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8,775,176 | 8 | 12 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: upon verifying an identity of a user: identifying, via a processor, a template for a domain associated with the user; receiving input speech from the user, the input speech comprising a substantive portion and an instructional portion, the instructional portion related to navigation between fields in the template; transcribing the substantive portion of the input speech to text, to yield transcribed text; inserting the transcribed text into the template, to yield a completed template; and storing the completed template in a database; and upon receiving a request to play a dictation for a particular word in the completed template, playing the dictation of the particular word. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: upon verifying an identity of a user: identifying, via a processor, a template for a domain associated with the user; receiving input speech from the user, the input speech comprising a substantive portion and an instructional portion, the instructional portion related to navigation between fields in the template; transcribing the substantive portion of the input speech to text, to yield transcribed text; inserting the transcribed text into the template, to yield a completed template; and storing the completed template in a database; and upon receiving a request to play a dictation for a particular word in the completed template, playing the dictation of the particular word. 12. The system of claim 8 , wherein transcribing the substantive portion of the input speech further comprises transcribing the substantive portion into a predefined document template. | 0.705128 |
9,536,200 | 4 | 5 | 4. The method of claim 3 further comprising: evaluating the plurality of entries using a source code parsing model, wherein the evaluation using the source code parsing model is based on the negative connotation found in one or more areas of negative connotation in a related source code corresponding to the software application, the evaluation using the source code parsing model generates a source code parsing model score that is used to compute the sentiment score. | 4. The method of claim 3 further comprising: evaluating the plurality of entries using a source code parsing model, wherein the evaluation using the source code parsing model is based on the negative connotation found in one or more areas of negative connotation in a related source code corresponding to the software application, the evaluation using the source code parsing model generates a source code parsing model score that is used to compute the sentiment score. 5. The method of claim 4 further comprising: receiving a set of learned model weights; using a weighted classifier to combine the learned model weights with the lexicon model score, the proximity model score, and the source code parsing model score to generate a set of sentiment scores that correspond to each of the plurality of entries; and highlighting a first set of one or more of the plurality of entries based on the set of sentiment scores corresponding to a set of highlighted entries. | 0.5 |
8,160,977 | 26 | 28 | 26. A computer program product tangibly embodied in a computer readable storage device, the computer program product for estimating a probability that a future event will occur based on user input, the computer program product comprises instructions for causing a computer to: decompose a data input stream to build a database of precursor data to build at least one predictive model; build at least one model generated by a model building process using the precursor data in the database, with the at least one model being a model that produces predictions of the likelihood of an event occurring in the future; build a statistical model of parent-child relationships from data strings in the dataset by instructions to: determine incidence values for the data strings in the dataset; concatenate the incident values with the data strings to provide child variables; analyze the child variables and the parent variables to produce statistical relationships between the child variables and a parent variable; determine probabilities values based on the determined parent child relationships; and store the at least one model in a second database that stores models, with the database being searchable to permit the at least one model in the second database to be accessed by users. | 26. A computer program product tangibly embodied in a computer readable storage device, the computer program product for estimating a probability that a future event will occur based on user input, the computer program product comprises instructions for causing a computer to: decompose a data input stream to build a database of precursor data to build at least one predictive model; build at least one model generated by a model building process using the precursor data in the database, with the at least one model being a model that produces predictions of the likelihood of an event occurring in the future; build a statistical model of parent-child relationships from data strings in the dataset by instructions to: determine incidence values for the data strings in the dataset; concatenate the incident values with the data strings to provide child variables; analyze the child variables and the parent variables to produce statistical relationships between the child variables and a parent variable; determine probabilities values based on the determined parent child relationships; and store the at least one model in a second database that stores models, with the database being searchable to permit the at least one model in the second database to be accessed by users. 28. The computer program product of claim 26 , further comprising instructions to: publish the model. | 0.765116 |
8,947,736 | 2 | 3 | 2. The method of claim 1 , further comprising: (d) after step (b) and before step (c), dividing the gray-scale document image into halftone text regions containing only halftone text characters and non-halftone text regions containing non-halftone text characters, wherein step (c) comprises binarizing each halftone text region using pixel value statistics calculated from pixels in that region only, to generate a binary map for each halftone text region. | 2. The method of claim 1 , further comprising: (d) after step (b) and before step (c), dividing the gray-scale document image into halftone text regions containing only halftone text characters and non-halftone text regions containing non-halftone text characters, wherein step (c) comprises binarizing each halftone text region using pixel value statistics calculated from pixels in that region only, to generate a binary map for each halftone text region. 3. The method of claim 2 , further comprising: (e) after step (d), binarizing each non-halftone text region using pixel value statistics calculated from pixels in that region only, to generate a binary map for each non-halftone text region. | 0.5 |
9,203,881 | 14 | 19 | 14. A method for translating entity mentions in a message to social networking sites specific identifiers when posting the message to different social networking sites, the method including: sending a message to be embedded in different social networking sites, wherein the message mentions an entity and a database is accessible that stores entity profiles with multiple handles representing the entity at the different social networking sites; receiving a list of handles or social networking sites for which the handles are known; and selecting from the list and specifying separate instances of the message to be embedded with the handles in the different social networking sites. | 14. A method for translating entity mentions in a message to social networking sites specific identifiers when posting the message to different social networking sites, the method including: sending a message to be embedded in different social networking sites, wherein the message mentions an entity and a database is accessible that stores entity profiles with multiple handles representing the entity at the different social networking sites; receiving a list of handles or social networking sites for which the handles are known; and selecting from the list and specifying separate instances of the message to be embedded with the handles in the different social networking sites. 19. The method of claim 14 , wherein the separate instances of the message are automatically embedded in the social networking sites corresponding to the multiple handles as a configuration before receiving the list of the handles or the social networking sites for which the handles are known. | 0.5 |
9,870,124 | 10 | 14 | 10. A system comprising: at least one processor; and a computer storage medium encoding computer executable instructions that, when executed by the at least one processor perform a method comprising: receiving a message from a client for sending to a recipient; including a conversation identifier in the message; sending the message to the recipient; receiving a reply message that responds to the message, the reply message including the conversation identifier from the message; receiving a request for messages related to the conversation, wherein the request includes the conversation identifier; identifying the message and the reply message using the conversation identifier; in response to the request, sending information from the message and the reply message to the client; receiving an indication that the conversation is to be ignored; in response to receiving the selection to ignore the selected conversation, performing an ignore action on the conversation, wherein the ignore action comprises removing a plurality of previously displayed e-mail messages associated with the selected conversation from display; receiving a new message related to the conversation, wherein upon receiving the indication the new message will not be displayed; receiving a selection to change an ignore status; displaying a list of ignored conversations; receiving a selection of at least one ignored conversation from the list of ignored conversations; changing the ignore status of the at least one ignored conversation; and displaying the plurality of e-mail messages that were previously removed from display. | 10. A system comprising: at least one processor; and a computer storage medium encoding computer executable instructions that, when executed by the at least one processor perform a method comprising: receiving a message from a client for sending to a recipient; including a conversation identifier in the message; sending the message to the recipient; receiving a reply message that responds to the message, the reply message including the conversation identifier from the message; receiving a request for messages related to the conversation, wherein the request includes the conversation identifier; identifying the message and the reply message using the conversation identifier; in response to the request, sending information from the message and the reply message to the client; receiving an indication that the conversation is to be ignored; in response to receiving the selection to ignore the selected conversation, performing an ignore action on the conversation, wherein the ignore action comprises removing a plurality of previously displayed e-mail messages associated with the selected conversation from display; receiving a new message related to the conversation, wherein upon receiving the indication the new message will not be displayed; receiving a selection to change an ignore status; displaying a list of ignored conversations; receiving a selection of at least one ignored conversation from the list of ignored conversations; changing the ignore status of the at least one ignored conversation; and displaying the plurality of e-mail messages that were previously removed from display. 14. The system of claim 10 , wherein the conversation identifier is a unique string of characters. | 0.829268 |
9,824,128 | 1 | 14 | 1. A distributed computer apparatus configured to perform schema-less queries of heterogeneous databases comprising: at least one registrar computer configured with database management software to register a plurality of heterogeneous databases within an information grid by storing a URL at which each of said plurality of heterogeneous databases accepts search queries; at least one search query object which contains at least two user-defined schema values that define at least one relationship between two or more of said plurality of heterogeneous databases; and at least one API processing computer which provides a user interface for a user to instantiate a search query object, of said at least one search query object, which initiates and supports a search session with the information grid, wherein the user interface is updated in real time during the search session to display available context fields, wherein the search query object invokes functions to update said user interface to display results obtained from a first heterogeneous database within the information grid which are related to search results obtained from a second heterogeneous database within the information grid, wherein at least one of the first or second heterogeneous database is a schema-less database that stores data without using any schema relationships, and wherein at least the other of the first or second heterogeneous database stores data using a schema relationship. | 1. A distributed computer apparatus configured to perform schema-less queries of heterogeneous databases comprising: at least one registrar computer configured with database management software to register a plurality of heterogeneous databases within an information grid by storing a URL at which each of said plurality of heterogeneous databases accepts search queries; at least one search query object which contains at least two user-defined schema values that define at least one relationship between two or more of said plurality of heterogeneous databases; and at least one API processing computer which provides a user interface for a user to instantiate a search query object, of said at least one search query object, which initiates and supports a search session with the information grid, wherein the user interface is updated in real time during the search session to display available context fields, wherein the search query object invokes functions to update said user interface to display results obtained from a first heterogeneous database within the information grid which are related to search results obtained from a second heterogeneous database within the information grid, wherein at least one of the first or second heterogeneous database is a schema-less database that stores data without using any schema relationships, and wherein at least the other of the first or second heterogeneous database stores data using a schema relationship. 14. The distributed computer apparatus of claim 1 , wherein a plurality of said search results are used as a search key in a subsequent search of said plurality of heterogeneous databases. | 0.718563 |
8,935,278 | 1 | 2 | 1. A method for searching a web service registry system by use of a search controller, said method comprising: performing, by a processor of a computer system, a first search of a service registry program product with a service name received by the search controller from a user of the web service registry system, wherein the web service registry system comprises a search module and the service registry program product, wherein the search module comprises the search controller, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; after said performing the first search, said processor determining that the received service name does not have a service description associated with the received service name in the service registry program product; said processor coordinating a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and said processor discovering that the service description is associated with the candidate service name within the service registry program product and subsequently returning the discovered service description to the user, said coordinating comprising: determining, from the received service name, a component word list that includes all words constituting the received service name; determining, from the component word list, a respective synonym list for each word in the component word list, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; determining, from the respective synonym list for each word in the component word list, the candidate service name; and sending a second search request for the service description associated with the candidate service name to the service registry program product and subsequently receiving the service description in response to the second search request. | 1. A method for searching a web service registry system by use of a search controller, said method comprising: performing, by a processor of a computer system, a first search of a service registry program product with a service name received by the search controller from a user of the web service registry system, wherein the web service registry system comprises a search module and the service registry program product, wherein the search module comprises the search controller, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; after said performing the first search, said processor determining that the received service name does not have a service description associated with the received service name in the service registry program product; said processor coordinating a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and said processor discovering that the service description is associated with the candidate service name within the service registry program product and subsequently returning the discovered service description to the user, said coordinating comprising: determining, from the received service name, a component word list that includes all words constituting the received service name; determining, from the component word list, a respective synonym list for each word in the component word list, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; determining, from the respective synonym list for each word in the component word list, the candidate service name; and sending a second search request for the service description associated with the candidate service name to the service registry program product and subsequently receiving the service description in response to the second search request. 2. The method of claim 1 , said performing the first search comprising: sending a first search request for the service description associated with the received service name to the service registry program product; and receiving a null from the service registry program product in response to the first search request, wherein the service registry program product returns the null upon failing to find the service description associated with the received service name. | 0.776555 |
8,543,715 | 3 | 4 | 3. The method of claim 2 , wherein the frame element is an inline frame element. | 3. The method of claim 2 , wherein the frame element is an inline frame element. 4. The method of claim 3 , wherein the inline frame element is associated with a third-party content delivery system. | 0.5 |
10,038,730 | 14 | 15 | 14. The method of claim 12 , wherein the web meeting identifier further defines characteristics inherited by each instance thereof, the characteristics being defined by a custom template from which the web meeting identifier was cloned. | 14. The method of claim 12 , wherein the web meeting identifier further defines characteristics inherited by each instance thereof, the characteristics being defined by a custom template from which the web meeting identifier was cloned. 15. The method of claim 14 , wherein the characteristics include at least one of a predefined annotating input, a title, a font, and a formatting parameter. | 0.5 |
8,364,509 | 1 | 67 | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. 67. The method of claim 1 , wherein receiving at least one query includes receiving at least one query for at least one report listing respective grades for a plurality of respective agents on the individual agent-basis or the group-level agent-basis, all of which agents support one given client. | 0.598649 |
