow to the selection/layout step when the selection result in the first selection step indicates arbitrary selection; the first layout step of executing layout when automatic selection is determined in the first determination step to have been performed; the first layout determination step of determining whether all elements have been laid out; the second conditioning step of ending the layout when the determined result in the first layout determination step indicates that all said elements have been laid out, and performing extraction of connection information, condition determination of the connection strength, and layout candidate ordering, and storing results in second extracted-element storage means when the determination result in the first layout determination step indicates that all said elements have not been laid out; the second automatic selection step of automatically selecting a layout candidate on the basis of information in the second conditioning step and the information stored in said first extracted-element storage means; the second determination step of determining whether automatic selection has been performed in the second automatic selection step; the second selection step of selecting whether automatic selection or arbitrary selection is performed when a determination result in the second determination step indicates that automatic selection has not been performed; the step of returning the flow to the selection/layout step when arbitrary selection is selected in the second selection step; the layout candidate selection step of selecting whether the information stored in said first extracted-element storage means or the information stored in said second extracted-element storage means is used when automatic selection is selected in the second selection step; the step of returning the flow to the second automatic selection step when a selection result in the layout candidate selection step indicates that the information stored in said first extracted-element storage means is used; the third automatic selection step of automatically selecting a layout candidate on the basis of the information stored in said second extracted-element storage means when the information stored in said second extracted-element storage means is selected to be used in the layout candidate selection step; the third determination step of determining whether automatic selection has been performed in the third automatic selection step; the third selection step of selecting whether automatic selection or arbitrary selection is performed when determination in the third determination step indicates that automatic selection has not been performed; the step of returning the flow to the third automatic selection step when automatic selection is selected to be performed in the third selection step; the step of returning the flow to the selection/layout step when arbitrary selection is selected to be performed in the third selection step; the second layout step of executing layout when automatic selection is determined in the third determination step to have been performed, or when automatic selection is determined in the second determination step to have been performed; the second layout determination step of determining whether all elements have been laid out in the second layout step; the step of returning the flow to the second conditioning step when all said elements are determined in the second layout determination step not to have been laid out; and the step of ending layout when all said elements are determined in the second layout determination step to have been laid out. 7. A method according to claim 4, wherein the layout candidate ordering is determined by layout condition setting arbitrarily set in said layout condition storage means. | 0.973377 |
9,529,924 | 16 | 25 | 16. A system comprising: a user device having a display and a battery; one or more processors configured to perform operations comprising: providing an interface that: receives text for a search query; communicates with at least one search engine server via a network; in response to the receipt of a first portion of the text for the search query: displays a first set of localized results retrieved based on the first portion of text without displaying remote search results from the search engine server; while displaying the first set of localized results, receives a second portion of text for the search query; and in response to receiving the second portion of the text: in accordance with a determination that the first portion of text and the second portion of text together include more than a predetermined number of characters, wherein the predetermined number of characters is greater than 1 and is based on a low battery state of the battery, concurrently displays a plurality of results that include: a set of results received from the search engine server; and a second set of localized results associated with one or more applications on the device retrieved based on the first portion of the text and the second portion of the text. | 16. A system comprising: a user device having a display and a battery; one or more processors configured to perform operations comprising: providing an interface that: receives text for a search query; communicates with at least one search engine server via a network; in response to the receipt of a first portion of the text for the search query: displays a first set of localized results retrieved based on the first portion of text without displaying remote search results from the search engine server; while displaying the first set of localized results, receives a second portion of text for the search query; and in response to receiving the second portion of the text: in accordance with a determination that the first portion of text and the second portion of text together include more than a predetermined number of characters, wherein the predetermined number of characters is greater than 1 and is based on a low battery state of the battery, concurrently displays a plurality of results that include: a set of results received from the search engine server; and a second set of localized results associated with one or more applications on the device retrieved based on the first portion of the text and the second portion of the text. 25. The system of claim 16 , wherein the plurality of results are displayed in-line with indications that the one or more applications are installed on the user device. | 0.820513 |
8,762,433 | 2 | 3 | 2. The integration architecture of claim 1 , wherein said firmware component further comprises: a plurality of connector components configured to connect said firmware component to an external requirements system database, an external repository database and the revision control repository database; a design artifacts component that manages files, properties, analyses, design and test data for a project design; a model component that manages an architecture framework and software based models; a code component that manages a collection of files to convert software files from a human readable form to a computer executable form; a working files component that manages properties and files including configuration files, libraries, settings and files needed to generate executable files; and a burn component for managing properties and files for executable files used to embed firmware code onto a programmable device. | 2. The integration architecture of claim 1 , wherein said firmware component further comprises: a plurality of connector components configured to connect said firmware component to an external requirements system database, an external repository database and the revision control repository database; a design artifacts component that manages files, properties, analyses, design and test data for a project design; a model component that manages an architecture framework and software based models; a code component that manages a collection of files to convert software files from a human readable form to a computer executable form; a working files component that manages properties and files including configuration files, libraries, settings and files needed to generate executable files; and a burn component for managing properties and files for executable files used to embed firmware code onto a programmable device. 3. The integration architecture of claim 2 , wherein said model component is configured to manage SysML or UML models. | 0.5 |
9,081,853 | 20 | 32 | 20. A computer implemented method for processing information files characterized by containing or pertaining to targets of analysis, said method comprising: using at least one processor with accessible input/output and at least one data store to perform the following: storing information files and associated metadata in computer readable storage, the metadata including targets indicating information about the associated information files, said targets being typed-attributes usable by logic to process the information files; storing hierarchically organized profile data structures in a database including a plurality of individually addressable user records, each including named interest nodes which are user-tunable channels, each named interest node data structure being logically connected with at least one target data structure, each target data structure being logically connected with at least one typed-attribute which can be logically connected by the user to any of said plural user-tunable channels at the user's option; filtering the information files and metadata using said at least one target in a selected named interest node to produce a filtered set of information files, by executing a procedure on a data processing system in communication with the storage and the database, said meta data being produced by a person or an analyze engine performing analysis, extraction or classification on the associated information files; composing, using the data processing system, a first executable document for rendition of a graphical user interface at a user terminal including display to the user of the interest node names, including a representation of the filtered set of information files with user selectable mark-up identifying typed-attributes represented in the filtered set of information files and a representation of the profile data structure; sending said first executable document on a data network across a data network from the data processing system to the user terminal; modifying, using the data processing system, the selected named interest node which is a user-tunable channel in the profile data structure in response to an indication of a selected mark-up by adding the identified target; composing, using the data processing system, a second executable document for rendition of the graphical user interface using said modified named interest node; and sending said second executable document across the data network from the data processing system to the user terminal. | 20. A computer implemented method for processing information files characterized by containing or pertaining to targets of analysis, said method comprising: using at least one processor with accessible input/output and at least one data store to perform the following: storing information files and associated metadata in computer readable storage, the metadata including targets indicating information about the associated information files, said targets being typed-attributes usable by logic to process the information files; storing hierarchically organized profile data structures in a database including a plurality of individually addressable user records, each including named interest nodes which are user-tunable channels, each named interest node data structure being logically connected with at least one target data structure, each target data structure being logically connected with at least one typed-attribute which can be logically connected by the user to any of said plural user-tunable channels at the user's option; filtering the information files and metadata using said at least one target in a selected named interest node to produce a filtered set of information files, by executing a procedure on a data processing system in communication with the storage and the database, said meta data being produced by a person or an analyze engine performing analysis, extraction or classification on the associated information files; composing, using the data processing system, a first executable document for rendition of a graphical user interface at a user terminal including display to the user of the interest node names, including a representation of the filtered set of information files with user selectable mark-up identifying typed-attributes represented in the filtered set of information files and a representation of the profile data structure; sending said first executable document on a data network across a data network from the data processing system to the user terminal; modifying, using the data processing system, the selected named interest node which is a user-tunable channel in the profile data structure in response to an indication of a selected mark-up by adding the identified target; composing, using the data processing system, a second executable document for rendition of the graphical user interface using said modified named interest node; and sending said second executable document across the data network from the data processing system to the user terminal. 32. The method of claim 20 , wherein the graphical user interface includes a front page format viewable to the user that reflects the named interest nodes. | 0.840206 |
10,019,426 | 5 | 9 | 5. The method according to claim 1 , wherein the creating the logic schema and the configuration file according to the annotation rule and the retrieved annotations added to the sample data comprises: deriving a corresponding tree structure according to the annotation rule and the retrieved annotations added to the sample data, nodes of the tree structure comprising the data elements and the annotations in the sample data. | 5. The method according to claim 1 , wherein the creating the logic schema and the configuration file according to the annotation rule and the retrieved annotations added to the sample data comprises: deriving a corresponding tree structure according to the annotation rule and the retrieved annotations added to the sample data, nodes of the tree structure comprising the data elements and the annotations in the sample data. 9. The method of claim 5 , wherein deriving a corresponding tree structure according to the annotation rule and the retrieved annotations added to the sample data in automatically performed by the processor. | 0.640625 |
8,676,780 | 11 | 20 | 11. A computer-based system for processing one or more citations within a document, the system comprising: a processor; a memory communicatively coupled with the processor; computer executable code stored in the memory, the computer executable code comprising: citation identifying code set adapted to identify an unformatted citation within a document; a matching citation code set adapted to access a citation library having stored therein a set of citations and to compare the identified unformatted citation against the citation library to identify a set of citations that potentially match the unformatted citation; and an insertion code set adapted to insert a formatted citation into the document based on receiving a selection of one of the set of potentially matching citations. | 11. A computer-based system for processing one or more citations within a document, the system comprising: a processor; a memory communicatively coupled with the processor; computer executable code stored in the memory, the computer executable code comprising: citation identifying code set adapted to identify an unformatted citation within a document; a matching citation code set adapted to access a citation library having stored therein a set of citations and to compare the identified unformatted citation against the citation library to identify a set of citations that potentially match the unformatted citation; and an insertion code set adapted to insert a formatted citation into the document based on receiving a selection of one of the set of potentially matching citations. 20. The method of claim 11 , further comprising: a code set adapted to provide a list of citation references included in the document, the list including at least one hyperlink to a source citation reference. | 0.733333 |