9,953,636 | 1 | 6 | 1. A method comprising: accessing a baseline language model that associates a respective baseline probability of occurrence with each of multiple different terms; obtaining information related to recent language usage from recent search queries that were submitted by multiple users of a search engine within a predetermined period of time; determining a quantity of occurrences of a particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; selectively modifying the baseline language model to independently revise the baseline probability of occurrence associated with the particular term based at least on the quantity of occurrences of the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time while maintaining unchanged a baseline probability of occurrence associated with a different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time by assigning a first probability to the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time that is greater than a second probability for the different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; and generating, by an automated speech recognizer using the modified language model, a transcription of one or more utterances of one or more different users of the search engine. | 1. A method comprising: accessing a baseline language model that associates a respective baseline probability of occurrence with each of multiple different terms; obtaining information related to recent language usage from recent search queries that were submitted by multiple users of a search engine within a predetermined period of time; determining a quantity of occurrences of a particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; selectively modifying the baseline language model to independently revise the baseline probability of occurrence associated with the particular term based at least on the quantity of occurrences of the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time while maintaining unchanged a baseline probability of occurrence associated with a different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time by assigning a first probability to the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time that is greater than a second probability for the different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; and generating, by an automated speech recognizer using the modified language model, a transcription of one or more utterances of one or more different users of the search engine. 6. The method of claim 1 , further comprising receiving a verbal command for an application that is associated, using a recognizer implementing the language model, with a text command. | 0.525773 |
8,688,603 | 25 | 34 | 25. A computer-readable storage medium, storing program instructions computer-executable on a computer to implement a genetic rule generator configured to: based on reference data that includes pairs of information items and labels that each indicate whether a given pair of information items have a specific relationship, generate a first machine learning model for determining whether pairs of information items have said specific relationship; identify one or more false positive pairs, wherein a given false positive pair is a pair of information items that the first machine learning model indicates as having said specific relationship and which are labeled within the reference data as not having said specific relationship; generate an indication of one or more of the identified false positive pairs as candidates to be corrected within the reference data. | 25. A computer-readable storage medium, storing program instructions computer-executable on a computer to implement a genetic rule generator configured to: based on reference data that includes pairs of information items and labels that each indicate whether a given pair of information items have a specific relationship, generate a first machine learning model for determining whether pairs of information items have said specific relationship; identify one or more false positive pairs, wherein a given false positive pair is a pair of information items that the first machine learning model indicates as having said specific relationship and which are labeled within the reference data as not having said specific relationship; generate an indication of one or more of the identified false positive pairs as candidates to be corrected within the reference data. 34. The medium of claim 25 , wherein the first machine learning model is a support vector machine (SVM) model including slack variables associated with different pairs of information items mapped in a hyperspace, wherein the program instructions are configured to, based on the slack variables, select one or more false positive pairs as candidates to be corrected. | 0.688567 |
9,904,732 | 1 | 4 | 1. A method of improving the way a computer performs an internet search comprising the steps of: a) providing an index server maintaining dynamic indices to internet web pages and employing a preexisting plurality of topic categories whose contents, including topics and links not provided by a particular end user, are maintained and updated by the index server without end user intervention being required, wherein a master index is maintained as well as an end user's index for each user as customized by each user; b) updating the end user's index to include any subset of the plurality of topic categories specified by the end user; c) adding to an electronic medium controlled by the end user link information permitting execution of searches of the index server in any category of the subset but only of categories in the subset; d) permitting the end user to propose addition of an internet web page to the master index in conjunction with one or more categories of the subset; and e) automatically adding the proposed page to the end user's index wherein the end user can search the proposed page via the link information and wherein initially other users will not search the proposed page even if searching the proposed one or more categories; and wherein the index server updates web pages in the topic categories of the master index and the end user's index without any end user intervention and permits the end user to create and organize search indexes specific to the end user's needs. | 1. A method of improving the way a computer performs an internet search comprising the steps of: a) providing an index server maintaining dynamic indices to internet web pages and employing a preexisting plurality of topic categories whose contents, including topics and links not provided by a particular end user, are maintained and updated by the index server without end user intervention being required, wherein a master index is maintained as well as an end user's index for each user as customized by each user; b) updating the end user's index to include any subset of the plurality of topic categories specified by the end user; c) adding to an electronic medium controlled by the end user link information permitting execution of searches of the index server in any category of the subset but only of categories in the subset; d) permitting the end user to propose addition of an internet web page to the master index in conjunction with one or more categories of the subset; and e) automatically adding the proposed page to the end user's index wherein the end user can search the proposed page via the link information and wherein initially other users will not search the proposed page even if searching the proposed one or more categories; and wherein the index server updates web pages in the topic categories of the master index and the end user's index without any end user intervention and permits the end user to create and organize search indexes specific to the end user's needs. 4. The method of claim 1 additionally comprising the step of allowing the end user to rename one or more categories of the subset as it will appear on the electronic medium controlled by the end user. | 0.6139 |
9,009,256 | 5 | 6 | 5. A system comprising: a data store; and at least one computing device in communication with the data store, the at least one computing device configured to at least: retrieve a plurality of text blocks from a network site, wherein each text block of the plurality of text blocks corresponds to a respective user of a plurality of users; employ a text classifier for generating a binary result for each text block of the plurality of text blocks, wherein the text classifier is configured to be trained by feedback and the binary result indicates whether a content of the text block expresses an actionable user concern capable of being addressed by a customer service agent; and associate, with a queue, a representation of each text block of the plurality of text blocks having content that expresses the actionable user concern as indicated by the binary result for the text block. | 5. A system comprising: a data store; and at least one computing device in communication with the data store, the at least one computing device configured to at least: retrieve a plurality of text blocks from a network site, wherein each text block of the plurality of text blocks corresponds to a respective user of a plurality of users; employ a text classifier for generating a binary result for each text block of the plurality of text blocks, wherein the text classifier is configured to be trained by feedback and the binary result indicates whether a content of the text block expresses an actionable user concern capable of being addressed by a customer service agent; and associate, with a queue, a representation of each text block of the plurality of text blocks having content that expresses the actionable user concern as indicated by the binary result for the text block. 6. The system of claim 5 , wherein the at least one computing device is further configured to at least structure the plurality of text blocks for maintaining a relationship among the plurality of text blocks. | 0.566667 |
9,697,184 | 2 | 3 | 2. The method according to claim 1 , further comprising: comparing the average precision P with a second reference value M, and when P≧M, decreasing the layout size of the target hyperlink by an amount commensurate with an adjustment value in a predetermined step based on the adjustment parameter. | 2. The method according to claim 1 , further comprising: comparing the average precision P with a second reference value M, and when P≧M, decreasing the layout size of the target hyperlink by an amount commensurate with an adjustment value in a predetermined step based on the adjustment parameter. 3. The method according to claim 2 , wherein the larger the difference between the average precision P and the reference value N is, or the larger the difference between the average precision P and the second reference value M is, the larger the predetermined step is. | 0.5 |
7,636,700 | 10 | 11 | 10. An object recognition system incorporating swarming domain classifiers as set forth in claim 9 , wherein the multi-dimensional solution space consists of the dimensions (x, y, z), size, scale, internal classifier parameters, object rotation angle, and time. | 10. An object recognition system incorporating swarming domain classifiers as set forth in claim 9 , wherein the multi-dimensional solution space consists of the dimensions (x, y, z), size, scale, internal classifier parameters, object rotation angle, and time. 11. An object recognition system incorporating swarming domain classifiers as set forth in claim 10 , wherein the domain is a domain selected from a group consisting of an image, space, frequency, time, Doppler shift, time delay, wave length, and phase. | 0.5 |
8,161,114 | 1 | 8 | 1. A method for transmitting information by a processor, comprising the steps of: using a data structure that is defined by a formal language called Abstract Syntax Notation One; transmitting the information encoded as plain text; and transmitting a designation of a data type with each piece of the transmitted information, the designation of the data type being defined by the formal language called Abstract Syntax Notation One, wherein the encoded text is decoded without accessing a reference to an Abstract Syntax Notation One definition internal to an application. | 1. A method for transmitting information by a processor, comprising the steps of: using a data structure that is defined by a formal language called Abstract Syntax Notation One; transmitting the information encoded as plain text; and transmitting a designation of a data type with each piece of the transmitted information, the designation of the data type being defined by the formal language called Abstract Syntax Notation One, wherein the encoded text is decoded without accessing a reference to an Abstract Syntax Notation One definition internal to an application. 8. The method according to claim 1 , further comprising the step of: using encoding tables, the encoding tables being adaptable to character sets of transmitting systems. | 0.716667 |
9,449,598 | 16 | 22 | 16. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: obtaining audio data corresponding to an utterance; initiating speech recognition on the audio data using a grammar, wherein speech recognition using the grammar proceeds to at least a first state of the grammar, wherein the first state of the grammar is linked to a second state of the grammar and a first state of a statistical language model, and wherein individual links between the grammar and the statistical language model are configured to bias speech recognition to use the grammar over the statistical language model; determining a first score and a second score, wherein the first score is determined using a weight associated with a link from the first state of the grammar to the second state of the grammar; if the first score is greater than the second score, continuing speech recognition on the audio data using the second state of the grammar; and if the second score is greater than the first score, continuing speech recognition on the audio data using the first state of the statistical language model, wherein speech recognition using the statistical language model is based at least in part on a score associated with the correspondence between the first state of the grammar and the first state of the statistical language model. | 16. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: obtaining audio data corresponding to an utterance; initiating speech recognition on the audio data using a grammar, wherein speech recognition using the grammar proceeds to at least a first state of the grammar, wherein the first state of the grammar is linked to a second state of the grammar and a first state of a statistical language model, and wherein individual links between the grammar and the statistical language model are configured to bias speech recognition to use the grammar over the statistical language model; determining a first score and a second score, wherein the first score is determined using a weight associated with a link from the first state of the grammar to the second state of the grammar; if the first score is greater than the second score, continuing speech recognition on the audio data using the second state of the grammar; and if the second score is greater than the first score, continuing speech recognition on the audio data using the first state of the statistical language model, wherein speech recognition using the statistical language model is based at least in part on a score associated with the correspondence between the first state of the grammar and the first state of the statistical language model. 22. The one or more non-transitory computer readable media of claim 16 , the process further comprising: obtaining second audio data corresponding to a second utterance; performing speech recognition on the second utterance exclusively with the grammar. | 0.766605 |
9,495,964 | 8 | 13 | 8. A system comprising: a processor; and a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising: comparing a transcription of a media presentation to a list of anchor word candidates to identify a pair of anchor words separated from one another within the media presentation by a time greater than an anchor word time duration requirement; and generating captions by aligning the transcription with an automatic speech recognition output of the media presentation according to the pair of anchor words. | 8. A system comprising: a processor; and a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising: comparing a transcription of a media presentation to a list of anchor word candidates to identify a pair of anchor words separated from one another within the media presentation by a time greater than an anchor word time duration requirement; and generating captions by aligning the transcription with an automatic speech recognition output of the media presentation according to the pair of anchor words. 13. The system of claim 8 , wherein the media presentation is in real-time, and wherein the computer-readable storage device stores further instructions which, when executed by the processor, cause the processor to perform an operation further comprising: buffering the captions based on the media presentation and the aligning of the transcription to yield buffered caption; and outputting a delayed media presentation and the buffered captions together. | 0.5 |
7,599,899 | 5 | 6 | 5. A computer implemented method of creating a prose style of a user, for the purpose of applying said prose style to an information of interest in a given context, comprising the steps of: providing equivalent name sets; deriving a plurality of preferred equivalent name set entries from said equivalent name sets for said given context; providing a plurality of equivalent pattern specification sets; deriving a preferred pattern specification set from said equivalent pattern specification sets for the given context; and creating said prose style based on said preferred equivalent name set entries and said preferred pattern specification sets. | 5. A computer implemented method of creating a prose style of a user, for the purpose of applying said prose style to an information of interest in a given context, comprising the steps of: providing equivalent name sets; deriving a plurality of preferred equivalent name set entries from said equivalent name sets for said given context; providing a plurality of equivalent pattern specification sets; deriving a preferred pattern specification set from said equivalent pattern specification sets for the given context; and creating said prose style based on said preferred equivalent name set entries and said preferred pattern specification sets. 6. The computer implemented method of claim 5 , wherein said equivalent name set is captured in the process of capturing the reading style of the user. | 0.818945 |
7,650,633 | 7 | 10 | 7. A computer program product comprising a computer-useable medium having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: accessing existing permissions granted to users in an organizational environment; analyzing the permissions to create permission characteristics; performing cladistics analysis on the permission characteristics to determine role perspective relationships between individual users of the organizational environment; and generating a role based access control model for the organizational environment based on the determined role perspective relationships between individual users of the organizational environment. | 7. A computer program product comprising a computer-useable medium having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: accessing existing permissions granted to users in an organizational environment; analyzing the permissions to create permission characteristics; performing cladistics analysis on the permission characteristics to determine role perspective relationships between individual users of the organizational environment; and generating a role based access control model for the organizational environment based on the determined role perspective relationships between individual users of the organizational environment. 10. The computer program product of claim 7 , wherein the role based access control model is a hierarchical role based access control model. | 0.668246 |
7,689,580 | 24 | 30 | 24. A framework embodied in a computer-readable storage medium for enabling at least one application to be searched, the framework comprising: an interface, the interface being arranged to translate a query from a first format to a query of a second format, the interface further being arranged to be associated with a canonical business object associated with the at least one application; a search engine, the search engine being arranged to search the at least one application in response to the query of the second format; an index store, wherein a result of the query of the second format is indicated in the index store and is accessed using the search engine; a runtime manager, the runtime manager being arranged to interface the search engine with the at least one application, wherein the interface is further arranged to cause the result of the query of the second format to be displayed and a link to invoke the at least one application to be displayed; and a display device, the display device being arranged to display a result associated with the query. | 24. A framework embodied in a computer-readable storage medium for enabling at least one application to be searched, the framework comprising: an interface, the interface being arranged to translate a query from a first format to a query of a second format, the interface further being arranged to be associated with a canonical business object associated with the at least one application; a search engine, the search engine being arranged to search the at least one application in response to the query of the second format; an index store, wherein a result of the query of the second format is indicated in the index store and is accessed using the search engine; a runtime manager, the runtime manager being arranged to interface the search engine with the at least one application, wherein the interface is further arranged to cause the result of the query of the second format to be displayed and a link to invoke the at least one application to be displayed; and a display device, the display device being arranged to display a result associated with the query. 30. The framework of claim 24 further including a metadata arrangement, the metadata arrangement being arranged to store the canonical business object. | 0.648837 |
7,707,160 | 8 | 9 | 8. The computer system of claim 7 wherein the web browser is operable to display a summary information screen providing general information on a named object using a portion of the factual knowledge retrieved from the knowledge base. | 8. The computer system of claim 7 wherein the web browser is operable to display a summary information screen providing general information on a named object using a portion of the factual knowledge retrieved from the knowledge base. 9. The computer system of claim 8 wherein the summary information screen includes a link corresponding to each named object which generate further summary information screens when the link is activated. | 0.5 |
9,195,942 | 12 | 13 | 12. A computer-readable storage medium containing instructions for controlling a computer system to provide information about people, by a method comprising: providing an indication of people that have relationships to objects; clustering the people into people clusters based on the people having relationships to the same objects by creating initial clusters of people based on their relationships to the same objects and combining clusters of people that are most closely related based on their relationships to the same objects until a target number of clusters remain, wherein the clustering of people includes generating an object vector for each person, the object vector identifying objects with which the person has a relationship, wherein the clustering is based on distance between the object vectors; for people clusters, identifying object clusters of related objects from the objects with which the people of the people cluster have a relationship; and providing an indication of people of a people cluster and an indication of object clusters for that people cluster. | 12. A computer-readable storage medium containing instructions for controlling a computer system to provide information about people, by a method comprising: providing an indication of people that have relationships to objects; clustering the people into people clusters based on the people having relationships to the same objects by creating initial clusters of people based on their relationships to the same objects and combining clusters of people that are most closely related based on their relationships to the same objects until a target number of clusters remain, wherein the clustering of people includes generating an object vector for each person, the object vector identifying objects with which the person has a relationship, wherein the clustering is based on distance between the object vectors; for people clusters, identifying object clusters of related objects from the objects with which the people of the people cluster have a relationship; and providing an indication of people of a people cluster and an indication of object clusters for that people cluster. 13. The computer-readable storage medium of claim 12 including generating a description of a topic of the objects of an object cluster. | 0.5 |
8,549,467 | 1 | 2 | 1. A computerized method comprising: modeling a software system having pairs of coupled software components to yield a platform-independent model of pairs of respective platform-independent software component models, such that each software component model being a placeholder associated with a respective variable set of concrete platform-specific software components; applying a materialization process to the platform-independent model to yield a platform-specific model by selecting respective concrete platform-specific software components for at least some of the software component models; analyzing using a processor the platform-specific model to identify automatically mismatched pairs of concrete -platform-specific software components; automatically re-modeling the platform-specific model such that each automatically identified mismatched pair becomes coupled together via a configurable glue component model which comprises interface maps usable to eliminate the mismatch; configuring the respective glue component model of each of the mismatched pairs by determining, in response to a feedback from a user, at least: the interface maps, method maps associated with the_determined interface maps, parameter maps associated with the determined methods, and code snippets associated with at least one of the determined interface maps, the determined method maps, and the determined parameter maps; and transforming each configured glue component model into a computer code in the platform-specific language to eliminate the respective mismatch, said glue component model is transformed by assembling all determined code snippets into a single piece of code. | 1. A computerized method comprising: modeling a software system having pairs of coupled software components to yield a platform-independent model of pairs of respective platform-independent software component models, such that each software component model being a placeholder associated with a respective variable set of concrete platform-specific software components; applying a materialization process to the platform-independent model to yield a platform-specific model by selecting respective concrete platform-specific software components for at least some of the software component models; analyzing using a processor the platform-specific model to identify automatically mismatched pairs of concrete -platform-specific software components; automatically re-modeling the platform-specific model such that each automatically identified mismatched pair becomes coupled together via a configurable glue component model which comprises interface maps usable to eliminate the mismatch; configuring the respective glue component model of each of the mismatched pairs by determining, in response to a feedback from a user, at least: the interface maps, method maps associated with the_determined interface maps, parameter maps associated with the determined methods, and code snippets associated with at least one of the determined interface maps, the determined method maps, and the determined parameter maps; and transforming each configured glue component model into a computer code in the platform-specific language to eliminate the respective mismatch, said glue component model is transformed by assembling all determined code snippets into a single piece of code. 2. The computerized method according to claim 1 , wherein the configuring further comprises determining, for each component, respective initialization and message-exchange support. | 0.770992 |
7,543,270 | 1 | 4 | 1. In an electronic device, a method comprising: receiving a textual input description, the input description including text to be displayed and a first set of textual cross-references associated with segments of the text to be displayed, each textual cross-reference including one or more textual identifiers for the associated segment of the text to be displayed; receiving a textual output description, the output description including text to be displayed and a second set of textual cross-references associated with segments of the text to be displayed, each textual cross-reference including one or more textual identifiers for the associated segment of the text to be displayed; identifying a first cross-reference in the first set of cross-references associated with a segment of the text to be displayed in the input description using the electronic device; searching the second set of cross-references in the output description to identify a second cross-reference that matches the first cross-reference using the electronic device, the second cross-reference matching the first cross-reference when at least one identifier in the second cross-reference matches at least one identifier in the first cross-reference, the second cross-reference being associated with a segment of the text to be displayed in the output description that corresponds to the segment of the text to be displayed in the input description; and displaying the segment of the text to be displayed in the input description and the segment of the text to be displayed in the output description together on a display. | 1. In an electronic device, a method comprising: receiving a textual input description, the input description including text to be displayed and a first set of textual cross-references associated with segments of the text to be displayed, each textual cross-reference including one or more textual identifiers for the associated segment of the text to be displayed; receiving a textual output description, the output description including text to be displayed and a second set of textual cross-references associated with segments of the text to be displayed, each textual cross-reference including one or more textual identifiers for the associated segment of the text to be displayed; identifying a first cross-reference in the first set of cross-references associated with a segment of the text to be displayed in the input description using the electronic device; searching the second set of cross-references in the output description to identify a second cross-reference that matches the first cross-reference using the electronic device, the second cross-reference matching the first cross-reference when at least one identifier in the second cross-reference matches at least one identifier in the first cross-reference, the second cross-reference being associated with a segment of the text to be displayed in the output description that corresponds to the segment of the text to be displayed in the input description; and displaying the segment of the text to be displayed in the input description and the segment of the text to be displayed in the output description together on a display. 4. The method of claim 1 wherein the input description and the output description are displayed in separate panes of a same window. | 0.653439 |
9,298,852 | 1 | 5 | 1. 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 a query prefix from a user; obtaining query completions for the query prefix, each query completion having a respective ranking score, the query completions having a first ranking based on the ranking scores; obtaining a reference query for the user; identifying matching user activity sessions, the matching user activity sessions being user activity session that each include an occurrence of the reference query; identifying one or more likely queries, the likely queries being queries that occur in the matching user activity sessions, wherein each of the likely queries is associated with a respective likelihood score, wherein the likelihood score represents a likelihood of the likely query occurring in the matching user activity sessions relative to a likelihood of the likely query occurring over all user activity sessions; designating, as a matching query completion, a first query completion of the query completions that matches a first likely query of the one or more likely queries; boosting the ranking score for the matching query completion by an amount based on the likelihood score associated with the first likely query; determining a modified ranking of the query completions using the boosted ranking score of the matching query completion; and providing the modified ranking of the query completions in response to receiving the query prefix. | 1. 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 a query prefix from a user; obtaining query completions for the query prefix, each query completion having a respective ranking score, the query completions having a first ranking based on the ranking scores; obtaining a reference query for the user; identifying matching user activity sessions, the matching user activity sessions being user activity session that each include an occurrence of the reference query; identifying one or more likely queries, the likely queries being queries that occur in the matching user activity sessions, wherein each of the likely queries is associated with a respective likelihood score, wherein the likelihood score represents a likelihood of the likely query occurring in the matching user activity sessions relative to a likelihood of the likely query occurring over all user activity sessions; designating, as a matching query completion, a first query completion of the query completions that matches a first likely query of the one or more likely queries; boosting the ranking score for the matching query completion by an amount based on the likelihood score associated with the first likely query; determining a modified ranking of the query completions using the boosted ranking score of the matching query completion; and providing the modified ranking of the query completions in response to receiving the query prefix. 5. The system of claim 1 , wherein identifying the one or more likely queries comprises: identifying the one or more likely queries using user activity sessions for at least a threshold number of users, wherein a user activity session describes activity of a particular user over a particular time period. | 0.566761 |
9,826,056 | 12 | 14 | 12. A method comprising: sending for display to a target user of a social networking system a news ticker presenting a plurality of stories each describing an action performed by a user of the social networking system connected to the target user and identifying the user performing the action, each of the plurality of stories associated with an action, the news ticker including stories associated with a threshold number of actions, the threshold number of story types comprising a plurality of story types, the news ticker comprising a graphical user interface; detecting, by an action interface module, one or more actions performed by acting users connected to the target user after the news ticker is sent to the target user, the action interface module configured to detect and store actions performed by acting users of the social networking system in real time; retrieving, by the news ticker computing system, candidate stories each describing a detected action performed by an acting user connected to the target user; selecting, by the news ticker computing system, a candidate story associated with an action for inclusion in an updated news ticker such that the updated news ticker includes at least the threshold number of actions; without receiving an input from the target user, modifying, by the news ticker computing system, a presentation of stories within the news ticker to include the selected candidate story, to remove an existing story from the presentation of stories within the news ticker associated with the same story type as the selected candidate story, and such that the presentation of stories within the news ticker includes at least the threshold number of story types to generate the updated news ticker; and sending the updated news ticker including the selected candidate story for display to the target user. | 12. A method comprising: sending for display to a target user of a social networking system a news ticker presenting a plurality of stories each describing an action performed by a user of the social networking system connected to the target user and identifying the user performing the action, each of the plurality of stories associated with an action, the news ticker including stories associated with a threshold number of actions, the threshold number of story types comprising a plurality of story types, the news ticker comprising a graphical user interface; detecting, by an action interface module, one or more actions performed by acting users connected to the target user after the news ticker is sent to the target user, the action interface module configured to detect and store actions performed by acting users of the social networking system in real time; retrieving, by the news ticker computing system, candidate stories each describing a detected action performed by an acting user connected to the target user; selecting, by the news ticker computing system, a candidate story associated with an action for inclusion in an updated news ticker such that the updated news ticker includes at least the threshold number of actions; without receiving an input from the target user, modifying, by the news ticker computing system, a presentation of stories within the news ticker to include the selected candidate story, to remove an existing story from the presentation of stories within the news ticker associated with the same story type as the selected candidate story, and such that the presentation of stories within the news ticker includes at least the threshold number of story types to generate the updated news ticker; and sending the updated news ticker including the selected candidate story for display to the target user. 14. The method of claim 12 , wherein selecting the candidate story associated with an action comprises: selecting, by the news ticker computing system, a candidate story associated with an action having a specified type such that at least a threshold number of types of actions are associated with stories included in the updated news ticker. | 0.601399 |
8,285,750 | 15 | 20 | 15. A computer-implemented method of automatically analyzing text documents in which a computer performs the following steps in the order recited: receiving a subject text document; comparing the text of the subject text document or the text of a subset of the subject text document to the text of a plurality of given text templates, each text template containing at least one paragraph of text; determining which given text template or text templates has text that matches the text of the subject text document or the text of the subset of the subject test document to a given degree of correspondence; and generating a report of the differences between the text of the subject text document or the text of the subset of the subject text document and the text of the matching text template or text templates. | 15. A computer-implemented method of automatically analyzing text documents in which a computer performs the following steps in the order recited: receiving a subject text document; comparing the text of the subject text document or the text of a subset of the subject text document to the text of a plurality of given text templates, each text template containing at least one paragraph of text; determining which given text template or text templates has text that matches the text of the subject text document or the text of the subset of the subject test document to a given degree of correspondence; and generating a report of the differences between the text of the subject text document or the text of the subset of the subject text document and the text of the matching text template or text templates. 20. The computer-implemented method of claim 15 wherein the determining matches to a degree of correspondence uses a longest common subsequence algorithm. | 0.839917 |