9,852,625 | 1 | 7 | 1. A method for providing a tutorial message to a driver in a vehicle using an in-vehicle tutorial system comprising a multimodal user interface, the vehicle comprising a processing unit and a plurality of sensors arranged internally and externally of the vehicle and configured to determine a driving context for the driver, wherein the method comprises the steps of: assigning at least an area of improvement, comprising at least one tutorial task, to the tutorial system, wherein different areas of improvement are related to one of a plurality of predefined different categories of improvement; identifying, using the processing unit, a driving context using information collected using the plurality of sensors provided with the vehicle for which a tutorial task is to be performed, the driving context comprising an operational context relating to environmental, vehicle, and traffic conditions under which the vehicle is operated wherein one of the plurality of sensors arranged internally of the vehicle is adapted to measure and detect a behavior of the driver during vehicle operation; based on the tutorial task and the driving context, selecting a tutorial message for the operational context, the tutorial message encouraging a desired driving behavior; providing the selected tutorial message to the driver using the multimodal user interface, wherein the tutorial message is provided as at least a combination of two of an audio, voice, visual, and haptic output during vehicle operation and after vehicle operation; logging a driver response to the provided tutorial message; and determining a correlation between the desired driving behavior and the driver response; determining a goal fulfillment based on the correlation between the desired driving behavior and the driver response; and selecting a further area of improvement to assign to the tutorial system based on the goal fulfillment, wherein the step of determining the correlation between the desired driving behavior and the driver response comprises relating the driver response to at least one of the plurality of predefined categories of improvement and establishing a skill level of the driver as one of at least novice driver and more skilled driver, the step of selecting the further area of improvement to be assigned to the tutorial system is further based on previous assignments to the plurality of predefined categories of improvement, and the step of selecting the tutorial message is at least partially based on the skill level of the driver. | 1. A method for providing a tutorial message to a driver in a vehicle using an in-vehicle tutorial system comprising a multimodal user interface, the vehicle comprising a processing unit and a plurality of sensors arranged internally and externally of the vehicle and configured to determine a driving context for the driver, wherein the method comprises the steps of: assigning at least an area of improvement, comprising at least one tutorial task, to the tutorial system, wherein different areas of improvement are related to one of a plurality of predefined different categories of improvement; identifying, using the processing unit, a driving context using information collected using the plurality of sensors provided with the vehicle for which a tutorial task is to be performed, the driving context comprising an operational context relating to environmental, vehicle, and traffic conditions under which the vehicle is operated wherein one of the plurality of sensors arranged internally of the vehicle is adapted to measure and detect a behavior of the driver during vehicle operation; based on the tutorial task and the driving context, selecting a tutorial message for the operational context, the tutorial message encouraging a desired driving behavior; providing the selected tutorial message to the driver using the multimodal user interface, wherein the tutorial message is provided as at least a combination of two of an audio, voice, visual, and haptic output during vehicle operation and after vehicle operation; logging a driver response to the provided tutorial message; and determining a correlation between the desired driving behavior and the driver response; determining a goal fulfillment based on the correlation between the desired driving behavior and the driver response; and selecting a further area of improvement to assign to the tutorial system based on the goal fulfillment, wherein the step of determining the correlation between the desired driving behavior and the driver response comprises relating the driver response to at least one of the plurality of predefined categories of improvement and establishing a skill level of the driver as one of at least novice driver and more skilled driver, the step of selecting the further area of improvement to be assigned to the tutorial system is further based on previous assignments to the plurality of predefined categories of improvement, and the step of selecting the tutorial message is at least partially based on the skill level of the driver. 7. Method according to claim 1 , wherein the driving context and the corresponding tutorial task are logged for allowing the driver to be allowed to review in an offline state, thereby allowing the driver to receive further tutorial messages. | 0.558394 |
9,904,675 | 5 | 7 | 5. The method according to claim 1 , wherein the question type is determined based on a question type database. | 5. The method according to claim 1 , wherein the question type is determined based on a question type database. 7. The method according to anyone of the claim 5 , wherein the question type is determined based on the question type database is a coarse question type which is refined or adjusted. | 0.686207 |
9,953,186 | 10 | 11 | 10. The system of claim 7 , wherein the network proxy server is further configured to determine the character type of the search term, to pad at least one trailing character to the search term using the minimum possible value associated with the character type of the search term to generate the minimum possible plaintext string, and to pad at least one trailing character to the search term using the maximum possible value associated with the character type of the search term to generate the maximum possible plaintext string. | 10. The system of claim 7 , wherein the network proxy server is further configured to determine the character type of the search term, to pad at least one trailing character to the search term using the minimum possible value associated with the character type of the search term to generate the minimum possible plaintext string, and to pad at least one trailing character to the search term using the maximum possible value associated with the character type of the search term to generate the maximum possible plaintext string. 11. The system of claim 10 , wherein the network proxy server is further configured to pad at least one trailing character to the search term using the minimum possible value associated with the character type of the search term based on the ASCII values assigned to the character type. | 0.5 |
8,341,160 | 3 | 4 | 3. The system of claim 1 , wherein the first plurality of index signatures includes a plurality of features, wherein the plurality of feature includes a first feature of the first member. | 3. The system of claim 1 , wherein the first plurality of index signatures includes a plurality of features, wherein the plurality of feature includes a first feature of the first member. 4. The system of claim 3 , wherein the first feature includes at least one entity, wherein the at least one entity includes a first entity that includes a string of text that is included in the first member information and delimited from other strings of text that are included in the first member information. | 0.5 |
8,732,174 | 15 | 16 | 15. The computer program product of claim 13 , wherein the merging of the first search result set and the second search result set comprises performing a logical AND operation on the first search result set and the second search result set to produce a resultant set. | 15. The computer program product of claim 13 , wherein the merging of the first search result set and the second search result set comprises performing a logical AND operation on the first search result set and the second search result set to produce a resultant set. 16. The computer program product of claim 15 , further comprising merging the resultant set with an additional search result set. | 0.5 |
7,818,378 | 43 | 48 | 43. A computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the computer readable storage medium being non-transitory, the one or more programs in the computer readable storage medium comprising: instructions for receiving a plurality of messages directed to a user, each message having a unique message identifier; instructions for associating each of the plurality of messages with a respective conversation, each conversation having a respective conversation identifier; wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria and the respective conversation identifier is distinct from a subject reference of the one or more messages in the respective conversation; instructions for associating with each conversation a set of senders of messages included in the conversation; and instructions for providing presentation information for displaying a list of conversations in an order determined in accordance with second predefined criteria, each conversation being represented as a single item in the list, wherein a plurality of conversations in the list of conversations each include a plurality of messages that share a common set of characteristics that meet the first predefined criteria; wherein the instructions for providing presentation information include instructions for providing information to display the list of conversations as a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, wherein the sender list of a row in the list of conversations includes identifiers of one or more senders of at least one message in the corresponding conversation, including identifiers of a plurality of the senders in the set of senders, but less than all of the senders in the set of senders, when the set of senders exceeds a predefined limit. | 43. A computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the computer readable storage medium being non-transitory, the one or more programs in the computer readable storage medium comprising: instructions for receiving a plurality of messages directed to a user, each message having a unique message identifier; instructions for associating each of the plurality of messages with a respective conversation, each conversation having a respective conversation identifier; wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria and the respective conversation identifier is distinct from a subject reference of the one or more messages in the respective conversation; instructions for associating with each conversation a set of senders of messages included in the conversation; and instructions for providing presentation information for displaying a list of conversations in an order determined in accordance with second predefined criteria, each conversation being represented as a single item in the list, wherein a plurality of conversations in the list of conversations each include a plurality of messages that share a common set of characteristics that meet the first predefined criteria; wherein the instructions for providing presentation information include instructions for providing information to display the list of conversations as a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, wherein the sender list of a row in the list of conversations includes identifiers of one or more senders of at least one message in the corresponding conversation, including identifiers of a plurality of the senders in the set of senders, but less than all of the senders in the set of senders, when the set of senders exceeds a predefined limit. 48. The computer readable storage medium of claim 43 , including instructions for providing presentation information include instructions for replacing a sender's identifier in the sender list with a unique character string or icon when the sender is the user. | 0.801527 |
10,026,328 | 7 | 12 | 7. A healthcare diagnosis training and evaluation system comprises: a virtual patient examination simulator interface module that renders a computer graphics animation of a virtual physical exam diagnostic device and a real-time motory change to an organ or a body part of an animated virtual patient when a user's diagnostic gesture pattern is drawn with a mouse or a finger on top of the animated virtual patient on a display screen, wherein the virtual patient examination simulator interface prompts the user to specify diagnostic prediction indicators for a diagnostics result before invoking the user's diagnostic gesture pattern to initiate a diagnostics test and determine correctness of the user's diagnostic indicators, wherein the real-time motory change to the organ or the body part and the diagnostics test is associated with an ocular motor examination, and wherein the user's diagnostic gesture pattern drawn on top of the animated virtual patient is an “H” pattern gestured over the animated virtual patient's eyes with the mouse or the finger; a test mode selection interface module that generates a user selection menu for a basic linear test mode, a beginner student test mode for dynamic differential diagnosis, and an advanced student test mode for dynamic differential diagnosis; a hypothesis selection and ranking interface module that allows a student to add, delete, rank, or modify a hypothesis in the differential diagnosis list during a health questioning, a simulated physical exam, a simulated medical test, and a simulated medical tests review, wherein the hypothesis selection and ranking interface module generates a differential diagnosis management menu to create or modify a differential diagnosis list for patient condition determination; a virtual patient health questioning interface module that generates a list of health questions selected by a student, an image of a simulated virtual patient, and simulated responses from the simulated virtual patient from the list of health questions, wherein the virtual patient health questioning interface module also incorporates the differential diagnosis management menu to allow the student to create or modify the differential diagnosis list for patient condition determination; a physical exam interface module that enables the student to perform the simulated physical exam on the simulated virtual patient, wherein the physical exam interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination during or after the simulated physical exam; a hypothesis and medical test association interface module that allows the student to associate the simulated medical test to a particular hypothesis in the differential diagnosis list, wherein the hypothesis and medical test association interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination; a medical test selection and differential diagnosis commitment interface module that requires the student to commit a current set of the differential diagnosis list for computerized evaluation, while also requiring the student to finalize simulated medical test selections for patient condition determination; a medical test results interface module that generates results of the simulated medical test, wherein the results are reviewed by the student for deducing a definitive diagnosis for evaluation; a treatment and management plan composition interface module that takes the student's input for a treatment and management plan; a student diagnosis evaluation interface module that evaluates the definitive diagnosis, the treatment and management plan, and associated diagnostic reasoning to generate a grading result based on correctness of the definitive diagnosis, the treatment and management plan, and the associated diagnostic reasoning from the student; and a central processing unit (CPU) and a memory unit of a computer system or another electronic device, wherein the CPU and the memory unit execute at least one of the virtual patient examination simulator interface module, the testing mode selection interface module, the hypothesis selection and ranking interface module, the virtual patient health questioning interface module, the physical exam interface module, the hypothesis and medical test association interface module, the medical test selection and differential diagnosis commitment interface module, the medical test results interface module, the treatment and management plan composition interface module, and the student diagnosis evaluation interface module. | 7. A healthcare diagnosis training and evaluation system comprises: a virtual patient examination simulator interface module that renders a computer graphics animation of a virtual physical exam diagnostic device and a real-time motory change to an organ or a body part of an animated virtual patient when a user's diagnostic gesture pattern is drawn with a mouse or a finger on top of the animated virtual patient on a display screen, wherein the virtual patient examination simulator interface prompts the user to specify diagnostic prediction indicators for a diagnostics result before invoking the user's diagnostic gesture pattern to initiate a diagnostics test and determine correctness of the user's diagnostic indicators, wherein the real-time motory change to the organ or the body part and the diagnostics test is associated with an ocular motor examination, and wherein the user's diagnostic gesture pattern drawn on top of the animated virtual patient is an “H” pattern gestured over the animated virtual patient's eyes with the mouse or the finger; a test mode selection interface module that generates a user selection menu for a basic linear test mode, a beginner student test mode for dynamic differential diagnosis, and an advanced student test mode for dynamic differential diagnosis; a hypothesis selection and ranking interface module that allows a student to add, delete, rank, or modify a hypothesis in the differential diagnosis list during a health questioning, a