7,818,658 | 39 | 52 | 39. A multimedia presentation system, comprising: a first data store that stores a plurality of content assets and a presentation script, the presentation script including: instructions that include identification of a content asset, identification of one or more visual displays in which the identified content asset is to be included, one or more modifications of the content asset to be performed prior to inclusion of the identified content asset in the one or more visual displays, instructions for positioning the modified content asset in the one or more visual displays, and layering instructions for determining, for a portion of the visual display that includes plurality of modified content assets, the forward and backward relation of the plurality of modified assets to each other in the visual display; a first processor coupled to the first data store, the first processor configured to: allow a first user to create a multimedia presentation that includes a sequence of visual frames, using a user interface comprising a defined set of characteristics, the multimedia presentation being stored on the first data store as a presentation script and content assets identified in the presentation script; a second data store that stores the multimedia presentation; and a second processor coupled to the second data store, the second processor configured to: generate a displayed multimedia presentation using the stored multimedia presentation; and allow a second user to edit the stored multimedia presentation to create a second multimedia presentation using a user interface comprising the defined set of characteristics. | 39. A multimedia presentation system, comprising: a first data store that stores a plurality of content assets and a presentation script, the presentation script including: instructions that include identification of a content asset, identification of one or more visual displays in which the identified content asset is to be included, one or more modifications of the content asset to be performed prior to inclusion of the identified content asset in the one or more visual displays, instructions for positioning the modified content asset in the one or more visual displays, and layering instructions for determining, for a portion of the visual display that includes plurality of modified content assets, the forward and backward relation of the plurality of modified assets to each other in the visual display; a first processor coupled to the first data store, the first processor configured to: allow a first user to create a multimedia presentation that includes a sequence of visual frames, using a user interface comprising a defined set of characteristics, the multimedia presentation being stored on the first data store as a presentation script and content assets identified in the presentation script; a second data store that stores the multimedia presentation; and a second processor coupled to the second data store, the second processor configured to: generate a displayed multimedia presentation using the stored multimedia presentation; and allow a second user to edit the stored multimedia presentation to create a second multimedia presentation using a user interface comprising the defined set of characteristics. 52. The multimedia presentation system of claim 39 , wherein the multimedia presentation is stored in a format compatible with the first processor and the second processor on the first data store and the second data store. | 0.781065 |
8,825,468 | 5 | 13 | 5. The apparatus of claim 1 wherein the control output is further a control command enabling control of the at least one host computing device, and the controller further configured to provide control instructions to the display, the microphone, and the speaker in a format for interacting in a visual and audio manner in response to the control commands, the format being associated with an avatar. | 5. The apparatus of claim 1 wherein the control output is further a control command enabling control of the at least one host computing device, and the controller further configured to provide control instructions to the display, the microphone, and the speaker in a format for interacting in a visual and audio manner in response to the control commands, the format being associated with an avatar. 13. The apparatus of claim 5 wherein the wireless interface is further configured to communicate with at least one remote device to receive a software application including at least one different avatar. | 0.614068 |
7,921,137 | 1 | 2 | 1. A computer-implemented method for managing documents implemented in a business processing chain, comprising: receiving a request to generate a document for electronic publication with a computer processor; determining a first object to be included in the document, the first object having characteristics; classifying the characteristics of the first object into a plurality of classes; describing a characteristic of the first object with a first semantic primitive, the first semantic primitive; identifying at least one class among a plurality of classes; wherein, each class among the plurality of classes is stored as metadata defining a document definition associated with the document; determining whether at least one characteristic of the first object belongs to the class identified by the first semantic primitive and whether or not there is a constraint on the use of the first object in the document; wherein when a constraint on the use of the first object in the document or a document template exists, a message is generated indicating a conflict and, wherein when a constraint on the use of the first object in the document or the document template does not exist, metadata associated with the first object and the first semantic primitive is used in generating a document model; generating a first document model, based on a result of the determination of the constraints and the document definition; publishing the document to a computer display using the computer processor, wherein updates to the first document model and document definition are reflected in the document when the document is published; receiving a request to modify the first object based on information associated with the business processing chain; modifying the first semantic primitive describing a characteristic of the first object and the document definition based on the request; modifying subsequent publications of the document based on the modified document definition; receiving a request to publish a second document associated with a second document model referencing the first object; and publishing the second document based on a second document model, the second document being published based on the modifications to the first object. | 1. A computer-implemented method for managing documents implemented in a business processing chain, comprising: receiving a request to generate a document for electronic publication with a computer processor; determining a first object to be included in the document, the first object having characteristics; classifying the characteristics of the first object into a plurality of classes; describing a characteristic of the first object with a first semantic primitive, the first semantic primitive; identifying at least one class among a plurality of classes; wherein, each class among the plurality of classes is stored as metadata defining a document definition associated with the document; determining whether at least one characteristic of the first object belongs to the class identified by the first semantic primitive and whether or not there is a constraint on the use of the first object in the document; wherein when a constraint on the use of the first object in the document or a document template exists, a message is generated indicating a conflict and, wherein when a constraint on the use of the first object in the document or the document template does not exist, metadata associated with the first object and the first semantic primitive is used in generating a document model; generating a first document model, based on a result of the determination of the constraints and the document definition; publishing the document to a computer display using the computer processor, wherein updates to the first document model and document definition are reflected in the document when the document is published; receiving a request to modify the first object based on information associated with the business processing chain; modifying the first semantic primitive describing a characteristic of the first object and the document definition based on the request; modifying subsequent publications of the document based on the modified document definition; receiving a request to publish a second document associated with a second document model referencing the first object; and publishing the second document based on a second document model, the second document being published based on the modifications to the first object. 2. The computer-implemented method of claim 1 , wherein the document is published without the first object based on determining that the first semantic primitive reflects a constraint on using the first object in the first document. | 0.746171 |
9,569,593 | 1 | 30 | 1. A method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a surgical procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the surgical procedure; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the surgical procedure, at least in part by automatically extracting one or more clinical facts from the transcribed audio data using a fact extraction component implemented via at least one processor, to identify relevant information for documenting the surgical procedure, wherein analyzing the transcribed audio data comprises identifying within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the surgical procedure; automatically generating a text report including the relevant information documenting the surgical procedure, wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense text portion in the report, stating that the particular step of the surgical procedure was performed; and outputting the automatically generated text report for review via a user interface on an audio and/or visual display device. | 1. A method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a surgical procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the surgical procedure; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the surgical procedure, at least in part by automatically extracting one or more clinical facts from the transcribed audio data using a fact extraction component implemented via at least one processor, to identify relevant information for documenting the surgical procedure, wherein analyzing the transcribed audio data comprises identifying within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the surgical procedure; automatically generating a text report including the relevant information documenting the surgical procedure, wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense text portion in the report, stating that the particular step of the surgical procedure was performed; and outputting the automatically generated text report for review via a user interface on an audio and/or visual display device. 30. The method of claim 1 , wherein the surgical procedure is performed on a patient, and wherein the method further comprises including at least part of the relevant information in a discrete structured data repository for the patient. | 0.876827 |
9,323,830 | 7 | 8 | 7. A non-transitory computer-readable storage medium embodying instructions that, when executed by a processing device, cause said processing device to perform a method of suggesting an alternative search query based on recorded search activities on an electronic search engine, said method comprising: accessing a record of a plurality of search sessions of a plurality of users performed on said electronic search engine, wherein said record comprises: for a respective search session, a plurality of search query terms entered by a respective user in a sequence; and an outcome event following said plurality of query terms; accessing an original query term in a search session; identifying a plurality of candidate replacement terms from said record based on said original query term; identifying a set of search sessions from said record, wherein said original query term is used for searching during each of said set of search sessions, and wherein said plurality of candidate replacement terms correspond to search query terms entered subsequent to said original query term in respective search sessions of said set of search sessions; calculating a first occurrence rate of a predefined event resulted from using said original query term for searching, based on said record regarding said plurality of search sessions; calculating respective occurrence rates of said predefined event resulted from using each candidate replacement term over said plurality of candidate replacement terms for searching subsequent to using said original query term for searching, based on said record regarding said plurality of search sessions; and determining a resultant query term based on said first occurrence rate and said respective occurrence rates. | 7. A non-transitory computer-readable storage medium embodying instructions that, when executed by a processing device, cause said processing device to perform a method of suggesting an alternative search query based on recorded search activities on an electronic search engine, said method comprising: accessing a record of a plurality of search sessions of a plurality of users performed on said electronic search engine, wherein said record comprises: for a respective search session, a plurality of search query terms entered by a respective user in a sequence; and an outcome event following said plurality of query terms; accessing an original query term in a search session; identifying a plurality of candidate replacement terms from said record based on said original query term; identifying a set of search sessions from said record, wherein said original query term is used for searching during each of said set of search sessions, and wherein said plurality of candidate replacement terms correspond to search query terms entered subsequent to said original query term in respective search sessions of said set of search sessions; calculating a first occurrence rate of a predefined event resulted from using said original query term for searching, based on said record regarding said plurality of search sessions; calculating respective occurrence rates of said predefined event resulted from using each candidate replacement term over said plurality of candidate replacement terms for searching subsequent to using said original query term for searching, based on said record regarding said plurality of search sessions; and determining a resultant query term based on said first occurrence rate and said respective occurrence rates. 8. A non-transitory computer-readable storage medium of claim 7 , wherein said electronic search engine is a web search engine configured to search commodities from an on-line store. | 0.822266 |
5,440,678 | 8 | 9 | 8. The computer system of claim 6, wherein said means for entering comprises: means for displaying said create footnote window; and means for placing said data in predesignated areas of said window. | 8. The computer system of claim 6, wherein said means for entering comprises: means for displaying said create footnote window; and means for placing said data in predesignated areas of said window. 9. The computer system of claim 8, wherein said means for placing comprises: a keyboard. | 0.5 |
9,235,562 | 15 | 16 | 15. A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: identify a document that received a classification by a machine learning classifier for data loss prevention; identify at least one linguistic constituent within the document that contributed to the classification; identify a relevant passage of the document that contextualizes the linguistic constituent; display a user interface comprising the linguistic constituent in context of the relevant passage; receive user input via the user interface indicating a type of mistake, selected via the user interface from a plurality of types of mistakes, that potentially caused the machine learning classifier to misclassify the document, wherein indicating the type of mistake that potentially caused the machine learning classifier to misclassify the document comprises indicating a basis of classification relied upon by the machine learning classifier that resulted in the machine learning classifier misclassifying the document. | 15. A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: identify a document that received a classification by a machine learning classifier for data loss prevention; identify at least one linguistic constituent within the document that contributed to the classification; identify a relevant passage of the document that contextualizes the linguistic constituent; display a user interface comprising the linguistic constituent in context of the relevant passage; receive user input via the user interface indicating a type of mistake, selected via the user interface from a plurality of types of mistakes, that potentially caused the machine learning classifier to misclassify the document, wherein indicating the type of mistake that potentially caused the machine learning classifier to misclassify the document comprises indicating a basis of classification relied upon by the machine learning classifier that resulted in the machine learning classifier misclassifying the document. 16. The non-transitory computer-readable medium of claim 15 , wherein the one or more computer-executable instructions further cause the computing device to provide, via the user interface, a selection element for selecting from the plurality of types of mistakes in response to receiving user input via the user interface indicating that the machine learning classifier misclassified the document. | 0.529551 |
8,005,680 | 2 | 3 | 2. The method of claim 1 , wherein at least a subset of said user dependant language models is stored locally in a user device and synchronised with user dependant language models stored in a pervasive platform. | 2. The method of claim 1 , wherein at least a subset of said user dependant language models is stored locally in a user device and synchronised with user dependant language models stored in a pervasive platform. 3. The method of claim 2 , further comprising a step of performing speech recognition in said user device using said locally stored user dependant language models, wherein said aspect of a service is personalized using said centrally stored user dependant language models. | 0.659148 |
8,195,654 | 12 | 15 | 12. A computer-implemented method for performing a search, the method comprising: receiving, at a device, a search query; identifying, by the device, documents relevant to the search query, where the identified documents include business listings; obtaining, by the device, data based on the received search query and the identified documents, where the obtained data includes: first data indicating whether the received search query exactly matches a name of a business in the business listings, and second data indicating whether a term in the search query matches a suffix portion of the name of the business, the suffix portion including less than an entirety of the name of the business; obtaining, by the device, predicted human relevance evaluations for the documents based on the obtained data, the predicted human relevance evaluations being obtained from a evaluation model based on the obtained data and based on information associated with human generated relevance evaluations, to predict a relevance evaluation that a human user would assign a particular document based on a corresponding search query, where the human generated relevance evaluations include rating scores, assigned by one or more human evaluators, indicative of a relevance of the identified documents to the received search query; ranking, by the device, the identified documents based on the obtained predicted human relevance evaluations; and presenting the ranked documents. | 12. A computer-implemented method for performing a search, the method comprising: receiving, at a device, a search query; identifying, by the device, documents relevant to the search query, where the identified documents include business listings; obtaining, by the device, data based on the received search query and the identified documents, where the obtained data includes: first data indicating whether the received search query exactly matches a name of a business in the business listings, and second data indicating whether a term in the search query matches a suffix portion of the name of the business, the suffix portion including less than an entirety of the name of the business; obtaining, by the device, predicted human relevance evaluations for the documents based on the obtained data, the predicted human relevance evaluations being obtained from a evaluation model based on the obtained data and based on information associated with human generated relevance evaluations, to predict a relevance evaluation that a human user would assign a particular document based on a corresponding search query, where the human generated relevance evaluations include rating scores, assigned by one or more human evaluators, indicative of a relevance of the identified documents to the received search query; ranking, by the device, the identified documents based on the obtained predicted human relevance evaluations; and presenting the ranked documents. 15. The method of claim 12 , where the obtained data further includes one or more of: third data indicating whether a term in the search query matches a prefix portion of the name of the business; or fourth data indicating whether a term in the search query is a substring of the name of the business. | 0.785307 |