simulated physical exam, a simulated medical test, and a simulated medical tests review, wherein the hypothesis selection and ranking interface module generates a differential diagnosis management menu to create or modify a differential diagnosis list for patient condition determination; a virtual patient health questioning interface module that generates a list of health questions selected by a student, an image of a simulated virtual patient, and simulated responses from the simulated virtual patient from the list of health questions, wherein the virtual patient health questioning interface module also incorporates the differential diagnosis management menu to allow the student to create or modify the differential diagnosis list for patient condition determination; a physical exam interface module that enables the student to perform the simulated physical exam on the simulated virtual patient, wherein the physical exam interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination during or after the simulated physical exam; a hypothesis and medical test association interface module that allows the student to associate the simulated medical test to a particular hypothesis in the differential diagnosis list, wherein the hypothesis and medical test association interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination; a medical test selection and differential diagnosis commitment interface module that requires the student to commit a current set of the differential diagnosis list for computerized evaluation, while also requiring the student to finalize simulated medical test selections for patient condition determination; a medical test results interface module that generates results of the simulated medical test, wherein the results are reviewed by the student for deducing a definitive diagnosis for evaluation; a treatment and management plan composition interface module that takes the student's input for a treatment and management plan; a student diagnosis evaluation interface module that evaluates the definitive diagnosis, the treatment and management plan, and associated diagnostic reasoning to generate a grading result based on correctness of the definitive diagnosis, the treatment and management plan, and the associated diagnostic reasoning from the student; and a central processing unit (CPU) and a memory unit of a computer system or another electronic device, wherein the CPU and the memory unit execute at least one of the virtual patient examination simulator interface module, the testing mode selection interface module, the hypothesis selection and ranking interface module, the virtual patient health questioning interface module, the physical exam interface module, the hypothesis and medical test association interface module, the medical test selection and differential diagnosis commitment interface module, the medical test results interface module, the treatment and management plan composition interface module, and the student diagnosis evaluation interface module. 12. The healthcare diagnosis training and evaluation system of claim 7 , further comprising a display panel connected to the computer system or another electronic device, wherein the display panel displays computerized user interface information from the testing mode selection interface module, the hypothesis selection and ranking interface module, the virtual patient health questioning interface module, the physical exam interface module, the hypothesis and medical test association interface module, the medical test selection and differential diagnosis commitment interface module, the medical test results interface module, the treatment and management plan composition interface module, and the student diagnosis evaluation interface module. | 0.5 |
8,413,109 | 1 | 2 | 1. A computer-implemented method comprising: receiving a first metamodel conforming to a first meta-metamodel associated with first modeling unit types; and generating, based on the first metamodel and on a mapping between the first meta-metamodel and a second meta-metamodel associated with second modeling unit types, a second metamodel conforming to the second meta-metamodel, wherein the first modeling unit types are different from the second modeling unit types; after the generating of the second metamodel based on the first metamodel and the mapping, using the second metamodel conforming to the second meta-metamodel to develop a tool that is based on the first metamodel conforming to the first meta-metamodel; and after the using of the second metamodel conforming to the second meta-metamodel to develop a tool that is based on the first metamodel conforming to the first meta-metamodel, using the tool developed using the second metamodel to access model data conforming to the first meta-metamodel. | 1. A computer-implemented method comprising: receiving a first metamodel conforming to a first meta-metamodel associated with first modeling unit types; and generating, based on the first metamodel and on a mapping between the first meta-metamodel and a second meta-metamodel associated with second modeling unit types, a second metamodel conforming to the second meta-metamodel, wherein the first modeling unit types are different from the second modeling unit types; after the generating of the second metamodel based on the first metamodel and the mapping, using the second metamodel conforming to the second meta-metamodel to develop a tool that is based on the first metamodel conforming to the first meta-metamodel; and after the using of the second metamodel conforming to the second meta-metamodel to develop a tool that is based on the first metamodel conforming to the first meta-metamodel, using the tool developed using the second metamodel to access model data conforming to the first meta-metamodel. 2. The method according to claim 1 , wherein the mapping comprises a plurality of rules to generate instances of each of the second modeling unit types based on instances of respective ones of the first modeling unit types. | 0.5 |
8,840,695 | 1 | 17 | 1. A method of forming a shaped abrasive particle comprising: forming a mixture comprising a ceramic material into a sheet; sectioning at least a portion of the sheet using a mechanical object and forming at least one shaped abrasive particle from the sheet, wherein the at least one shaped abrasive particle comprises a two-dimensional shape as viewed in a plane defined by a length and a width of the shaped abrasive particle selected from the group consisting of polygons, ellipsoids, numerals, Greek alphabet characters, Latin alphabet characters, Russian alphabet characters, complex shapes having a combination of polygonal shapes, and a combination thereof, and wherein the at least one shaped abrasive particle comprises a body, wherein the body is essentially free of a binder. | 1. A method of forming a shaped abrasive particle comprising: forming a mixture comprising a ceramic material into a sheet; sectioning at least a portion of the sheet using a mechanical object and forming at least one shaped abrasive particle from the sheet, wherein the at least one shaped abrasive particle comprises a two-dimensional shape as viewed in a plane defined by a length and a width of the shaped abrasive particle selected from the group consisting of polygons, ellipsoids, numerals, Greek alphabet characters, Latin alphabet characters, Russian alphabet characters, complex shapes having a combination of polygonal shapes, and a combination thereof, and wherein the at least one shaped abrasive particle comprises a body, wherein the body is essentially free of a binder. 17. The method of claim 1 , wherein the body comprises a polycrystalline material. | 0.925725 |
8,078,517 | 16 | 17 | 16. The system of claim 15 , further comprising executable instructions configured to: image the document; and extract the information from an image of the document. | 16. The system of claim 15 , further comprising executable instructions configured to: image the document; and extract the information from an image of the document. 17. The system of claim 16 , further comprising executable instructions configured to provide the image of the document to an analyst to identify the information associated with the document. | 0.5 |
8,630,860 | 9 | 10 | 9. The computer-implemented method of claim 8 , further comprising: accessing utterances from a collection of utterances; separating utterances into groups of utterances based on identified acoustic voice features, wherein a given group of utterances represents a set of speakers having similar acoustic voice features; and for each group of utterances, creating a statistical language model specific to a respective group of utterances. | 9. The computer-implemented method of claim 8 , further comprising: accessing utterances from a collection of utterances; separating utterances into groups of utterances based on identified acoustic voice features, wherein a given group of utterances represents a set of speakers having similar acoustic voice features; and for each group of utterances, creating a statistical language model specific to a respective group of utterances. 10. The computer-implemented method of claim 9 , further comprising: receiving metadata that corresponds to the spoken query; wherein classifying the spoken query into at least one voice cluster based on the identified acoustic features of the voice signal includes classifying the spoken query based on the metadata in addition to the identified acoustic voice features; and using a user interaction log of user activity with the search results to update the voice cluster and text cluster. | 0.5 |
9,014,363 | 11 | 12 | 11. The method of claim 1 further comprising generating the customer interaction log with reference to a realtime model automatically generated for the interaction. | 11. The method of claim 1 further comprising generating the customer interaction log with reference to a realtime model automatically generated for the interaction. 12. The method of claim 11 wherein generating the realtime model is performed automatically from a global model. | 0.5 |
8,275,617 | 1 | 2 | 1. An interactive computer controlled display system with speech command input recognition comprising: means for predetermining a plurality of speech commands for respectively initiating each of a corresponding plurality of system actions, means for providing for each of said plurality of commands, an associated set of non-command speech terms, each term having relevance to its associated command, means for detecting speech command and non-command speech terms, means responsive to a detected speech command for displaying said command, and means responsive to a detected non-command speech term having relevance to one of said commands for displaying the relevant command simultaneously with said detected speech command. | 1. An interactive computer controlled display system with speech command input recognition comprising: means for predetermining a plurality of speech commands for respectively initiating each of a corresponding plurality of system actions, means for providing for each of said plurality of commands, an associated set of non-command speech terms, each term having relevance to its associated command, means for detecting speech command and non-command speech terms, means responsive to a detected speech command for displaying said command, and means responsive to a detected non-command speech term having relevance to one of said commands for displaying the relevant command simultaneously with said detected speech command. 2. The system of claim 1 further including interactive means for selecting a displayed command to thereby initiate a system action. | 0.5 |
9,443,513 | 7 | 10 | 7. A system for classifying a spoken response as being plagiarized or non-plagiarized, the system comprising: a processing system; and computer-readable memory in communication with the processing system encoded with instructions for commanding the processing system to execute steps comprising: processing a spoken response to generate a first text that is representative of the spoken response; processing the first text to remove disfluencies in the first text; processing the first text to identify a plurality of n-grams in the first text; processing the first text to identify a plurality of sentences in the first text; processing the plurality of n-grams and a source text to determine a first numerical measure indicative of a number of words and phrases of the first text that are included verbatim in the source text, each of the n-grams being compared to n-grams of the source text to determine the first numerical measure, the source text having been designated as a source of plagiarized content; processing the first text and the source text to determine a second numerical measure indicative of (i) an amount of the first text that paraphrases portions of the source text, or (ii) an amount of the first text that is semantically-similar to portions of the source text, the second numerical measure being determined by comparing units of text of the first text with corresponding units of text of the source text; processing the plurality of sentences and the source text to determine a third numerical measure indicative of a similarity between sentences of the first text and sentences of the source text, each sentence of the plurality of sentences being compared to each sentence of the source text to determine the third numerical measure; and applying a model to the first numerical measure, the second numerical measure, and the third numerical measure to classify the spoken response as being plagiarized or non-plagiarized, the model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the second variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. | 7. A system for classifying a spoken response as being plagiarized or non-plagiarized, the system comprising: a processing system; and computer-readable memory in communication with the processing system encoded with instructions for commanding the processing system to execute steps comprising: processing a spoken response to generate a first text that is representative of the spoken response; processing the first text to remove disfluencies in the first text; processing the first text to identify a plurality of n-grams in the first text; processing the first text to identify a plurality of sentences in the first text; processing the plurality of n-grams and a source text to determine a first numerical measure indicative of a number of words and phrases of the first text that are included verbatim in the source text, each of the n-grams being compared to n-grams of the source text to determine the first numerical measure, the source text having been designated as a source of plagiarized content; processing the first text and the source text to determine a second numerical measure indicative of (i) an amount of the first text that paraphrases portions of the source text, or (ii) an amount of the first text that is semantically-similar to portions of the source text, the second numerical measure being determined by comparing units of text of the first text with corresponding units of text of the source text; processing the plurality of sentences and the source text to determine a third numerical measure indicative of a similarity between sentences of the first text and sentences of the source text, each sentence of the plurality of sentences being compared to each sentence of the source text to determine the third numerical measure; and applying a model to the first numerical measure, the second numerical measure, and the third numerical measure to classify the spoken response as being plagiarized or non-plagiarized, the model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the second variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. 10. The system of claim 7 , wherein the processing of the spoken response to generate the first text includes applying an automatic speech recognition (ASR) algorithm to the spoken response, the ASR algorithm generating (i) a plurality of word hypotheses, and (ii) a confidence score for each of the word hypotheses, and wherein the first numerical measure is based on a weighted summation of scores, the scores being indicative of whether a word or phrase of the first text is included in the source text, and weights utilized in the weighted summation being based on the confidence scores. | 0.771285 |
9,529,904 | 11 | 17 | 11. A computer program product for updating ontology when a set of evidences and a set of constraints are given as inputs, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to categorize one or more new concepts included in a set of evidences into one of three sets, a) a definitely relevant set, b) a possibly relevant set, and c) an irrelevant set, wherein i) concepts included in the definitely relevant set meet or exceed a first categorization threshold, ii) concepts included in the irrelevant set are below a second categorization threshold, and iii) concepts included in the possibly relevant set are (a) below the first categorization threshold and (b) meet or exceed the second categorization threshold; program instructions to add a categorized new concept included in the definitely relevant set to an first ontology; program instructions to add a categorized new concept included in the possibly relevant set to a residual ontology; program instructions to match one or more new concepts included in the set of evidences to an old concept included in the first ontology or to an old concept included in the residual ontology, wherein an old concept existed as part of the first ontology or the residual ontology before the respective addition of the new concepts to the first ontology or the residual ontology; program instructions to determine to increase an associated confidence measure of the old concept, included in the first ontology or the residual ontology, based at least in part, on the matching; program instructions to determine to expand the first ontology or the residual ontology by respectively exchanging one or more old concepts between the first ontology and the residual ontology; and program instructions to remove one or more old concepts from the first ontology or the residual ontology based, at least in part, on a set of constraints, wherein the constraints dictate size and performance requirements of the first ontology. | 11. A computer program product for updating ontology when a set of evidences and a set of constraints are given as inputs, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to categorize one or more new concepts included in a set of evidences into one of three sets, a) a definitely relevant set, b) a possibly relevant set, and c) an irrelevant set, wherein i) concepts included in the definitely relevant set meet or exceed a first categorization threshold, ii) concepts included in the irrelevant set are below a second categorization threshold, and iii) concepts included in the possibly relevant set are (a) below the first categorization threshold and (b) meet or exceed the second categorization threshold; program instructions to add a categorized new concept included in the definitely relevant set to an first ontology; program instructions to add a categorized new concept included in the possibly relevant set to a residual ontology; program instructions to match one or more new concepts included in the set of evidences to an old concept included in the first ontology or to an old concept included in the residual ontology, wherein an old concept existed as part of the first ontology or the residual ontology before the respective addition of the new concepts to the first ontology or the residual ontology; program instructions to determine to increase an associated confidence measure of the old concept, included in the first ontology or the residual ontology, based at least in part, on the matching; program instructions to determine to expand the first ontology or the residual ontology by respectively exchanging one or more old concepts between the first ontology and the residual ontology; and program instructions to remove one or more old concepts from the first ontology or the residual ontology based, at least in part, on a set of constraints, wherein the constraints dictate size and performance requirements of the first ontology. 17. The computer program product of claim 11 , the program instructions further comprising: program instructions to determine a weighted value for one or more techniques of evidence accumulation, wherein the one or more techniques of evidence accumulation are used to generate sets of evidences; and program instructions to redistribute one or more weighted values among two or more different techniques of evidence accumulation. | 0.641903 |
7,849,036 | 13 | 14 | 13. The method as claimed in claim 12 , wherein the individual knowledge manager machine which has received the request from the collective knowledge manager in the individual manager machine makes an investigation within the individual knowledge manager machine of the individual knowledge manager machine, in response to the request, in accordance with specific aim and strategy rules. | 13. The method as claimed in claim 12 , wherein the individual knowledge manager machine which has received the request from the collective knowledge manager in the individual manager machine makes an investigation within the individual knowledge manager machine of the individual knowledge manager machine, in response to the request, in accordance with specific aim and strategy rules. 14. The method as claimed in claim 13 , comprising a further supplementary decision stage, including a technical analysis of the knowledge object, completed by information items resulting from foregoing decision stages, enabling a decision to be made by the individual knowledge manager machine in accordance with specific aim and strategy rules. | 0.5 |
7,757,204 | 21 | 29 | 21. A system comprising: one or more computers; and a computer program, the computer program, when executed, performing the following steps: selecting, on at least one computer, a plurality of patterns in a visual modeling environment and establishing connections between the plurality of patterns to create a design time graphical representation of one or more user interfaces of an end-user application, wherein each pattern performs one or more user interface tasks and different patterns performing different user interface tasks have different graphical representations, and wherein at least a first pattern of the plurality of patterns has a visual representation in the end-user application and at least a second pattern of the plurality of patterns does not have a visual representation in the end-user application, and wherein the plurality of patterns in the visual modeling environment further comprise syntax rules governing how the patterns can be composed and semantic rules governing how the patterns will be interpreted to generate the runtime version of the end-user application; configuring the plurality of patterns to specify application specific properties of each pattern to produce configuration data, the configuration data defining the behavior of the one or more user interfaces in the end-user application, wherein configuring the second pattern not having a visual representation in the end-user application comprises specifying a back-end system and data to be used by the second pattern; storing the configuration data in a repository; receiving user input defining an extension to at least one pattern, wherein a first pattern in the plurality of patterns has a property that indicates whether or not the first pattern is extendable, and querying the first pattern to determine whether the first pattern is extendable; and generating a runtime version of the end-user application using the configuration data. | 21. A system comprising: one or more computers; and a computer program, the computer program, when executed, performing the following steps: selecting, on at least one computer, a plurality of patterns in a visual modeling environment and establishing connections between the plurality of patterns to create a design time graphical representation of one or more user interfaces of an end-user application, wherein each pattern performs one or more user interface tasks and different patterns performing different user interface tasks have different graphical representations, and wherein at least a first pattern of the plurality of patterns has a visual representation in the end-user application and at least a second pattern of the plurality of patterns does not have a visual representation in the end-user application, and wherein the plurality of patterns in the visual modeling environment further comprise syntax rules governing how the patterns can be composed and semantic rules governing how the patterns will be interpreted to generate the runtime version of the end-user application; configuring the plurality of patterns to specify application specific properties of each pattern to produce configuration data, the configuration data defining the behavior of the one or more user interfaces in the end-user application, wherein configuring the second pattern not having a visual representation in the end-user application comprises specifying a back-end system and data to be used by the second pattern; storing the configuration data in a repository; receiving user input defining an extension to at least one pattern, wherein a first pattern in the plurality of patterns has a property that indicates whether or not the first pattern is extendable, and querying the first pattern to determine whether the first pattern is extendable; and generating a runtime version of the end-user application using the configuration data. 29. The system of claim 21 wherein the configuration data comprises: a specification of the back-end system; a query to be run in the back-end system; query fields to display in a drop down box; and result fields to display. | 0.608392 |
9,606,974 | 1 | 5 | 1. A method comprising: determining, by use of a networked computer system, that a webpage permits modification; based on the webpage permitting modification, comparing a portion of text contained in the webpage to at least one character string stored in a database, the at least one character string respectively corresponding to at least one data item; based on the portion of text contained in the webpage matching the character string stored in the database, modifying the webpage by inserting the corresponding data item into the webpage, the data item linking the webpage with a different webpage, both the webpage and the different webpage being contained on the same website, the modifying performed by the networked computer system; sending, by the networked computer system, the modified webpage to a web browser of a user; correlating the portion of text contained in the webpage with a common name stored in the database; and communicating, by the networked computer system, the corresponding common name to a producer of the portion of text contained in the webpage. | 1. A method comprising: determining, by use of a networked computer system, that a webpage permits modification; based on the webpage permitting modification, comparing a portion of text contained in the webpage to at least one character string stored in a database, the at least one character string respectively corresponding to at least one data item; based on the portion of text contained in the webpage matching the character string stored in the database, modifying the webpage by inserting the corresponding data item into the webpage, the data item linking the webpage with a different webpage, both the webpage and the different webpage being contained on the same website, the modifying performed by the networked computer system; sending, by the networked computer system, the modified webpage to a web browser of a user; correlating the portion of text contained in the webpage with a common name stored in the database; and communicating, by the networked computer system, the corresponding common name to a producer of the portion of text contained in the webpage. 5. The method of claim 1 , wherein the data item is a hyperlink. | 0.902439 |
10,140,991 | 9 | 14 | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable; when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by the one or more computers, a request from a client device for media content, the request including at least a portion of a first media item or a URL corresponding to the first media item, the first media item including speech of a person; based on the data indicating the first media item, selecting, by the one or more computers, one or more other media items based on one or more representations of acoustic characteristics of the one or more other media items, wherein the one or more representations of acoustic characteristics of the one or more other media items corn rise for each of the one or more other media items a media item, or (ii) a hash of an i-vector or d-vector generated from the other media item; wherein each of the one or more other media items is selected based on a comparison of (i) an i-vector, d-vector or hash determined from speech in the first media item with (ii) the speaker representation for the other media item, wherein: each of the selected one or more other media items is different from the first media item; each of the selected one or more other media items includes speech of the same person whose speech is included in the first media item; and each of the selected one or more other media items is determined, based on acoustic characteristics of the media item, to include speech demonstrating speaker characteristics that have at least a threshold level of similarity with speaker characteristics determined from speech in the first media item; generating, by the one or more computers, data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item; and providing, by the one or more computers and to the client device, a response to the request that includes the data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item. | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable; when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by the one or more computers, a request from a client device for media content, the request including at least a portion of a first media item or a URL corresponding to the first media item, the first media item including speech of a person; based on the data indicating the first media item, selecting, by the one or more computers, one or more other media items based on one or more representations of acoustic characteristics of the one or more other media items, wherein the one or more representations of acoustic characteristics of the one or more other media items corn rise for each of the one or more other media items a media item, or (ii) a hash of an i-vector or d-vector generated from the other media item; wherein each of the one or more other media items is selected based on a comparison of (i) an i-vector, d-vector or hash determined from speech in the first media item with (ii) the speaker representation for the other media item, wherein: each of the selected one or more other media items is different from the first media item; each of the selected one or more other media items includes speech of the same person whose speech is included in the first media item; and each of the selected one or more other media items is determined, based on acoustic characteristics of the media item, to include speech demonstrating speaker characteristics that have at least a threshold level of similarity with speaker characteristics determined from speech in the first media item; generating, by the one or more computers, data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item; and providing, by the one or more computers and to the client device, a response to the request that includes the data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item. 14. The system of claim 9 , wherein providing the response to the request further comprises: providing, by the one or more computers and to the client device, data indicating an identity of the person whose speech is included in the first media item. | 0.580537 |
9,236,043 | 2 | 4 | 2. The computer program product of claim 1 , wherein the knowledge base provides data that is specific to the type of the document. | 2. The computer program product of claim 1 , wherein the knowledge base provides data that is specific to the type of the document. 4. The computer program product of claim 2 , wherein accessing a knowledge base comprises: classify the document according to key words or phrases in the document; and retrieve data from the knowledge base that is associated with the classification of the document. | 0.521661 |
9,424,315 | 16 | 17 | 16. A method of overlapping execution of tasks for a query in a dataflow fashion to reduce overall latency of the tasks, said method comprising: receiving at least a portion of a query execution plan comprising a set of fragments with respective tasks that can be executed in one of a dataflow architecture hardware accelerator, a software execution module, or an input/output execution module having access to a memory having memory pages, wherein execution of the one or more respective tasks is based on execution of machine code instructions formatted for the dataflow architecture hardware accelerator and specifying a dataflow of data through the dataflow architecture hardware accelerator; locking memory pages for the selected tasks; filling output from a first task into the locked memory pages; and starting at least one additional task that consumes the output in one or more of the locked memory pages prior to the locked memory pages being released by the first task. | 16. A method of overlapping execution of tasks for a query in a dataflow fashion to reduce overall latency of the tasks, said method comprising: receiving at least a portion of a query execution plan comprising a set of fragments with respective tasks that can be executed in one of a dataflow architecture hardware accelerator, a software execution module, or an input/output execution module having access to a memory having memory pages, wherein execution of the one or more respective tasks is based on execution of machine code instructions formatted for the dataflow architecture hardware accelerator and specifying a dataflow of data through the dataflow architecture hardware accelerator; locking memory pages for the selected tasks; filling output from a first task into the locked memory pages; and starting at least one additional task that consumes the output in one or more of the locked memory pages prior to the locked memory pages being released by the first task. 17. The method of claim 16 , wherein the first task is an input/output task and the at least one additional task that is executed on a hardware accelerator. | 0.662338 |