7,769,234 | 16 | 19 | 16. The apparatus according to claim 15 , wherein the extraction section is adapted to select a graphic that makes the element parameter to be found within the corresponding parameter range from the document image and consolidate a plurality of ruled line elements that make the consolidation parameter to be found within the corresponding parameter range to generate the ruled line candidate. | 16. The apparatus according to claim 15 , wherein the extraction section is adapted to select a graphic that makes the element parameter to be found within the corresponding parameter range from the document image and consolidate a plurality of ruled line elements that make the consolidation parameter to be found within the corresponding parameter range to generate the ruled line candidate. 19. The apparatus according to claim 16 , wherein the ruled line is a solid ruled line; and the extraction section is adapted to divide a document image expressed by a binary system into a plurality of regions, select regions that make the element parameter to be found within the parameter range out of the regions as ruled line elements and consolidate the ruled line elements to generate a ruled line candidate. | 0.657285 |
8,086,441 | 21 | 23 | 21. An apparatus comprising: a finite state machine having a plurality of states logically coupled to each other via one or more paths, the plurality of states being mapped to a plurality of N-grams in an output table, wherein the finite state machine is operable to simultaneously search for the plurality of N-grams through a string of bytes in a single pass, wherein the string of bytes represents non-segmented text written in a non-delimited language; a counting module coupled to the finite state machine to count a number of occurrences of each of the plurality of N-grams in the string of bytes while tracing operations of the finite state machine over the string of bytes; and a classifying engine coupled to the counting module to classify the non-segmented text based on the number of occurrences of each of the plurality of N-grams, to block the string of bytes and to generate an error message if the non-segmented text is classified to be in a prohibited category, and to cause a display device to render the non-segmented text if the non-segmented text is classified to be in an allowable category. | 21. An apparatus comprising: a finite state machine having a plurality of states logically coupled to each other via one or more paths, the plurality of states being mapped to a plurality of N-grams in an output table, wherein the finite state machine is operable to simultaneously search for the plurality of N-grams through a string of bytes in a single pass, wherein the string of bytes represents non-segmented text written in a non-delimited language; a counting module coupled to the finite state machine to count a number of occurrences of each of the plurality of N-grams in the string of bytes while tracing operations of the finite state machine over the string of bytes; and a classifying engine coupled to the counting module to classify the non-segmented text based on the number of occurrences of each of the plurality of N-grams, to block the string of bytes and to generate an error message if the non-segmented text is classified to be in a prohibited category, and to cause a display device to render the non-segmented text if the non-segmented text is classified to be in an allowable category. 23. The apparatus of claim 21 , wherein the classifying engine is operable to compare the number of occurrences of each of the plurality of N-grams against corresponding information in a second model to determine if the non-segmented text is likely to be within the allowable category. | 0.5 |
9,626,348 | 1 | 13 | 1. A method, comprising: receiving, from a plurality of different computing devices and over a respective plurality of network connections, a plurality of data packets, wherein the plurality of different computing devices are operated by a plurality of different users, wherein each data packet in the plurality of data packets comprises: an annotation that has been assigned to a document by a respective user, wherein the annotation is a tuple that comprises a first word or phrase extracted from the document, a second word or phrase extracted from the document, and a third word or phrase extracted from the document, wherein the third word or phrase relates the first word or phrase to the second word or phrase; and relationship data that indicates that the annotation has been assigned to the document, wherein each data packet comprises a different annotation, and each data packet in the plurality of data packets has a same format; aggregating the plurality of data packets in a data repository to form a network of knowledge, wherein the data repository is accessible to a processor; and utilizing the processor to perform at least one processing function over at least one data packet in the data repository. | 1. A method, comprising: receiving, from a plurality of different computing devices and over a respective plurality of network connections, a plurality of data packets, wherein the plurality of different computing devices are operated by a plurality of different users, wherein each data packet in the plurality of data packets comprises: an annotation that has been assigned to a document by a respective user, wherein the annotation is a tuple that comprises a first word or phrase extracted from the document, a second word or phrase extracted from the document, and a third word or phrase extracted from the document, wherein the third word or phrase relates the first word or phrase to the second word or phrase; and relationship data that indicates that the annotation has been assigned to the document, wherein each data packet comprises a different annotation, and each data packet in the plurality of data packets has a same format; aggregating the plurality of data packets in a data repository to form a network of knowledge, wherein the data repository is accessible to a processor; and utilizing the processor to perform at least one processing function over at least one data packet in the data repository. 13. The method of claim 1 , wherein utilizing the processor to perform at least one processing function over at least one data packet in the data repository comprises executing a data mining algorithm over the plurality of data packets in the data repository. | 0.559524 |
5,544,260 | 5 | 6 | 5. A method of training a handwriting recognition system to recognize handwritten characters of a particular user, comprising: (a) storing plurality of prototype characters in a memory; (b) entering a string of user-generated handwritten characters on an input device; (c) comparing the user generated string of characters with the prototype characters stored in memory; (d) displaying, for each user generated handwritten character, a corresponding character, the corresponding character of a particular user-generated character being a prototype character most closely resembling the particular user-generated handwritten character; (e) entering a user-generated handwritten correction character for each incorrectly recognized user-input character; (f) comparing the user generated correction characters with the prototype characters stored in memory, excluding the incorrectly returned character; (g) displaying a corresponding correction character for each user generated correction character, the corresponding correction character of a particular user-generated correction character being a prototype character most closely resembling the particular user-generated handwritten correction character; (h) repeating steps (e) through (g) if the corresponding correction character does not match the user generated correction character; (i) comparing the misrecognized user generated handwritten character and the user generated correction character and determining whether they resemble one another within a predetermined threshold, and: if so, retraining the system to recognize the misrecognized user generated character and the user generated correction character as the corresponding correction character; if not, retraining the system to recognize the user generated correction character as the corresponding correction character. | 5. A method of training a handwriting recognition system to recognize handwritten characters of a particular user, comprising: (a) storing plurality of prototype characters in a memory; (b) entering a string of user-generated handwritten characters on an input device; (c) comparing the user generated string of characters with the prototype characters stored in memory; (d) displaying, for each user generated handwritten character, a corresponding character, the corresponding character of a particular user-generated character being a prototype character most closely resembling the particular user-generated handwritten character; (e) entering a user-generated handwritten correction character for each incorrectly recognized user-input character; (f) comparing the user generated correction characters with the prototype characters stored in memory, excluding the incorrectly returned character; (g) displaying a corresponding correction character for each user generated correction character, the corresponding correction character of a particular user-generated correction character being a prototype character most closely resembling the particular user-generated handwritten correction character; (h) repeating steps (e) through (g) if the corresponding correction character does not match the user generated correction character; (i) comparing the misrecognized user generated handwritten character and the user generated correction character and determining whether they resemble one another within a predetermined threshold, and: if so, retraining the system to recognize the misrecognized user generated character and the user generated correction character as the corresponding correction character; if not, retraining the system to recognize the user generated correction character as the corresponding correction character. 6. The method of claim 5, further comprising: retraining the system to recognize the user generated correction character as the corresponding correction character. | 0.544693 |
9,621,578 | 1 | 10 | 1. A computer-implemented method for detecting a network activity of interest, the method comprising: (a) obtaining, by one or more processors, a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; (b) creating, by the one or more processors, a combined packet from at least two network packets of the plurality of network packets obtained in (a), wherein creating the combined packet comprises converting, bitwise, content from a portion of a first network packet and a portion of a second network packet into a plurality of integers, wherein the first network packet represents a communication from a first node to a second node, and wherein the second network packet represents a communication from the second node to the first node, wherein the combined packet comprises the plurality of integers; (c) obtaining a stored meta-expression that: comprises a plurality of integers in an order, and corresponds to presence of the network activity of interest in network traffic; (d) determining whether the meta-expression obtained in (c) appears in the combined packet created in (b); (e) in response to determining that the meta-expression obtained in (c) appears in the combined packet created in (b), initiating an operation. | 1. A computer-implemented method for detecting a network activity of interest, the method comprising: (a) obtaining, by one or more processors, a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; (b) creating, by the one or more processors, a combined packet from at least two network packets of the plurality of network packets obtained in (a), wherein creating the combined packet comprises converting, bitwise, content from a portion of a first network packet and a portion of a second network packet into a plurality of integers, wherein the first network packet represents a communication from a first node to a second node, and wherein the second network packet represents a communication from the second node to the first node, wherein the combined packet comprises the plurality of integers; (c) obtaining a stored meta-expression that: comprises a plurality of integers in an order, and corresponds to presence of the network activity of interest in network traffic; (d) determining whether the meta-expression obtained in (c) appears in the combined packet created in (b); (e) in response to determining that the meta-expression obtained in (c) appears in the combined packet created in (b), initiating an operation. 10. The computer-implemented method of claim 1 , wherein creating the combined packet comprises: identifying the first and second network packets from a network conversation between the first node and the second node. | 0.840675 |
7,558,822 | 24 | 28 | 24. A computer readable storage medium storing one or more programs for execution by one or more processors of a client computer, the one or more programs including: a client assistant configured to monitor a user's browsing activities within a currently displayed document having links to one or more associated documents, including monitoring proximity of a user-controllable pointer to one or more of the links in the currently displayed document; the client assistant including instructions for identifying a link satisfying predefined criteria, the predefined criteria including proximity criteria with respect to the user-controllable pointer; and a communications interface coupled to the client assistant for transmitting to a server, prior to user selection of any respective link, a request for a document corresponding to the identified link. | 24. A computer readable storage medium storing one or more programs for execution by one or more processors of a client computer, the one or more programs including: a client assistant configured to monitor a user's browsing activities within a currently displayed document having links to one or more associated documents, including monitoring proximity of a user-controllable pointer to one or more of the links in the currently displayed document; the client assistant including instructions for identifying a link satisfying predefined criteria, the predefined criteria including proximity criteria with respect to the user-controllable pointer; and a communications interface coupled to the client assistant for transmitting to a server, prior to user selection of any respective link, a request for a document corresponding to the identified link. 28. The computer readable storage medium of claim 24 , wherein the client assistant includes instructions for determining whether a user-controllable pointer is positioned over a link in the currently displayed document. | 0.789675 |
10,008,203 | 13 | 16 | 13. A computer system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, causes the system to: receive data specifying a new voice action, the data identifying (i) an application, (ii) a voice command trigger phrase for triggering the application, and (iii) a context that must be satisfied for the application to be triggered; generate a data structure instance that specifies (i) the application, (ii) the voice command trigger phrase, and (iii) an alternate voice command trigger phrase, the alternate voice command trigger phrase being based on the received voice command trigger phrase; and after generating the data structure instance, enable triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises a plurality of other data structure instances, wherein each of the other data structure instances specifies (i) an application, and (ii) one or more voice command trigger phrases; determine that the context is satisfied; after enabling the triggering of the new voice action and based at least on determining that a transcription of a spoken utterance includes the alternate voice command trigger phrase specified by the generated data structure instance, select the generated data structure instance from the database; and based on the selection of the generated data structure instance and based on the determination that the context is satisfied, cause an activity associated with the application specified by the generated data structure to be performed on or by the application. | 13. A computer system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, causes the system to: receive data specifying a new voice action, the data identifying (i) an application, (ii) a voice command trigger phrase for triggering the application, and (iii) a context that must be satisfied for the application to be triggered; generate a data structure instance that specifies (i) the application, (ii) the voice command trigger phrase, and (iii) an alternate voice command trigger phrase, the alternate voice command trigger phrase being based on the received voice command trigger phrase; and after generating the data structure instance, enable triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises a plurality of other data structure instances, wherein each of the other data structure instances specifies (i) an application, and (ii) one or more voice command trigger phrases; determine that the context is satisfied; after enabling the triggering of the new voice action and based at least on determining that a transcription of a spoken utterance includes the alternate voice command trigger phrase specified by the generated data structure instance, select the generated data structure instance from the database; and based on the selection of the generated data structure instance and based on the determination that the context is satisfied, cause an activity associated with the application specified by the generated data structure to be performed on or by the application. 16. The computer system of claim 13 , wherein the context defines particular software that must be absent from a computing device that provides the spoken utterance that is transcribed. | 0.88423 |
9,036,806 | 14 | 15 | 14. A system for processing communications in a call center, comprising: a database storing records of calls to said call center, said records comprising call information comprising a call summary field that includes an assigned call class; a special-purpose telecommunications processor connected to said database, said special-purpose telecommunications processor comprising a tokenizer; and a graphical user interface connected to said special-purpose telecommunications processor, said special-purpose telecommunications processor analyzing said call summary field in said records of calls using said tokenizer, said tokenizer transforming a sequence of characters in said call summary field into a sequence of tokens, producing tokenized call data, said special-purpose telecommunications processor creating a maximum entropy (MaxEnt) model based on said tokenized call data, said MaxEnt model producing a probability distribution of all classes for a next call to said call center, said special-purpose telecommunications processor training a conditional random field (CRF) classifier with said MaxEnt model and said call information from said records of calls, said CRF classifier using chronologically ordered sequences of prior calls to said call center and predicting a class for a new call to said call center based on said records of calls to said call center stored in said database, said special-purpose telecommunications processor producing a call class prediction for a received call based on said CRF classifier and said MaxEnt model, and said special-purpose telecommunications processor displaying said call class prediction for said received call on said graphical user interface. | 14. A system for processing communications in a call center, comprising: a database storing records of calls to said call center, said records comprising call information comprising a call summary field that includes an assigned call class; a special-purpose telecommunications processor connected to said database, said special-purpose telecommunications processor comprising a tokenizer; and a graphical user interface connected to said special-purpose telecommunications processor, said special-purpose telecommunications processor analyzing said call summary field in said records of calls using said tokenizer, said tokenizer transforming a sequence of characters in said call summary field into a sequence of tokens, producing tokenized call data, said special-purpose telecommunications processor creating a maximum entropy (MaxEnt) model based on said tokenized call data, said MaxEnt model producing a probability distribution of all classes for a next call to said call center, said special-purpose telecommunications processor training a conditional random field (CRF) classifier with said MaxEnt model and said call information from said records of calls, said CRF classifier using chronologically ordered sequences of prior calls to said call center and predicting a class for a new call to said call center based on said records of calls to said call center stored in said database, said special-purpose telecommunications processor producing a call class prediction for a received call based on said CRF classifier and said MaxEnt model, and said special-purpose telecommunications processor displaying said call class prediction for said received call on said graphical user interface. 15. The system according to claim 14 , said call information further comprising: date and time of a received call; identity of agent handling said received call; identity of customer making said received call; demographics associated with said customer making said received call; and assigned class of said received call. | 0.5 |
8,260,787 | 1 | 5 | 1. A computer-implemented method of normalizing item recommendation scores, the method comprising: by a computer system comprising computer hardware: assigning scores to candidate recommendations with first and second recommenders, the first recommender configured to assign first scores to a first portion of the candidate recommendations, the second recommender configured to assign second scores to a second portion of the candidate recommendations using a different scoring scale than the first recommender; outputting the scores from each of the recommenders to a normalization engine; for each recommender, normalizing the scores output by the recommender with the normalization engine by at least: combining the scores for at least some of the candidate recommendations to generate a combined score, said combining comprising computing a moving average of at least some of the scores, and calculating normalized scores based at least in part on the combined score and the scores for at least some of the candidate recommendations; and using the normalized scores to select at least a portion of the candidate recommendations to recommend to the target user. | 1. A computer-implemented method of normalizing item recommendation scores, the method comprising: by a computer system comprising computer hardware: assigning scores to candidate recommendations with first and second recommenders, the first recommender configured to assign first scores to a first portion of the candidate recommendations, the second recommender configured to assign second scores to a second portion of the candidate recommendations using a different scoring scale than the first recommender; outputting the scores from each of the recommenders to a normalization engine; for each recommender, normalizing the scores output by the recommender with the normalization engine by at least: combining the scores for at least some of the candidate recommendations to generate a combined score, said combining comprising computing a moving average of at least some of the scores, and calculating normalized scores based at least in part on the combined score and the scores for at least some of the candidate recommendations; and using the normalized scores to select at least a portion of the candidate recommendations to recommend to the target user. 5. The method of claim 1 , further comprising assigning weights to candidate recommendations received from the first and second recommenders. | 0.773312 |
8,185,524 | 1 | 2 | 1. A method for locating and presenting events in-context comprising: automatically extracting, by a computing device, attributes from at least a portion of an electronic document associated with a user; obtaining, by the computing device, a set of contextual information, the set of contextual information comprising contextual information selected from a group of contextual information types consisting of user behavior, user preferences, and user environment; analyzing, by the computing device, the attributes and the set of contextual information to cause generation of one or more search terms; analyzing, by the computing device, context of the attributes of the document, where the context of the attributes includes sender and receiver of the document, location, time, and theme of the events to be searched; generating, based on the analyzing steps, the one or more search terms; determining, by the computing device, search results for events based on the one or more search terms; and causing, by the computing device, a display of the search results simultaneously with at least a portion of a display of the electronic document. | 1. A method for locating and presenting events in-context comprising: automatically extracting, by a computing device, attributes from at least a portion of an electronic document associated with a user; obtaining, by the computing device, a set of contextual information, the set of contextual information comprising contextual information selected from a group of contextual information types consisting of user behavior, user preferences, and user environment; analyzing, by the computing device, the attributes and the set of contextual information to cause generation of one or more search terms; analyzing, by the computing device, context of the attributes of the document, where the context of the attributes includes sender and receiver of the document, location, time, and theme of the events to be searched; generating, based on the analyzing steps, the one or more search terms; determining, by the computing device, search results for events based on the one or more search terms; and causing, by the computing device, a display of the search results simultaneously with at least a portion of a display of the electronic document. 2. The method of claim 1 , wherein the electronic document comprises an electronic document selected from a group of electronic document types consisting of text, image, graphics, URL, map, calendar, audio, and video. | 0.637124 |
9,672,268 | 8 | 9 | 8. The method of claim 1 , wherein said database query language is a Structured Query Language (SQL). | 8. The method of claim 1 , wherein said database query language is a Structured Query Language (SQL). 9. The method of claim 8 , wherein providing the first and each further real result table comprises using a “CREATE TABLE” command to create the table structure and an “INSERT” command in combination with one or more “SELECT” commands to fill the table structure. | 0.5 |
7,685,512 | 64 | 65 | 64. The computer-implemented method of claim 60 , wherein said XML entity is an element reference referencing a referenced global element declaration and further comprising: determining, by said processor, whether a target namespace of said referenced global element declaration is null or the same as a target namespace of an XML schema containing said element reference; and generating, by said processor, an element declaration based on said determining. | 64. The computer-implemented method of claim 60 , wherein said XML entity is an element reference referencing a referenced global element declaration and further comprising: determining, by said processor, whether a target namespace of said referenced global element declaration is null or the same as a target namespace of an XML schema containing said element reference; and generating, by said processor, an element declaration based on said determining. 65. The computer-implemented method of claim 64 , wherein said generating said element declaration comprises, if said determining determines that said target namespace of said referenced global element declaration is null or the same as the target namespace of an XML schema containing said element reference: generating, by said processor, in place of said element reference a new local element declaration with a derived type based on a determined type of said referenced global element declaration. | 0.631075 |
9,646,110 | 7 | 9 | 7. A system of governing information assets managed by an enterprise, the system comprising: a computer processor; and a memory storing an enterprise information asset management application which, when executed on the computer processor, performs an operation comprising: identifying, by an enterprise information asset management application executed on a computing system having at least a processor and a memory, a set of search results responsive to a query requesting a subset of information assets within the enterprise; providing the set of search results; receiving a selection of a first information asset presented in the set of search results; identifying at least a second information asset presented in the set of search results, wherein the first information asset and the second information asset are related to one another by an edge in a semantic graph that represents relationships between the plurality of information assets, wherein the semantic graph associates the plurality of information assets with nodes of the semantic graph, wherein the relationships between nodes in the semantic graph are generated and updated by monitoring user behavior in accessing the plurality of information assets with the set of search results and without requiring user input explicitly specifying to update the relationships, wherein the semantic graph is updated based on a domain ontology; parsing the semantic graph in order to identify at least one information asset selected from: (i) an informal information asset whose relationships satisfy an overuse criterion and (ii) an underused information asset whose relationships satisfy an underuse criterion; and designating the at least one information asset as being overused or underused, whereafter the at least one information asset is formally commissioned or decommissioned. | 7. A system of governing information assets managed by an enterprise, the system comprising: a computer processor; and a memory storing an enterprise information asset management application which, when executed on the computer processor, performs an operation comprising: identifying, by an enterprise information asset management application executed on a computing system having at least a processor and a memory, a set of search results responsive to a query requesting a subset of information assets within the enterprise; providing the set of search results; receiving a selection of a first information asset presented in the set of search results; identifying at least a second information asset presented in the set of search results, wherein the first information asset and the second information asset are related to one another by an edge in a semantic graph that represents relationships between the plurality of information assets, wherein the semantic graph associates the plurality of information assets with nodes of the semantic graph, wherein the relationships between nodes in the semantic graph are generated and updated by monitoring user behavior in accessing the plurality of information assets with the set of search results and without requiring user input explicitly specifying to update the relationships, wherein the semantic graph is updated based on a domain ontology; parsing the semantic graph in order to identify at least one information asset selected from: (i) an informal information asset whose relationships satisfy an overuse criterion and (ii) an underused information asset whose relationships satisfy an underuse criterion; and designating the at least one information asset as being overused or underused, whereafter the at least one information asset is formally commissioned or decommissioned. 9. The system of claim 7 , wherein the plurality of information assets include at least one of a database system, a web service, and a server application. | 0.865149 |
9,466,225 | 1 | 4 | 1. A speech learning apparatus comprising: a processor, programmed to detect a keyword corresponding to a character string selected from a text; calculate a score indicating a degree of emphasis of the keyword based on a manner of selecting the keyword; generate a synthesis parameter to determine a degree of reading of the keyword in accordance with the score; add to the keyword a tag for reading the keyword in accordance with the synthesis parameter; generate synthesized speech obtained by synthesizing speech of the keyword in accordance with the tag; calculate a social score indicating a score of the keyword selected by one or more other users different from the user; and calculate an integration score using the score and the social score, wherein the synthesis parameter is generated in accordance with the integration score. | 1. A speech learning apparatus comprising: a processor, programmed to detect a keyword corresponding to a character string selected from a text; calculate a score indicating a degree of emphasis of the keyword based on a manner of selecting the keyword; generate a synthesis parameter to determine a degree of reading of the keyword in accordance with the score; add to the keyword a tag for reading the keyword in accordance with the synthesis parameter; generate synthesized speech obtained by synthesizing speech of the keyword in accordance with the tag; calculate a social score indicating a score of the keyword selected by one or more other users different from the user; and calculate an integration score using the score and the social score, wherein the synthesis parameter is generated in accordance with the integration score. 4. The apparatus according to claim 1 , wherein the processor is further programmed to give a question relating to a keyword to the user; and calculate a correct answer rate based on an answer to the question from the user, to generate a learning history including information associated with the question and the correct answer rate, wherein the score indicating the degree of emphasis of the keyword calculates the score which becomes lower as the correct answer rate increases, in accordance with the learning history. | 0.5 |
7,528,990 | 26 | 27 | 26. The method according to claim 25 , wherein, if a portion in said input setting screen, resulting from said input setting screen information generated in said step of generating, is different from that corresponding to said portion in an initial input setting screen, resulting from initial setting values, said step of displaying an expected image finish displays said portion with emphasis. | 26. The method according to claim 25 , wherein, if a portion in said input setting screen, resulting from said input setting screen information generated in said step of generating, is different from that corresponding to said portion in an initial input setting screen, resulting from initial setting values, said step of displaying an expected image finish displays said portion with emphasis. 27. The method according to claim 26 , wherein, if said step of receiving receives at least a setting item by the operator and if said step of displaying displays an updated input setting screen which is updated according to said setting item by the operator, said step of displaying an expected image finish displays said portion with emphasis, in which said portion in said updated input setting screen is different from a portion corresponding to said portion in an input setting screen prior to updating. | 0.5 |
7,912,847 | 1 | 16 | 1. A method performing a comparative web search comprising: providing a meta-search engine in communication with a plurality of web-based search engines; providing said meta-search engine with a query, a search mode, and a selected set of said web-based search engines, said meta-search engine using said query to search for documents on the selected set of said web-based search engines, wherein the search mode includes the following modes: (a) a comparison of data sets collected from same or different generic web search engines in response to two or more different queries, (b) a comparison of data sets collected from same or different generic web search engines in response to a common query performed at different points of time, (c) a comparison of data sets collected from different generic web search engines in response to a common query performed simultaneously, (d) a comparison of data sets collected from same or different generic web search engines in response to a common query performed in different languages, (e) a comparison of result sets collected from same or different generic web search engines in response to a common query where intra-domain similarity between results of the same set is 100% while inter-geographic origin similarity between result sets is zero, (f) a comparison of result sets collected from same or different generic web search engines in response to a common query where intra-geographic origin similarity between results of same set is 100% while inter-geographic origin similarity between result sets is zero, and (g) a result set retrieved from a generic web search engine in response to a query is segmented into bins of equi-distant and equi-weighted segments and the segments are compared to generate comparative summaries; retrieving automatically search results from each of the web-based search engines in the selected set in the form of at least web snippets or documents from each member of the selected set of said web-based search engines and using the search result as raw data; providing automatically the raw data to a data pre-processing module which automatically removes stop words and HTML tags, and applies a stemming algorithm, resulting in pre-processed data; providing automatically the pre-processed data to a comparison engine, said comparison engine performing an object level comparison or a thematic level comparison depending on which comparison is specified in the search mode, said comparison resulting in a plurality of result sets from the selected set of said web-based search engines; determining automatically logical relationships between each of the plurality of result sets and providing a results comparison of the determined logical relationships; organizing automatically the search results in ranked lists when the object level comparison is performed by the comparison engine and labeled hierarchical clusters when the thematic level comparison is performed by the comparison engine, said organizing resulting in organized search results; and outputting the results comparison and the organized search results for viewing. | 1. A method performing a comparative web search comprising: providing a meta-search engine in communication with a plurality of web-based search engines; providing said meta-search engine with a query, a search mode, and a selected set of said web-based search engines, said meta-search engine using said query to search for documents on the selected set of said web-based search engines, wherein the search mode includes the following modes: (a) a comparison of data sets collected from same or different generic web search engines in response to two or more different queries, (b) a comparison of data sets collected from same or different generic web search engines in response to a common query performed at different points of time, (c) a comparison of data sets collected from different generic web search engines in response to a common query performed simultaneously, (d) a comparison of data sets collected from same or different generic web search engines in response to a common query performed in different languages, (e) a comparison of result sets collected from same or different generic web search engines in response to a common query where intra-domain similarity between results of the same set is 100% while inter-geographic origin similarity between result sets is zero, (f) a comparison of result sets collected from same or different generic web search engines in response to a common query where intra-geographic origin similarity between results of same set is 100% while inter-geographic origin similarity between result sets is zero, and (g) a result set retrieved from a generic web search engine in response to a query is segmented into bins of equi-distant and equi-weighted segments and the segments are compared to generate comparative summaries; retrieving automatically search results from each of the web-based search engines in the selected set in the form of at least web snippets or documents from each member of the selected set of said web-based search engines and using the search result as raw data; providing automatically the raw data to a data pre-processing module which automatically removes stop words and HTML tags, and applies a stemming algorithm, resulting in pre-processed data; providing automatically the pre-processed data to a comparison engine, said comparison engine performing an object level comparison or a thematic level comparison depending on which comparison is specified in the search mode, said comparison resulting in a plurality of result sets from the selected set of said web-based search engines; determining automatically logical relationships between each of the plurality of result sets and providing a results comparison of the determined logical relationships; organizing automatically the search results in ranked lists when the object level comparison is performed by the comparison engine and labeled hierarchical clusters when the thematic level comparison is performed by the comparison engine, said organizing resulting in organized search results; and outputting the results comparison and the organized search results for viewing. 16. The method of claim 1 , wherein the comparison engine conducts one of the following four procedures based on the search mode: i. determining common results between two result sets, clustering the common results based on themes they share, and ranking of results in each participating set to determine at least emerging, disappearing and steady results; ii. combining the results from all the participating result sets into a data reservoir and then clustering them based on common themes; iii. clustering the results belonging to the same set based on common themes, and then comparing the themes presented by clustered results in one result set with other sets to find commonalties; or iv. using term frequencies of keywords common to all participating result sets to determine at least what themes are emerging, disappearing or remaining steady. | 0.546375 |