9,779,364 | 4 | 5 | 4. The machine learning based procurement system of claim 3 , wherein to select one of the bids as the winning bid, the at least one processor is to: determine from the evaluation of the one of the bids, whether the one of the bids is associated with a high-risk procurement; if the one of the bids is determined to be associated with the high-risk procurement, invoke a secondary system to perform an audit of the one of the bids. | 4. The machine learning based procurement system of claim 3 , wherein to select one of the bids as the winning bid, the at least one processor is to: determine from the evaluation of the one of the bids, whether the one of the bids is associated with a high-risk procurement; if the one of the bids is determined to be associated with the high-risk procurement, invoke a secondary system to perform an audit of the one of the bids. 5. The machine learning based procurement system of claim 4 , wherein the secondary system is to: perform an audit process of the one of the bids; and determine from the audit process whether the procurement system is to accept or reject the one of the bids, the determining generating an identifier to accept the one of the bids or an identifier to reject the one of the bids; and the at least one processor is to: receive a message, from the secondary system, the message including the identifier to accept the one of the bids or the identifier to reject the one of the bids; and accept the one of the bids as the winning bid if the identifier to accept the one of the bids is received in the message. | 0.5 |
9,135,653 | 176 | 177 | 176. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a nonmobile Web browser identifier to a mobile Web browser identifier; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; and updating a first value associated with the first edge to a second value based on a time elapsed from at least one of the first activity information or second activity information. | 176. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a nonmobile Web browser identifier to a mobile Web browser identifier; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; and updating a first value associated with the first edge to a second value based on a time elapsed from at least one of the first activity information or second activity information. 177. The method of claim 176 wherein the first value associated with the first edge is reduced to the second value in proportion to how recent the first or second activity information occurred. | 0.57489 |
7,809,705 | 1 | 2 | 1. A computer system for classifying a web page, comprising: one or more processors to execute instructions; a classification engine for determining a quality of the web page using local features of a seed set of web pages and global web graph information about the seed set of web pages, wherein: each web page of the seed set of web pages is a web page of a known quality, the local features of the seed set of web pages comprises text, clicking, domain, or time stamp information concerning the seed set of web pages, and the global web graph information about the seed set of web pages comprises hyperlink or co-citation relationships among the seed set of web pages; a binary classifier coupled to the classification engine for performing binary classification to provide a binary score for the web page; and a collective inference engine coupled to the binary classifier for performing collective inference by applying collective inference for binary classification using the local features of the seed set of web pages and the global web graph information about the seed set of web pages, comprising finding a minimum value of a regularized convex dual of a logistic regression loss function for a node of a graph. | 1. A computer system for classifying a web page, comprising: one or more processors to execute instructions; a classification engine for determining a quality of the web page using local features of a seed set of web pages and global web graph information about the seed set of web pages, wherein: each web page of the seed set of web pages is a web page of a known quality, the local features of the seed set of web pages comprises text, clicking, domain, or time stamp information concerning the seed set of web pages, and the global web graph information about the seed set of web pages comprises hyperlink or co-citation relationships among the seed set of web pages; a binary classifier coupled to the classification engine for performing binary classification to provide a binary score for the web page; and a collective inference engine coupled to the binary classifier for performing collective inference by applying collective inference for binary classification using the local features of the seed set of web pages and the global web graph information about the seed set of web pages, comprising finding a minimum value of a regularized convex dual of a logistic regression loss function for a node of a graph. 2. The system of claim 1 further comprising a storage coupled to the classification engine for storing the local features of the seed set of web pages and the global web graph information about the seed set of web pages. | 0.5 |
7,761,464 | 7 | 10 | 7. The system of claim 6 , user intent being evinced by query-query reformulation patterns. | 7. The system of claim 6 , user intent being evinced by query-query reformulation patterns. 10. The system of claim 7 , the intent evaluation component selects query-query reformulations based upon at least one of most frequent reformulations, frequent but different reformulations, and frequent and satisfying reformulations. | 0.5 |
9,390,079 | 18 | 20 | 18. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by a computer system, configure the computer system to perform operations comprising: displaying, on an electronic display, a textual record including one or more nodes and one or more subnodes; receiving, from a user interacting with the textual record, a first input including a command and a first identifier; in response to receiving the command and the first identifier: identifying, based on a set of rules and the first identifier, a node of the textual record associated with the first identifier; determining a first portion of the textual record related to the identified node; and selecting the first portion of the textual record; receiving, from the user interacting with the textual record, a second input including the command and a second identifier; and in response to receiving the command and the second identifier: identifying, based on the set of rules and the second identifier, a subnode of the textual record associated with the second identifier; determining a second portion of the textual record related to the identified subnode; and selecting the second portion of the textual record. | 18. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by a computer system, configure the computer system to perform operations comprising: displaying, on an electronic display, a textual record including one or more nodes and one or more subnodes; receiving, from a user interacting with the textual record, a first input including a command and a first identifier; in response to receiving the command and the first identifier: identifying, based on a set of rules and the first identifier, a node of the textual record associated with the first identifier; determining a first portion of the textual record related to the identified node; and selecting the first portion of the textual record; receiving, from the user interacting with the textual record, a second input including the command and a second identifier; and in response to receiving the command and the second identifier: identifying, based on the set of rules and the second identifier, a subnode of the textual record associated with the second identifier; determining a second portion of the textual record related to the identified subnode; and selecting the second portion of the textual record. 20. The non-transitory computer-readable storage medium of claim 18 , wherein the identified node or subnode is associated with a plurality of respective subnodes or sub-subnodes, and wherein the computer system is further configured to perform operations comprising, in response to receiving the command and the respective first or second identifier: selecting a particular one of the plurality of respective subnodes or sub-subnodes associated with the identified node or subnode; determining a third portion of the textual record related to the selected one of the plurality of respective subnodes or sub-subnodes; and selecting the third portion of the textual record related to the selected one of the plurality of respective subnodes or sub-subnodes. | 0.5 |
10,127,022 | 1 | 23 | 1. A method comprising: providing a development environment for a dataflow programming language allowing specifying of at least one matcher state machine that can perform pattern matching in a received input stream and generate output data, wherein the development environment comprises a plurality of tools to perform at least one of the following: identifying a plurality of potential data streams; identifying a set of reactive functions and parameters corresponding to patterns of data in the streams; identifying a set of handling functions and parameters for transforming data matching declared patterns; identifying a set of timed events against which patterns of data flow are compared; creating a dataflow program from expressed intent which describes the identified streams, reactions, functions, and timed events; providing the dataflow program as input to a two-phase translation tool comprising a first-phase translation tool incorporating a matcher generator for translating program statements to corresponding matchers, data flow topologies, functions, and related symbolic components, and a second-phase translation tool for generating optimized platform-specific hardware instructions corresponding to the translated statements for execution on a hardware platform; and receiving the output of each phase of the translation tool. | 1. A method comprising: providing a development environment for a dataflow programming language allowing specifying of at least one matcher state machine that can perform pattern matching in a received input stream and generate output data, wherein the development environment comprises a plurality of tools to perform at least one of the following: identifying a plurality of potential data streams; identifying a set of reactive functions and parameters corresponding to patterns of data in the streams; identifying a set of handling functions and parameters for transforming data matching declared patterns; identifying a set of timed events against which patterns of data flow are compared; creating a dataflow program from expressed intent which describes the identified streams, reactions, functions, and timed events; providing the dataflow program as input to a two-phase translation tool comprising a first-phase translation tool incorporating a matcher generator for translating program statements to corresponding matchers, data flow topologies, functions, and related symbolic components, and a second-phase translation tool for generating optimized platform-specific hardware instructions corresponding to the translated statements for execution on a hardware platform; and receiving the output of each phase of the translation tool. 23. The method of claim 1 wherein the timed events comprise specific points in time before which data are to be collected. | 0.908955 |
9,348,329 | 15 | 20 | 15. A distributed automation control device, comprising: a memory circuit storing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; a processor configured to execute the multiple Boolean logical operations; and an interface configured to output any of the plurality of logical outputs based upon the operations executed by the processor. | 15. A distributed automation control device, comprising: a memory circuit storing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; a processor configured to execute the multiple Boolean logical operations; and an interface configured to output any of the plurality of logical outputs based upon the operations executed by the processor. 20. The distributed automation control device of claim 15 , wherein the distributed automation control device is an input/output terminal block. | 0.770701 |
9,703,832 | 10 | 11 | 10. The data processing system of claim 8 , wherein the processor is further configured with the computer software to cause the data processing system to perform the third search by executing a data collection sub-process as a plurality of parallel data collection sub-processes to retrieve, for each identified rule, the eligible fares from the fares database, and generating a plurality of fare lists. | 10. The data processing system of claim 8 , wherein the processor is further configured with the computer software to cause the data processing system to perform the third search by executing a data collection sub-process as a plurality of parallel data collection sub-processes to retrieve, for each identified rule, the eligible fares from the fares database, and generating a plurality of fare lists. 11. The data processing system of claim 10 , wherein the processor is further configured with the computer software to cause the data processing system to execute the data collection sub-process, for each of the plurality of parallel data collection sub-processes by: retrieving, from a rule category sequence, a list of corresponding fare keys; for each fare key, retrieving a fare and an associated fare application entity, and merging matching rule category sequences to form a fare record; matching each fare record with rule category data and first rule provision data corresponding to the attribute set; matching each fare record against the rule category sequence and retaining those fare records previously identified during the first search; retrieving second rule provision data corresponding to the rule category sequence and matching the rule category data against the fare record and the attribute set; and only storing the fare record in a fare list where a match occurs, wherein the plurality of parallel data collection sub-processes operate on disjoint data domains to avoid performing redundant operations. | 0.5 |
7,821,426 | 12 | 17 | 12. A computer-readable medium storing data and instructions to cause a processor to perform a method comprising: storing a first plurality of literal symbols as a compressed plurality of literal symbols in a first block of data; and storing a second plurality of literal symbols as an encoded plurality of literal symbols in a second block of data, wherein each of the second plurality of literal symbols occurs subsequently in a symbol stream to a literal symbol with the same value in the first plurality of literal symbols. | 12. A computer-readable medium storing data and instructions to cause a processor to perform a method comprising: storing a first plurality of literal symbols as a compressed plurality of literal symbols in a first block of data; and storing a second plurality of literal symbols as an encoded plurality of literal symbols in a second block of data, wherein each of the second plurality of literal symbols occurs subsequently in a symbol stream to a literal symbol with the same value in the first plurality of literal symbols. 17. The computer-readable medium storing data and instructions of claim 12 wherein the stored first block of data follows the stored second block of data. | 0.686992 |