9,223,619 | 1 | 2 | 1. An apparatus comprising: a processor component; a task selector for execution by the processor component to receive an indication of a specified task to be performed, wherein the specified task comprises first and second subtasks; a source selector for execution by the processor component to receive an indication of a specified source device to perform the first and second subtasks, and to retrieve from the specified source device an indication of a source processing environment currently available within at least the specified source device in response to receiving the indication of the specified source device, wherein: the source device stores a source data set to serve as an input to performance of the specified task; and the indication of the source processing environment comprises indications of an identity and version level of a database routine of the specified source device; and an instruction generator for execution by the processor component to determine a first set of one or more languages able to be interpreted by the database routine of the specified source device based on the identity and version level of the database routine of the specified source device, determine whether to perform the first and second subtasks sequentially or at least partly in parallel based on at least one aspect of the source processing environment, select a language of the first set of languages in which to generate instructions to perform at least the first subtask based on the determination of whether to perform the first and second subtasks sequentially or at least partly in parallel, generate the instructions to perform the first subtask in the selected language, and transmit first task instructions comprising at least the instructions generated to perform at least the first subtask to the specified source device. | 1. An apparatus comprising: a processor component; a task selector for execution by the processor component to receive an indication of a specified task to be performed, wherein the specified task comprises first and second subtasks; a source selector for execution by the processor component to receive an indication of a specified source device to perform the first and second subtasks, and to retrieve from the specified source device an indication of a source processing environment currently available within at least the specified source device in response to receiving the indication of the specified source device, wherein: the source device stores a source data set to serve as an input to performance of the specified task; and the indication of the source processing environment comprises indications of an identity and version level of a database routine of the specified source device; and an instruction generator for execution by the processor component to determine a first set of one or more languages able to be interpreted by the database routine of the specified source device based on the identity and version level of the database routine of the specified source device, determine whether to perform the first and second subtasks sequentially or at least partly in parallel based on at least one aspect of the source processing environment, select a language of the first set of languages in which to generate instructions to perform at least the first subtask based on the determination of whether to perform the first and second subtasks sequentially or at least partly in parallel, generate the instructions to perform the first subtask in the selected language, and transmit first task instructions comprising at least the instructions generated to perform at least the first subtask to the specified source device. 2. The apparatus of claim 1 , comprising a user interface (UI) component for execution by the processor component to generate, by circuitry for presentation on a display, a selection of tasks and a selection of operations to perform on at least a portion of the source data set, wherein: the selection of tasks comprises the specified task; and the instruction generator is to receive an indication of selection of one or more operations from the presented selection of operations, and to identify at least the first and second subtasks from the selected one or more operations. | 0.824423 |
8,447,751 | 14 | 19 | 14. A non-transitory computer readable medium storing computer readable instructions that, when executed, cause an apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes. | 14. A non-transitory computer readable medium storing computer readable instructions that, when executed, cause an apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes. 19. The non-transitory computer readable medium of claim 14 , wherein the computer readable instructions, when executed, further cause the apparatus to: receive a request to create an alert relating to at least one of: a document site, the network document and a portion of the network document, wherein the alert includes a user-specified condition to be met; determine whether the user-specified condition has been met; and in response to determining that the user-specified condition has been met, perform a specified action. | 0.5 |
8,990,082 | 1 | 2 | 1. A computer-implemented method of scoring non-native speech, comprising: receiving a speech sample spoken by a non-native speaker; performing automatic speech recognition on the speech sample to generate a transcript of the speech sample; processing the speech sample to generate a plurality of speech metrics associated with the speech sample; applying a plurality of non-scorable response filters to the plurality of speech metrics; determining whether the speech sample is scorable or non-scorable based upon the transcript and a collective application of said non-scorable response filters, wherein said determining is based on assessment of audio quality of the speech sample, an amount of speech of the speech sample, a degree to which the speech sample is off-topic, and whether the speech sample includes speech from an incorrect language; associating an indication of non-scorability with the speech sample when the sample is determined to be non-scorable; and providing the sample to a scoring model for scoring when the sample is determined to be scorable. | 1. A computer-implemented method of scoring non-native speech, comprising: receiving a speech sample spoken by a non-native speaker; performing automatic speech recognition on the speech sample to generate a transcript of the speech sample; processing the speech sample to generate a plurality of speech metrics associated with the speech sample; applying a plurality of non-scorable response filters to the plurality of speech metrics; determining whether the speech sample is scorable or non-scorable based upon the transcript and a collective application of said non-scorable response filters, wherein said determining is based on assessment of audio quality of the speech sample, an amount of speech of the speech sample, a degree to which the speech sample is off-topic, and whether the speech sample includes speech from an incorrect language; associating an indication of non-scorability with the speech sample when the sample is determined to be non-scorable; and providing the sample to a scoring model for scoring when the sample is determined to be scorable. 2. The method of claim 1 , wherein the speech sample is not provided to the scoring model when the speech sample is determined to be non-scorable. | 0.787791 |
7,844,956 | 1 | 2 | 1. A computer-implemented method, executed by a central processing unit (CPU), for application-specific object-oriented processing of a markup by a model instance associated with a class Model and a plurality of element instances, each of said plurality of element instances associated with a class Element, said class Model is configured to process instances of said class Element, comprising the steps of: responding to a construct-element request, said construct-element request is a member function of said class Model, dispatched to said model instance, in which a tag name is provided, said tag name corresponding to a tagged element from said markup, constructing a new element instance, one of said plurality of element instances, according to application-specific requirements as determined according to said tag name, performing application-specific processing as required, and returning said constructed new element instance; responding to an accept-attribute request, said accept-attribute request is a member function of said class Element, dispatched to one of said plurality of element instances, in which an attribute is provided, said attribute corresponding to a markup attribute of a tagged element from said markup, and performing application-specific processing as required; responding to an accept-element request, said accept-element request is a member function of said class Element, dispatched to one of said plurality of element instances, in which a child element instances, one of said plurality of element instances, is provided, and performing application-specific processing as required; and responding to an accept-root-element request, said accept-root-element request is a member function of said class Model, dispatched to said model instance, in which a root element instance, one of said plurality of element instances, is provided, and performing application-specific processing as required. | 1. A computer-implemented method, executed by a central processing unit (CPU), for application-specific object-oriented processing of a markup by a model instance associated with a class Model and a plurality of element instances, each of said plurality of element instances associated with a class Element, said class Model is configured to process instances of said class Element, comprising the steps of: responding to a construct-element request, said construct-element request is a member function of said class Model, dispatched to said model instance, in which a tag name is provided, said tag name corresponding to a tagged element from said markup, constructing a new element instance, one of said plurality of element instances, according to application-specific requirements as determined according to said tag name, performing application-specific processing as required, and returning said constructed new element instance; responding to an accept-attribute request, said accept-attribute request is a member function of said class Element, dispatched to one of said plurality of element instances, in which an attribute is provided, said attribute corresponding to a markup attribute of a tagged element from said markup, and performing application-specific processing as required; responding to an accept-element request, said accept-element request is a member function of said class Element, dispatched to one of said plurality of element instances, in which a child element instances, one of said plurality of element instances, is provided, and performing application-specific processing as required; and responding to an accept-root-element request, said accept-root-element request is a member function of said class Model, dispatched to said model instance, in which a root element instance, one of said plurality of element instances, is provided, and performing application-specific processing as required. 2. The computer-implemented method of claim 1 , further comprising the step of: responding to a configure request, said configure request is a member function of said class Element, dispatched to one of said plurality of element instances, said configure request indicating that no further is for said accept-attribute request will be dispatched to the one of said plurality of element instances, and performing application-specific processing as required. | 0.5 |
7,904,439 | 9 | 10 | 9. The display-building system of claim 7 , further comprising at least one control to the utility model. | 9. The display-building system of claim 7 , further comprising at least one control to the utility model. 10. The display-building system of claim 9 , wherein the at least one control adjusts various parameters associated with the utility model, the parameters adjusted via graphical sliders that are labeled with descriptions related to an influence of adjusting the at least one control in different directions. | 0.5 |
8,140,459 | 1 | 2 | 1. A method implemented by a computing device, the method comprising: receiving a formula in order to determine a satisfiability of the formula; propagating truth assignments to atomic constraints of the formula by applying a Davis Putnam Longman Loveland (DPLL)-based technique; eliminating conjunctions associated with the formula; representing the formula by disjunctions and negations based in part on the eliminating of the conjunctions; tracking which truth assignments are relevant for determining satisfiability of the formula based in part on emulating a Tableau solving technique using the disjunctions and the negations; and propagating the truth assignments of only the relevant atomic constraints to a theory solver. | 1. A method implemented by a computing device, the method comprising: receiving a formula in order to determine a satisfiability of the formula; propagating truth assignments to atomic constraints of the formula by applying a Davis Putnam Longman Loveland (DPLL)-based technique; eliminating conjunctions associated with the formula; representing the formula by disjunctions and negations based in part on the eliminating of the conjunctions; tracking which truth assignments are relevant for determining satisfiability of the formula based in part on emulating a Tableau solving technique using the disjunctions and the negations; and propagating the truth assignments of only the relevant atomic constraints to a theory solver. 2. The method as recited in claim 1 , further comprising creating relevancy propagation rules for tracking which truth assignments are relevant for determining satisfiability of the formula. | 0.5 |
8,920,469 | 10 | 16 | 10. A spinal fixation system, comprising: a bone anchor having a bone-engaging portion and a spinal fixation element receiving portion with opposed arms configured to receive a spinal fixation element therebetween; a connecting member having first and second ends, the first end having an opening extending therethrough; a threaded member having a portion thereof extending through the opening of the first end of the connecting member, the threaded member being configured to threadably engage the opposed arms of the spinal fixation element receiving portion of the bone anchor such that the threaded member contacts both arms of the opposed arms; and a locking member configured to engage a proximal portion of the threaded member and secure the first end of the connecting member between a proximal end of the locking member and a spinal fixation element disposed in the spinal fixation element receiving portion of the bone anchor. | 10. A spinal fixation system, comprising: a bone anchor having a bone-engaging portion and a spinal fixation element receiving portion with opposed arms configured to receive a spinal fixation element therebetween; a connecting member having first and second ends, the first end having an opening extending therethrough; a threaded member having a portion thereof extending through the opening of the first end of the connecting member, the threaded member being configured to threadably engage the opposed arms of the spinal fixation element receiving portion of the bone anchor such that the threaded member contacts both arms of the opposed arms; and a locking member configured to engage a proximal portion of the threaded member and secure the first end of the connecting member between a proximal end of the locking member and a spinal fixation element disposed in the spinal fixation element receiving portion of the bone anchor. 16. The system of claim 10 , further comprising a second bone anchor having a bone-engaging portion and a spinal fixation element receiving portion configured to receive a spinal fixation element therein, the second bone anchor being configured to be mated to the second end of the connecting member. | 0.5 |
8,700,555 | 40 | 44 | 40. A computer readable medium including processor executable instructions for sharing information between a semantic network and a knowledge sharing repository, including instructions to: access the knowledge sharing repository from the first computer system; retrieve, from the knowledge sharing repository, a set of data based on information included in the knowledge sharing repository; and transfer, from the first computer system, the set of data to a computer system hosting the semantic network for incorporation into the semantic network. | 40. A computer readable medium including processor executable instructions for sharing information between a semantic network and a knowledge sharing repository, including instructions to: access the knowledge sharing repository from the first computer system; retrieve, from the knowledge sharing repository, a set of data based on information included in the knowledge sharing repository; and transfer, from the first computer system, the set of data to a computer system hosting the semantic network for incorporation into the semantic network. 44. The computer readable medium of claim 40 wherein the instructions to transfer the set of data include instructions to extract tagged representations of content from the knowledge sharing repository and translate the tagged representations into content for insertion in the semantic network. | 0.527331 |
8,200,606 | 3 | 6 | 3. The method of claim 2 including the further steps of using historical statistics data to identify the past behavior of said components and combining the enriched alert and identified past behavior of said components to generate at least one alert resolution action. | 3. The method of claim 2 including the further steps of using historical statistics data to identify the past behavior of said components and combining the enriched alert and identified past behavior of said components to generate at least one alert resolution action. 6. The method of claim 3 wherein the said computer network is made of several data centers. | 0.830855 |