9,210,234 | 1 | 2 | 1. A computer-implemented method comprising: receiving, at a first server separate and remote from a computing device, a request from the computing device to edit an electronic document stored at a second server; causing the electronic document to be edited responsive to input received from the computing device by: receiving, from the computing device, a full-page postback that includes postback name-value pairs; translating, at the first server, the postback name-value pairs from the full-page postback into an event log; and sending the event log to a second server, separate and remote from the first server and the computing device, to enable editing of the electronic document based at least in part on the event log; and receiving results of the editing of the electronic document; determining capabilities of the computing device, including one or more capabilities that indicate the computing device is a limited-capability computing device which is incapable, without external assistance, of rendering at least some view information of the electronic document; and building, at the first server, renderable view information for the electronic document based at least in part on the results of the editing and in response to said determining of the capabilities of the computing device, the renderable view information including a selectable indicia of an electronic form associated with a hierarchical view of one or more nested items, the one or more nested items including information from the postback name-value pairs. | 1. A computer-implemented method comprising: receiving, at a first server separate and remote from a computing device, a request from the computing device to edit an electronic document stored at a second server; causing the electronic document to be edited responsive to input received from the computing device by: receiving, from the computing device, a full-page postback that includes postback name-value pairs; translating, at the first server, the postback name-value pairs from the full-page postback into an event log; and sending the event log to a second server, separate and remote from the first server and the computing device, to enable editing of the electronic document based at least in part on the event log; and receiving results of the editing of the electronic document; determining capabilities of the computing device, including one or more capabilities that indicate the computing device is a limited-capability computing device which is incapable, without external assistance, of rendering at least some view information of the electronic document; and building, at the first server, renderable view information for the electronic document based at least in part on the results of the editing and in response to said determining of the capabilities of the computing device, the renderable view information including a selectable indicia of an electronic form associated with a hierarchical view of one or more nested items, the one or more nested items including information from the postback name-value pairs. 2. The computer-implemented method of claim 1 , wherein the request includes an indication to treat the computing device as a limited-capability device for purposes of editing the electronic document. | 0.84472 |
9,544,263 | 1 | 4 | 1. A method for displaying dynamic content from a networked post in a text message, the method performed by a computer system, the method comprising: receiving a text message, the text message displaying dynamic content from a networked post, wherein the networked post is accessible on a network at a network location; wherein the networked post includes a photo or video, and the photo or video is displayed in the text message; displaying the text message to a user; initiating a call to a first server-side script to retrieve the number of likes that the networked post has received, a client-side handler function being associated with the first server-side script; after completion of the first server-side script, executing the client-side handler function to process a return value of the first server-side script and cause the display of the number of likes that the networked post has received; displaying a like button for liking the networked post; in response to activation of the like button, transmitting an indication of the user liking the networked post to a server to cause a representation of the user's act of liking the networked post to be displayed with the networked post; wherein the act of transmitting the indication of the user liking the networked post to the server comprises initiating a call to a second server-side script to cause the indication of the user liking the networked post to be stored in a database accessible to the server; displaying one or more comments from one or more other users about the networked post in a comment section associated with the text message; displaying a comment field for accepting a comment from the user; in response to the user submitting a comment via the comment field, initiating a call to a third server-side script to cause text of the user-submitted comment to be stored in the database accessible to the server; in response to submission of a new comment by the user or another user, dynamically updating the display of comments associated with the text message to include the new comment. | 1. A method for displaying dynamic content from a networked post in a text message, the method performed by a computer system, the method comprising: receiving a text message, the text message displaying dynamic content from a networked post, wherein the networked post is accessible on a network at a network location; wherein the networked post includes a photo or video, and the photo or video is displayed in the text message; displaying the text message to a user; initiating a call to a first server-side script to retrieve the number of likes that the networked post has received, a client-side handler function being associated with the first server-side script; after completion of the first server-side script, executing the client-side handler function to process a return value of the first server-side script and cause the display of the number of likes that the networked post has received; displaying a like button for liking the networked post; in response to activation of the like button, transmitting an indication of the user liking the networked post to a server to cause a representation of the user's act of liking the networked post to be displayed with the networked post; wherein the act of transmitting the indication of the user liking the networked post to the server comprises initiating a call to a second server-side script to cause the indication of the user liking the networked post to be stored in a database accessible to the server; displaying one or more comments from one or more other users about the networked post in a comment section associated with the text message; displaying a comment field for accepting a comment from the user; in response to the user submitting a comment via the comment field, initiating a call to a third server-side script to cause text of the user-submitted comment to be stored in the database accessible to the server; in response to submission of a new comment by the user or another user, dynamically updating the display of comments associated with the text message to include the new comment. 4. The method of claim 1 , wherein the computer system is a mobile phone connected to a base transceiver station (BTS) and a base controller station (BSC), the text message is received through the BTS and BSC, and the act of transmitting the indication of the user liking the networked post to the server includes transmitting data through the BTS and BSC. | 0.5 |
9,794,198 | 1 | 11 | 1. A method of creating an automatic reply (auto-reply) message, comprising: on a client system having one or more processors and memory storing one or more programs for execution by the one or more processors: obtaining content information of a webpage, the content information of the webpage comprising a set of predetermined tags and information concerning a plurality of content items that are configured to be displayed together in the webpage; creating a graphical user interface (GUI) for composing the auto-reply message; generating a preview of the webpage in the GUI for composing the auto-reply message, the webpage preview including the plurality of content items configured for user selection; composing the auto-reply message in accordance with a user selection of a specific content item of the webpage in the webpage preview, wherein the auto-reply message at least comprises corresponding information of the specific content item displayed in the webpage; associating the auto-reply message with one or more predefined keywords according to one or more auto-reply rules; and sending the auto-reply message and the corresponding predefined keywords to a server system, wherein the server system is configured to store the auto-reply message in an auto-reply database and return the auto-reply message automatically to a subscriber device in response to a subsequent user inquiry including at least one of the predefined keywords from the subscriber device. | 1. A method of creating an automatic reply (auto-reply) message, comprising: on a client system having one or more processors and memory storing one or more programs for execution by the one or more processors: obtaining content information of a webpage, the content information of the webpage comprising a set of predetermined tags and information concerning a plurality of content items that are configured to be displayed together in the webpage; creating a graphical user interface (GUI) for composing the auto-reply message; generating a preview of the webpage in the GUI for composing the auto-reply message, the webpage preview including the plurality of content items configured for user selection; composing the auto-reply message in accordance with a user selection of a specific content item of the webpage in the webpage preview, wherein the auto-reply message at least comprises corresponding information of the specific content item displayed in the webpage; associating the auto-reply message with one or more predefined keywords according to one or more auto-reply rules; and sending the auto-reply message and the corresponding predefined keywords to a server system, wherein the server system is configured to store the auto-reply message in an auto-reply database and return the auto-reply message automatically to a subscriber device in response to a subsequent user inquiry including at least one of the predefined keywords from the subscriber device. 11. The method of claim 1 , wherein the content information of the webpage comprises HTML source codes of the webpage further comprising HTML tags and links to the plurality of content items, and the plurality of content items at least include textual content and pictures. | 0.689066 |
9,110,979 | 1 | 4 | 1. A system, comprising: at least one or more processors; a citation search engine with the at least one or more processors that in operation retrieves a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria, a citation graph coupled to the citation engine, the citation graph used to determine an influence of each of the subjects and the objects, the citation graph including the plurality of citations each describing an opinion of an object by a subject, the citation graph including nodes or entities that are 1) subjects that have an opinion or making citations, and 2) objects cited by citations relative to subjects that have opinions or make citations; an influence evaluation engine with the at least one or more processors that in operation, determines an expertise of a subject as a measure of the subject's expertise in a topic relative to a larger population of multiple subjects and allows for determination of expertise on any query term in real-time; and an object/subject selection engine with the at least one or more processors, which in operation: ranks the cited objects of the plurality of citations using the influence and relative expertise of the subjects, and selects objects as the search result for the user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. | 1. A system, comprising: at least one or more processors; a citation search engine with the at least one or more processors that in operation retrieves a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria, a citation graph coupled to the citation engine, the citation graph used to determine an influence of each of the subjects and the objects, the citation graph including the plurality of citations each describing an opinion of an object by a subject, the citation graph including nodes or entities that are 1) subjects that have an opinion or making citations, and 2) objects cited by citations relative to subjects that have opinions or make citations; an influence evaluation engine with the at least one or more processors that in operation, determines an expertise of a subject as a measure of the subject's expertise in a topic relative to a larger population of multiple subjects and allows for determination of expertise on any query term in real-time; and an object/subject selection engine with the at least one or more processors, which in operation: ranks the cited objects of the plurality of citations using the influence and relative expertise of the subjects, and selects objects as the search result for the user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. 4. The system of claim 1 , wherein: each of the plurality of objects is one of: Internet web sites, blogs, videos, books, films, music, image, video, documents, data files, objects for sale, objects that are reviewed or recommended or cited, subjects/authors, natural or legal persons, citations, or any entities that are associated with a Uniform Resource Identifier (URI). | 0.624498 |
8,688,704 | 1 | 9 | 1. A method performed by data processing apparatus, the method comprising: receiving a search query, the search query including one or more terms that include a name corresponding to one or more individuals; identifying a plurality of search results responsive to the query, wherein the plurality of search results includes a first search result, the first search result corresponding to a cluster of social media resources associated with a particular individual of the one or more individuals, and wherein each resource in the cluster of resources is associated with a corresponding cluster identifier that identifies the cluster of resources; providing for presentation the first search result and one or more other search results of the plurality of search results; receiving user feedback for the first search result that identifies the cluster of resources associated with the particular individual, wherein the feedback provides an indication of the accuracy of the cluster of resources; and processing the received feedback to determine whether to modify the cluster of resources associated with the particular individual, where the processing includes assigning a weight to the user feedback, where the weight of the user feedback is determined based at least on one or more factors associated with the user, and where the one or more factors include a level of a social connection between the user and the one or more individuals. | 1. A method performed by data processing apparatus, the method comprising: receiving a search query, the search query including one or more terms that include a name corresponding to one or more individuals; identifying a plurality of search results responsive to the query, wherein the plurality of search results includes a first search result, the first search result corresponding to a cluster of social media resources associated with a particular individual of the one or more individuals, and wherein each resource in the cluster of resources is associated with a corresponding cluster identifier that identifies the cluster of resources; providing for presentation the first search result and one or more other search results of the plurality of search results; receiving user feedback for the first search result that identifies the cluster of resources associated with the particular individual, wherein the feedback provides an indication of the accuracy of the cluster of resources; and processing the received feedback to determine whether to modify the cluster of resources associated with the particular individual, where the processing includes assigning a weight to the user feedback, where the weight of the user feedback is determined based at least on one or more factors associated with the user, and where the one or more factors include a level of a social connection between the user and the one or more individuals. 9. The method of claim 1 , where processing the received feedback includes assigning the feedback to a human operator for evaluation. | 0.626404 |
8,289,282 | 1 | 2 | 1. A method of facilitating input for a handheld electronic device comprising an input apparatus, the input apparatus comprising a plurality of input keys, the method comprising: analyzing one or more language objects comprising a plurality of linguistic elements to identify a language object that comprises sequential linguistic elements corresponding to an input key; creating a word frame comprising a contracted portion and a root portion, the contracted portion comprising a representation of the input key corresponding to the sequential linguistic elements of the identified language object, the root portion comprising the linguistic elements of the identified language object except the sequential linguistic elements; and storing the word frame in a memory. | 1. A method of facilitating input for a handheld electronic device comprising an input apparatus, the input apparatus comprising a plurality of input keys, the method comprising: analyzing one or more language objects comprising a plurality of linguistic elements to identify a language object that comprises sequential linguistic elements corresponding to an input key; creating a word frame comprising a contracted portion and a root portion, the contracted portion comprising a representation of the input key corresponding to the sequential linguistic elements of the identified language object, the root portion comprising the linguistic elements of the identified language object except the sequential linguistic elements; and storing the word frame in a memory. 2. The method of claim 1 , further comprising: associating the word frame with the identified language object. | 0.817276 |
8,700,594 | 1 | 14 | 1. A computer-implemented process for enabling multidimensional search capabilities on a computing device, other than a desktop personal computer or a laptop computer, being utilized by a user, comprising: using said computing device to perform the following process actions: receiving an original query submitted by the user via the computing device; accessing a structured data repository to extract structured data that is available for the original query, wherein the extracted structured data represents attributes of the original query; providing the extracted structured data to the user in the form of a hierarchical menu which allows the user to interactively modify the original query by selecting at least one item from the hierarchical menu, such modification resulting in a revised query; submitting the revised query to a search service; receiving search results for the revised query from the search service; and providing the search results to the user via the computing device. | 1. A computer-implemented process for enabling multidimensional search capabilities on a computing device, other than a desktop personal computer or a laptop computer, being utilized by a user, comprising: using said computing device to perform the following process actions: receiving an original query submitted by the user via the computing device; accessing a structured data repository to extract structured data that is available for the original query, wherein the extracted structured data represents attributes of the original query; providing the extracted structured data to the user in the form of a hierarchical menu which allows the user to interactively modify the original query by selecting at least one item from the hierarchical menu, such modification resulting in a revised query; submitting the revised query to a search service; receiving search results for the revised query from the search service; and providing the search results to the user via the computing device. 14. The process of claim 1 , wherein the computing device comprises a display device and a handheld three-dimensional remote controller device, and the process action of providing the extracted structured data to the user in the form of a hierarchical menu which allows the user to interactively modify the original query comprises the actions of: displaying a plurality of graphical elements on the display device, wherein each graphical element represents a different item of extracted structured data and is labeled to identify said item; and whenever the user utilizes the remote controller device to virtually point to and select one or more of the graphical elements, using the item of extracted structured data represented by each selected graphical element to generate the revised query. | 0.663421 |
8,150,842 | 35 | 49 | 35. A system comprising: a processor; a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor cause the processor to perform operations comprising: receiving a plurality of online content items authored by a plurality of authors for online publication; and for each online content item, determining a reputation score for an author of the online content item, where the reputation score is based at least in part on: (a) scores of online content items authored by the author, the scores provided by one or more reviewers other than the author; and (b) an authentication score for the author, the authentication score being a function of determinations made to identify that the author is who the author purports to be and in response to a query for online content, generating a set of search results including an online content item from the plurality of online content items; and determining a ranking of the online content item in the set based at least in part on a reputation score of the author. | 35. A system comprising: a processor; a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor cause the processor to perform operations comprising: receiving a plurality of online content items authored by a plurality of authors for online publication; and for each online content item, determining a reputation score for an author of the online content item, where the reputation score is based at least in part on: (a) scores of online content items authored by the author, the scores provided by one or more reviewers other than the author; and (b) an authentication score for the author, the authentication score being a function of determinations made to identify that the author is who the author purports to be and in response to a query for online content, generating a set of search results including an online content item from the plurality of online content items; and determining a ranking of the online content item in the set based at least in part on a reputation score of the author. 49. The system of claim 35 , wherein the instructions, when executed by the processor cause the processor to perform operations further comprising: authenticating an identity of the author prior to determining a reputation score of the author. | 0.745816 |
9,053,091 | 1 | 7 | 1. A method comprising: assigning a value to a first token in a description, the value indicating either: that the first token also occurs in a header of the description, that a lexical association exists between the first token and a second token in the header, or that the lexical association does not exist and the first token is absent from the header; computing a relevance value of a group of tokens that occur in the description and include the first token with the assigned value, the relevance value of the group being computed by a processor of a machine based on the value assigned to the first token; indicating that the group of tokens is a most relevant group of tokens in the description; wherein: the assigning of the value to the first token includes initially assigning a default value that indicates the lexical association does not exist and the first token is absent from the header; and the assigning of the value to the first token includes overwriting the initially assigned default value based on the first token occurring in the header. | 1. A method comprising: assigning a value to a first token in a description, the value indicating either: that the first token also occurs in a header of the description, that a lexical association exists between the first token and a second token in the header, or that the lexical association does not exist and the first token is absent from the header; computing a relevance value of a group of tokens that occur in the description and include the first token with the assigned value, the relevance value of the group being computed by a processor of a machine based on the value assigned to the first token; indicating that the group of tokens is a most relevant group of tokens in the description; wherein: the assigning of the value to the first token includes initially assigning a default value that indicates the lexical association does not exist and the first token is absent from the header; and the assigning of the value to the first token includes overwriting the initially assigned default value based on the first token occurring in the header. 7. The method of claim 1 , wherein: the assigned value represents a relevance probability of the first token; and the computing of the relevance value of the group of tokens is based on the relevance probability of the first token and further based on an irrelevance probability of the first token. | 0.5 |
8,161,105 | 15 | 16 | 15. The method of claim 13 wherein said extracting contents of at least two fields comprises extracting contents of a “FROM” field of said text-based message. | 15. The method of claim 13 wherein said extracting contents of at least two fields comprises extracting contents of a “FROM” field of said text-based message. 16. The method of claim 15 wherein said extracting contents of at least two fields comprises extracting contents of at least one of a “TO” field and a “CC” field of said text-based message. | 0.5 |
5,473,741 | 7 | 8 | 7. The method as recited in claim 6, wherein the step of examining said actual page description language file further comprises: (a) determining the area for each graduated fill of said actual page description language file; (b) determining the area for each patterned fill of said actual page description language file; and (c) determining the area for each radial fill of said actual page description language file. | 7. The method as recited in claim 6, wherein the step of examining said actual page description language file further comprises: (a) determining the area for each graduated fill of said actual page description language file; (b) determining the area for each patterned fill of said actual page description language file; and (c) determining the area for each radial fill of said actual page description language file. 8. The method as recited in claim 7, wherein the step of determining the total combined size of all image files of said actual page description language file comprises: (a) determining the total combined size of all non-rotated, non-scaled image files of said actual page description language file, thereby creating a first image size element; (b) determining the total combined size of all rotated, non-scaled image files of said actual page description language file, multiplying said total combined size by said first factor, and thereby creating a second image size element; (c) determining the total combined size of all scaled, non-rotated image files of said actual page description language file, multiplying said total combined size by said second factor, and thereby creating a third image size element; (d) determining the total combined size of all scaled and rotated image files of said actual page description language file, multiplying said total combined size by said first and second factors, and thereby creating a fourth image size element; (e) summing said first, second, third, and fourth image size elements to create a fifth image size element multiplying said fifth image size element by said raster image processing time per image file size, thereby creating a thirteenth time interval; (f) determining the total combined areas of all graduated fills of said actual page description language file, nmltiplying said total combined areas by said raster image processing time per unit graduated fill area, thereby creating a fourteenth time interval; (g) determining the total combined areas of all patterned fills of said actual page description language file, multiplying said total combined areas by said raster image processing time per unit patterned fill area, thereby creating a fifteenth time interval; (h) determining the total combined areas of all radial fills of said actual page description language file, multiplying said total combined areas by said raster image processing time per unit radial fill area, thereby creating a sixteenth time interval; and (i) summing said thirteenth, fourteenth, fifteenth, and sixteenth time intervals, thereby creating said first time period. | 0.5 |
5,577,249 | 9 | 17 | 9. A method for recognizing and accessing a reference string of tokens in one or more original token strings within a database comprising the steps of: creating one or more original tuples for each of the original token strings in the database by: a. partitioning each original token string into three or more original substrings of contiguous tokens; b. appending together two or more original substrings of the original token string to form one or more original tuples associated with the original token string, at least one original tuple being formed by appending two or more non-contiguous original substrings of the original token string; creating a unique original index for each original tuple created from the original token string by using an index algorithm, the original index being associated with the original token string from which the original tuple was created; using the original index to point to a cell in a first memory look-up structure and storing in the cell an information record associated with the original string, the information record containing pointing information used to locate the original token string in the database containing the tuple from which the original index was derived and displacement information used to determine the position of the matched reference sequence in the original token string; creating one or more reference tuples from the reference string of tokens by: c. partitioning the reference string of tokens into three or more reference substrings of contiguous tokens; d. appending together two or more reference substrings to form one or more reference tuples, at least one on the reference tuples being formed by appending together two or more non-contiguous reference substrings; creating a unique reference index for each reference tuple using the index algorithm comparing at least one reference index to at least one original index using the memory look-up structure; tracking the matches between the reference index and original index; storing the tracking results in a second memory look-up structure; selecting an original token string in the database based on the number of matches between one or more original indexes and one or more reference indexes. | 9. A method for recognizing and accessing a reference string of tokens in one or more original token strings within a database comprising the steps of: creating one or more original tuples for each of the original token strings in the database by: a. partitioning each original token string into three or more original substrings of contiguous tokens; b. appending together two or more original substrings of the original token string to form one or more original tuples associated with the original token string, at least one original tuple being formed by appending two or more non-contiguous original substrings of the original token string; creating a unique original index for each original tuple created from the original token string by using an index algorithm, the original index being associated with the original token string from which the original tuple was created; using the original index to point to a cell in a first memory look-up structure and storing in the cell an information record associated with the original string, the information record containing pointing information used to locate the original token string in the database containing the tuple from which the original index was derived and displacement information used to determine the position of the matched reference sequence in the original token string; creating one or more reference tuples from the reference string of tokens by: c. partitioning the reference string of tokens into three or more reference substrings of contiguous tokens; d. appending together two or more reference substrings to form one or more reference tuples, at least one on the reference tuples being formed by appending together two or more non-contiguous reference substrings; creating a unique reference index for each reference tuple using the index algorithm comparing at least one reference index to at least one original index using the memory look-up structure; tracking the matches between the reference index and original index; storing the tracking results in a second memory look-up structure; selecting an original token string in the database based on the number of matches between one or more original indexes and one or more reference indexes. 17. A method for recognizing and accessing a reference string of tokens in one or more original token strings within a database, as in claim 9, where the first look-up structure is a data structure that includes structures like a vector, array, and hash table. | 0.61194 |
8,489,632 | 1 | 2 | 1. A computer-implemented method comprising: receiving training data for predictive modeling; setting an ultimate time by which each of a plurality of processes executing training functions to generate respective trained predictive models is to be completed; executing the plurality of processes simultaneously in parallel to generate the trained predictive models using the training data; determining, after executing each of the plurality of processes for an initial time that is earlier than the ultimate time, a respective convergence status of each of the plurality of processes, wherein the convergence status indicates a likelihood that the process will converge, and based on the determination, identifying one or more processes that are not likely to converge, terminating processes that are not likely to converge, and allowing the remaining processes to continue executing; after the ultimate time has been reached, terminating processes that have not yet converged and generating an effectiveness score for each of a plurality of trained predictive models that were generated by the remaining processes, wherein the effectiveness score for a particular trained predictive model represents an estimation of the effectiveness of the particular trained predictive model; storing the plurality of trained predictive models in a repository of trained predictive models; receiving input data and a prediction request; selecting, for use in servicing the prediction request, a first trained predictive model from among the plurality of trained predictive models based on their respective effectiveness scores; providing the input data to the first trained predictive model; and receiving a predictive output from the first trained predictive model. | 1. A computer-implemented method comprising: receiving training data for predictive modeling; setting an ultimate time by which each of a plurality of processes executing training functions to generate respective trained predictive models is to be completed; executing the plurality of processes simultaneously in parallel to generate the trained predictive models using the training data; determining, after executing each of the plurality of processes for an initial time that is earlier than the ultimate time, a respective convergence status of each of the plurality of processes, wherein the convergence status indicates a likelihood that the process will converge, and based on the determination, identifying one or more processes that are not likely to converge, terminating processes that are not likely to converge, and allowing the remaining processes to continue executing; after the ultimate time has been reached, terminating processes that have not yet converged and generating an effectiveness score for each of a plurality of trained predictive models that were generated by the remaining processes, wherein the effectiveness score for a particular trained predictive model represents an estimation of the effectiveness of the particular trained predictive model; storing the plurality of trained predictive models in a repository of trained predictive models; receiving input data and a prediction request; selecting, for use in servicing the prediction request, a first trained predictive model from among the plurality of trained predictive models based on their respective effectiveness scores; providing the input data to the first trained predictive model; and receiving a predictive output from the first trained predictive model. 2. The method of claim 1 , wherein the training data is received from a client computing system over a network, the method further comprising: providing the client computing system access to the first trained predictive model in the repository of trained predictive models over the network. | 0.816223 |
9,262,941 | 11 | 12 | 11. The method of claim 1 , wherein one or more of the vowel space metrics are calculated based on a first vowel space characteristic, formant F 1 , and a second vowel space characteristic, formant F 2 ; wherein the vowel space metrics comprise a within category vowel space dispersion. | 11. The method of claim 1 , wherein one or more of the vowel space metrics are calculated based on a first vowel space characteristic, formant F 1 , and a second vowel space characteristic, formant F 2 ; wherein the vowel space metrics comprise a within category vowel space dispersion. 12. The method of claim 11 , wherein the within category vowel space dispersion is calculated according to: dispersion = 1 3 * ( ∑ D IY i , I Y _ N IY + ∑ D AA i , A _ A N AA + ∑ D OW i , O W _ N OW ) , where N IY is a number of IY vowel tokens, N AA is a number of AA vowel tokens, N OW is a number of OW vowel tokens, D IY i , IY is a distance from an IY vowel token i to mean F 1 and F 2 values for vowel IY, D AA i , AA is a distance from an AA vowel token i to mean F 1 and F 2 values for vowel AA, and D OW i , OW is a distance from an OW vowel token i to mean F 1 and F 2 values for vowel OW. | 0.5 |
8,364,661 | 1 | 3 | 1. A non-transitory, computer readable media having stored thereon computer executable instructions for providing a search result, the instructions performing steps comprising: parsing an input customer master file comprised of data indicative of plural item entries to discern each item entry, wherein the input customer master file is an Extensible Markup Language (XML) file or a markup language file; parsing each discerned item entry to uncover one or more keywords within each discerned item entry, the keywords being product stocking keeping units (SKUs), product parametric values, and product descriptors recognized by a search engine associated with a hardware database of a vendor; providing the uncovered keywords to the search engine associated with the hardware database device of the vendor to thereby locate for each discerned item entry having one or more keywords recognized by the search engine associated with the hardware database of the vendor one or more items in the hardware database device of the vendor; and causing the one or more items in the hardware database device of the vendor located for each discerned item entry having one or more keywords recognized by the search engine associated with the hardware database of the vendor to be returned as the search result. | 1. A non-transitory, computer readable media having stored thereon computer executable instructions for providing a search result, the instructions performing steps comprising: parsing an input customer master file comprised of data indicative of plural item entries to discern each item entry, wherein the input customer master file is an Extensible Markup Language (XML) file or a markup language file; parsing each discerned item entry to uncover one or more keywords within each discerned item entry, the keywords being product stocking keeping units (SKUs), product parametric values, and product descriptors recognized by a search engine associated with a hardware database of a vendor; providing the uncovered keywords to the search engine associated with the hardware database device of the vendor to thereby locate for each discerned item entry having one or more keywords recognized by the search engine associated with the hardware database of the vendor one or more items in the hardware database device of the vendor; and causing the one or more items in the hardware database device of the vendor located for each discerned item entry having one or more keywords recognized by the search engine associated with the hardware database of the vendor to be returned as the search result. 3. The non-transitory, computer readable media as recited in claim 1 , wherein the instructions use a catalog index to uncover one or more keywords within each discerned item entry. | 0.770886 |
8,731,617 | 12 | 13 | 12. A method for initiating voice calls from a communication device, comprising: causing, without user intervention, each number string in text of a data item which matches first predetermined criteria to be displayed in a first format and each number string in the text of the data item which does not match the first predetermined criteria to be displayed in a second format; causing a voice call to be initiated to a number string displayed in the first format when the number string is selected and first predetermined user input is detected; causing a list of user selectable functions to be displayed in response to detecting second predetermined user input when a position marker is located within a number string, the list of user selectable functions including a voice call function for initiating a voice call to the number string when the number string matches second predetermined criteria, wherein the second predetermined criteria are different from the first predetermined criteria; causing a voice call to be initiated to a number string when the voice call function for the number string is selected from the list of user selectable functions; and causing a voice call to be initiated to a number string displayed in the second format in which a position marker is located when the first predetermined user input is detected and the number string meets third predetermined criteria, wherein the third predetermined criteria are more stringent than the second predetermined criteria but less stringent than the first predetermined criteria. | 12. A method for initiating voice calls from a communication device, comprising: causing, without user intervention, each number string in text of a data item which matches first predetermined criteria to be displayed in a first format and each number string in the text of the data item which does not match the first predetermined criteria to be displayed in a second format; causing a voice call to be initiated to a number string displayed in the first format when the number string is selected and first predetermined user input is detected; causing a list of user selectable functions to be displayed in response to detecting second predetermined user input when a position marker is located within a number string, the list of user selectable functions including a voice call function for initiating a voice call to the number string when the number string matches second predetermined criteria, wherein the second predetermined criteria are different from the first predetermined criteria; causing a voice call to be initiated to a number string when the voice call function for the number string is selected from the list of user selectable functions; and causing a voice call to be initiated to a number string displayed in the second format in which a position marker is located when the first predetermined user input is detected and the number string meets third predetermined criteria, wherein the third predetermined criteria are more stringent than the second predetermined criteria but less stringent than the first predetermined criteria. 13. The method of claim 12 , wherein the first predetermined user input is actuation of a SEND key. | 0.613281 |
8,477,109 | 28 | 29 | 28. One or more non-transitory computer-readable media as recited in claim 26 , wherein the multiple different reference work entries each reside within a same category of reference work. | 28. One or more non-transitory computer-readable media as recited in claim 26 , wherein the multiple different reference work entries each reside within a same category of reference work. 29. One or more non-transitory computer-readable media as recited in claim 28 , wherein the multiple different reference work entries within the same category of reference work comprise one or more of a science reference work entry, a science-fiction reference work entry, a medical reference work entry, a business reference work entry, a legal reference work entry, a native-language reference work entry, or a non-native-language reference work entry. | 0.5 |
8,731,934 | 21 | 22 | 21. A method of data-mining a monitored telephone conversation, the method comprising: transcribing a monitored telephone conversation; extracting a plurality of characteristics of the monitored telephone conversation; associating the extracted plurality of characteristics of the monitored telephone conversation with a transcript of the monitored telephone conversation; analyzing the transcript of the monitored telephone conversation to detect one or more events within the monitored telephone conversation on a computing device following the transcription of the monitored telephone conversation; determining a topic of the monitored telephone conversation based upon querying a topic database with one or more extracted phrases from the transcript, wherein the topic database includes a slang term associated with both a major topic and a minor topic; associating metadata information indicative of the detected one or more events with the transcript of the monitored telephone conversation on a computing device; and storing at least the transcript of the monitored telephone conversation and the characteristics and metadata information associated therewith in a multimedia data warehouse as a data record for the monitored telephone conversation. | 21. A method of data-mining a monitored telephone conversation, the method comprising: transcribing a monitored telephone conversation; extracting a plurality of characteristics of the monitored telephone conversation; associating the extracted plurality of characteristics of the monitored telephone conversation with a transcript of the monitored telephone conversation; analyzing the transcript of the monitored telephone conversation to detect one or more events within the monitored telephone conversation on a computing device following the transcription of the monitored telephone conversation; determining a topic of the monitored telephone conversation based upon querying a topic database with one or more extracted phrases from the transcript, wherein the topic database includes a slang term associated with both a major topic and a minor topic; associating metadata information indicative of the detected one or more events with the transcript of the monitored telephone conversation on a computing device; and storing at least the transcript of the monitored telephone conversation and the characteristics and metadata information associated therewith in a multimedia data warehouse as a data record for the monitored telephone conversation. 22. The method according to claim 21 , further comprising: atomizing the data record for the monitored telephone conversation with respect to a plurality of data records stored within the multimedia data warehouse; and creating one or more logical links between the data record for the monitored telephone conversation and one or more of the plurality of data records stored within the multimedia data warehouse. | 0.5 |
8,694,528 | 2 | 3 | 2. The method of claim 1 , wherein analyzing a plurality of previously received search queries containing the first phrase and previously provided user interactions with the search results provided in response to the plurality of previously received search queries further comprises: determining a frequency with which previously provided user interactions are with search results that are associated with a known location relative to a frequency with which previously provided user interactions are with search results that are not associated with a known location. | 2. The method of claim 1 , wherein analyzing a plurality of previously received search queries containing the first phrase and previously provided user interactions with the search results provided in response to the plurality of previously received search queries further comprises: determining a frequency with which previously provided user interactions are with search results that are associated with a known location relative to a frequency with which previously provided user interactions are with search results that are not associated with a known location. 3. The method of claim 2 , wherein analyzing a plurality of previously received search queries containing the first phrase and previously provided user interactions with the search results provided in response to the plurality of previously received search queries further comprises: determining a distribution of the previously provided user interactions with search results as a function of the locations with which those search results are associated; and determining the location factor as a measure of the width of the distribution. | 0.5 |
8,442,812 | 18 | 35 | 18. A system for creating a recognition grammar for use with an interactive user interface to human readable text data that is also machine readable, the interactive user interface being responsive to spoken input, the system comprising: means for providing access to a phrase thesaurus database comprising a plurality of classes of phrases, wherein any two phrases that are semantic equivalent of each other are assigned to a same class; means for formulating an expression representing a part of the text data for each of one or more parts of the text data, wherein each formulated expression is constructed as one or more combinations of one or more phrases in the phrase thesaurus database; and means for automatically using the phrase thesaurus database to construct one or more equivalent expressions of each formulated expression based on assigned classes of the one or more phrases of each formulated expression, wherein the recognition grammar comprises the collection of all of the expressions. | 18. A system for creating a recognition grammar for use with an interactive user interface to human readable text data that is also machine readable, the interactive user interface being responsive to spoken input, the system comprising: means for providing access to a phrase thesaurus database comprising a plurality of classes of phrases, wherein any two phrases that are semantic equivalent of each other are assigned to a same class; means for formulating an expression representing a part of the text data for each of one or more parts of the text data, wherein each formulated expression is constructed as one or more combinations of one or more phrases in the phrase thesaurus database; and means for automatically using the phrase thesaurus database to construct one or more equivalent expressions of each formulated expression based on assigned classes of the one or more phrases of each formulated expression, wherein the recognition grammar comprises the collection of all of the expressions. 35. The system as in claim 18 , wherein the means for automatically using the phrase thesaurus database to construct equivalent phrases further comprises: means for selecting a combination of one or more phrases representing a formulated expression, wherein the phrases of the selected combination of one or more phrases are original phrases of the formulated expression; means for identifying an equivalent phrase for each of one or more original phrases of the formulated expression; and means for producing a new combination of one or more phrases representing the formulated expression, the new combination including at least one of the identified equivalent phrases, wherein the new combination represents the equivalent expression. | 0.5 |
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