7,533,372 | 11 | 17 | 11. A system for modifying a computer system or computer application from a first language to at least a second language comprising: means for determining a structure of a system about to be migrated; means for storing migration information based on the determination of the structure; means for performing said migration based on said stored migration information, wherein performing said migration modifies at least some core code of the computer system from a language dependent form into a language independent form; means for performing said migration based on a module-type migration and based on said stored information to a stored link to provide a path backwards to reestablish the stored link using pre-migration information including: means for setting a user-related string; means for setting at least one system-wide string, with each user-related or system wide setting string allowing a registry value association between said stored migration information and a stored registry in an automatically generated string table; wherein said migration information can compare a file name with said stored registry, to said automatically generated string table; and means for performing said migration based on said stored migration information to a stored registry to synchronize the post-migration system structure. | 11. A system for modifying a computer system or computer application from a first language to at least a second language comprising: means for determining a structure of a system about to be migrated; means for storing migration information based on the determination of the structure; means for performing said migration based on said stored migration information, wherein performing said migration modifies at least some core code of the computer system from a language dependent form into a language independent form; means for performing said migration based on a module-type migration and based on said stored information to a stored link to provide a path backwards to reestablish the stored link using pre-migration information including: means for setting a user-related string; means for setting at least one system-wide string, with each user-related or system wide setting string allowing a registry value association between said stored migration information and a stored registry in an automatically generated string table; wherein said migration information can compare a file name with said stored registry, to said automatically generated string table; and means for performing said migration based on said stored migration information to a stored registry to synchronize the post-migration system structure. 17. The system according to claim 11 , wherein said means for performing further comprises; means for unlocking a registry. | 0.671123 |
7,962,550 | 1 | 3 | 1. A machine readable storage having stored thereon a computer program for discussion forum management, the computer program comprising a routine set of instructions which when executed by a machine cause the machine to perform the steps of: receiving externally sourced data for posting in a discussion forum resource; creating a new topic thread for said externally sourced data; and, responsively posting[s] to said externally sourced data in said new topic thread. | 1. A machine readable storage having stored thereon a computer program for discussion forum management, the computer program comprising a routine set of instructions which when executed by a machine cause the machine to perform the steps of: receiving externally sourced data for posting in a discussion forum resource; creating a new topic thread for said externally sourced data; and, responsively posting[s] to said externally sourced data in said new topic thread. 3. The machine readable storage of claim 1 , wherein said externally sourced data comprises data selected from the group consisting of text, audio, imagery and video. | 0.796069 |
8,364,661 | 1 | 5 | 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. 5. The non-transitory, computer readable media as recited in claim 1 , wherein the instructions search the input customer master file for textual transition indicators to discern each item entry within the input customer master file. | 0.705063 |
8,229,252 | 27 | 55 | 27. A method comprising: recognizing an aspect of an item in response to an annotation environment signal that includes a context information indicative of a recognizable aspect of an item, the recognizable aspect of the item being indicative of an incidental element capable of distinguishing the item, the incidental element comprising at least a physical attribute of the item; processing the annotation environment signal, the processing comprising at least a pre-recognition stage, a slicing stage, and a marking stage; recognizing a user expression associated with the recognizable aspect of the item in response to an expression signal that includes an annotation information indicative of a user expression associated with the recognizable aspect of the item; and electronically associating the recognized user expression and the recognizable aspect of the item. | 27. A method comprising: recognizing an aspect of an item in response to an annotation environment signal that includes a context information indicative of a recognizable aspect of an item, the recognizable aspect of the item being indicative of an incidental element capable of distinguishing the item, the incidental element comprising at least a physical attribute of the item; processing the annotation environment signal, the processing comprising at least a pre-recognition stage, a slicing stage, and a marking stage; recognizing a user expression associated with the recognizable aspect of the item in response to an expression signal that includes an annotation information indicative of a user expression associated with the recognizable aspect of the item; and electronically associating the recognized user expression and the recognizable aspect of the item. 55. The method of claim 27 , wherein the marking stage includes marking segments of the annotation environment signal based upon at least one of one or more GPS coordinates, and/or a temperature, and/or an orientation parameter of a device that generated the annotation signal. | 0.5 |
9,633,095 | 22 | 23 | 22. The method of claim 14 , further comprising identifying the incremental transactional data present on the plurality of source machines. | 22. The method of claim 14 , further comprising identifying the incremental transactional data present on the plurality of source machines. 23. The method of claim 22 , further comprising triggering an alert to the data extraction module to extract the incremental transactional data from the plurality of source machines. | 0.5 |
8,020,104 | 15 | 16 | 15. A system for improving responses to context information based on automated learning techniques, multiple responses each being associated with a group of context information, comprising: at least one processor configured to execute: a processor; a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions to implement the system, including: a learning component that receives indications of past user actions by at least one user related to each of multiple automatically generated responses and of context information related to each of the multiple responses, the context information includes at least one attribute, the at least one attribute includes an attribute value and an uncertainty value of the attribute value, wherein the uncertainty value indicates a range of values around the attribute value that the attribute value will likely be within, and the learning component automatically detects a relationship between a group of context information and one of the responses based on the received indications and at least one defined theme, wherein the theme includes a related set of attributes that reflect a context related to a user; and a response modifier component that creates an association between the group of context information and the one response. | 15. A system for improving responses to context information based on automated learning techniques, multiple responses each being associated with a group of context information, comprising: at least one processor configured to execute: a processor; a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions to implement the system, including: a learning component that receives indications of past user actions by at least one user related to each of multiple automatically generated responses and of context information related to each of the multiple responses, the context information includes at least one attribute, the at least one attribute includes an attribute value and an uncertainty value of the attribute value, wherein the uncertainty value indicates a range of values around the attribute value that the attribute value will likely be within, and the learning component automatically detects a relationship between a group of context information and one of the responses based on the received indications and at least one defined theme, wherein the theme includes a related set of attributes that reflect a context related to a user; and a response modifier component that creates an association between the group of context information and the one response. 16. The system of claim 15 wherein the system is a wearable computer. | 0.5 |
9,047,869 | 7 | 8 | 7. An article of manufacture comprising a computer-readable medium storing a computer program that, when executed by at least one processor, causes the at least one processor to perform a method for voice enabling a Web page, the method comprising: receiving speech input for an input field in the Web page; determining whether the input field is a free form input field; and performing a plurality of first actions in response to determining that the input field is not a free form input field, wherein the plurality of first actions includes: generating a speech grammar for the input field based upon terms associated with the input field, wherein the terms associated with the input field comprise terms in a hidden title attribute of the input field, and wherein generating the speech grammar comprises generating the speech grammar for the input field based upon the terms in the hidden title attribute; providing the received speech input and the generated speech grammar to an ASR engine configured to recognize the received speech input to produce a first textual equivalent to the received speech input using the generated speech grammar; and inserting the first textual equivalent into the input field. | 7. An article of manufacture comprising a computer-readable medium storing a computer program that, when executed by at least one processor, causes the at least one processor to perform a method for voice enabling a Web page, the method comprising: receiving speech input for an input field in the Web page; determining whether the input field is a free form input field; and performing a plurality of first actions in response to determining that the input field is not a free form input field, wherein the plurality of first actions includes: generating a speech grammar for the input field based upon terms associated with the input field, wherein the terms associated with the input field comprise terms in a hidden title attribute of the input field, and wherein generating the speech grammar comprises generating the speech grammar for the input field based upon the terms in the hidden title attribute; providing the received speech input and the generated speech grammar to an ASR engine configured to recognize the received speech input to produce a first textual equivalent to the received speech input using the generated speech grammar; and inserting the first textual equivalent into the input field. 8. The article of manufacture of claim 7 , wherein the method further comprises: performing a plurality of second actions in response to determining that the input field is a free form field, wherein the plurality of second actions includes: identifying an external statistical language model (SLM) specified in a markup language element associated with the input field, wherein the markup language element is an HTML element; providing, by using at least one processor, the received speech input and the SLM to an automatic speech recognition (ASR) engine configured to recognize the received speech input to produce a second textual equivalent to the received speech input using the SLM; and inserting the second textual equivalent into the input field. | 0.5 |
9,619,551 | 4 | 5 | 4. A system according to claim 1 , wherein the central processing unit further represents latent semantics of the document set by mapping each term in the document set against a total frequency occurrence, wherein the total frequency occurrence is calculated as a sum of the term frequencies within each document in the set. | 4. A system according to claim 1 , wherein the central processing unit further represents latent semantics of the document set by mapping each term in the document set against a total frequency occurrence, wherein the total frequency occurrence is calculated as a sum of the term frequencies within each document in the set. 5. A system according to claim 4 , wherein the central processing unit further selects a median value and edge conditions for the total frequency occurrences of the terms and generates the subset of documents from those documents in the set that satisfy the edge conditions. | 0.5 |
7,606,797 | 1 | 5 | 1. A computer implemented method for extracting attribute values from formatted data, the method comprising the steps of: maintaining, by a computer, an attribute repository containing information concerning a plurality of attributes, wherein an attribute comprises an entity for which any of a plurality of values to which is assigned one from a finite group of values, and wherein the information concerning each attribute comprises at least one matching attribute name and at least one matching value for that attribute; parsing formatted data and creating a plurality of elements, by a computer, each element representing a segment of the data, comprising a canonical representation of the data, independent of the data format, said canonical representation comprising a sequence at least of text elements, each text element representing a contiguous unit of text from said formatted data, wherein said canonical representation excludes non-substantive content; scanning, by a computer, the elements of the plurality for occurrences of attribute values; ranking, by a computer, each element based on how many distinct attributes occur in that element; for each of a plurality of attributes, ranking, by a computer, each matching value for that attribute based on the highest ranking of an element in which that value occurs, and on an occurrence of that value in the same element as an occurrence of a matching name of that attribute; for each of a plurality of values occurring in the formatted data, inferring, by a computer, occurrence in the formatted data of the attribute for which that value has the highest ranking, and assigning that value to that attribute; and preparing a summary of the data, using at least one attribute inferred to occur in the data and an assigned value of said at least one attribute, by a computer. | 1. A computer implemented method for extracting attribute values from formatted data, the method comprising the steps of: maintaining, by a computer, an attribute repository containing information concerning a plurality of attributes, wherein an attribute comprises an entity for which any of a plurality of values to which is assigned one from a finite group of values, and wherein the information concerning each attribute comprises at least one matching attribute name and at least one matching value for that attribute; parsing formatted data and creating a plurality of elements, by a computer, each element representing a segment of the data, comprising a canonical representation of the data, independent of the data format, said canonical representation comprising a sequence at least of text elements, each text element representing a contiguous unit of text from said formatted data, wherein said canonical representation excludes non-substantive content; scanning, by a computer, the elements of the plurality for occurrences of attribute values; ranking, by a computer, each element based on how many distinct attributes occur in that element; for each of a plurality of attributes, ranking, by a computer, each matching value for that attribute based on the highest ranking of an element in which that value occurs, and on an occurrence of that value in the same element as an occurrence of a matching name of that attribute; for each of a plurality of values occurring in the formatted data, inferring, by a computer, occurrence in the formatted data of the attribute for which that value has the highest ranking, and assigning that value to that attribute; and preparing a summary of the data, using at least one attribute inferred to occur in the data and an assigned value of said at least one attribute, by a computer. 5. The method of claim 1 , wherein inferring, by a computer, occurrence of specific attributes in the formatted data and assigning, by a computer, most appropriate occurring values to the specific attributes is based at least upon at least one maintained datum concerning attributes from a group of data concerning attributes consisting of: a set of matching values for each of a plurality of attributes; a set of matching names for each of a plurality of attributes; and a number of matching values for each of a plurality of attributes. | 0.595489 |
8,918,323 | 17 | 18 | 17. The system of claim 15 , wherein the one or more tables include a first table and a second table that comprise, respectively, a first entry and a second entry, and wherein the substitution unit of the first entry is different from the substitution unit of the second entry. | 17. The system of claim 15 , wherein the one or more tables include a first table and a second table that comprise, respectively, a first entry and a second entry, and wherein the substitution unit of the first entry is different from the substitution unit of the second entry. 18. The system of claim 17 , wherein the substitution unit in the first entry is less inclusive than the substitution unit in the second entry. | 0.5 |
4,803,641 | 2 | 5 | 2. A knowledge engineering tool comprising a computer having memory for storing a knowledge base and memory for storing predetermined instructions including means to augment and edit the knowledge base, and means for interpreting the knowledge base to run an interactive consultation with the user to determine the value of at least one predetermined goal expression, wherein said knowledge base includes rules including premises having logical operations and corresponding conclusions concluding at least one value for said goal expression, said rules including rules having universally quantified variables, certainty factors associated with said rules for encoding uncertain as well as certain knowledge, propositions including arithmetic operations, propositions responsive to whether a value of a predetermined expression has been determined with a predetermined degree of certainty, and wherein said means for interpreting the knowledge base includes means for determining the value of said goal expression including means for invoking and chaining said rules to conclude a value for said goal expression, means for evaluating the logical operations of the premises of the invoked rules and selecting certainty factors for the concluded values based on the certainty factors of the rules and the certainty factors of the premises, means for updating the certainty factor of a value of an expression by combining certainty factors, means for evaluating said propositions, means for instantiating and deinstantiating the universally quantified variables in said rules, and means for conveying to the user said value of said goal expression and its certainty factor. | 2. A knowledge engineering tool comprising a computer having memory for storing a knowledge base and memory for storing predetermined instructions including means to augment and edit the knowledge base, and means for interpreting the knowledge base to run an interactive consultation with the user to determine the value of at least one predetermined goal expression, wherein said knowledge base includes rules including premises having logical operations and corresponding conclusions concluding at least one value for said goal expression, said rules including rules having universally quantified variables, certainty factors associated with said rules for encoding uncertain as well as certain knowledge, propositions including arithmetic operations, propositions responsive to whether a value of a predetermined expression has been determined with a predetermined degree of certainty, and wherein said means for interpreting the knowledge base includes means for determining the value of said goal expression including means for invoking and chaining said rules to conclude a value for said goal expression, means for evaluating the logical operations of the premises of the invoked rules and selecting certainty factors for the concluded values based on the certainty factors of the rules and the certainty factors of the premises, means for updating the certainty factor of a value of an expression by combining certainty factors, means for evaluating said propositions, means for instantiating and deinstantiating the universally quantified variables in said rules, and means for conveying to the user said value of said goal expression and its certainty factor. 5. The knowledge engineering tool as claimed in claim 2, wherein the same variables are used in more than one rule, and said means for instantiating and de-instantiating includes means for localizing variable bindings to the rules in which the variable bindings are applied. | 0.665854 |
8,599,801 | 8 | 13 | 8. A mobile device for sharing information, comprising: a memory component for storing data; and a processing component for executing data that enables actions, comprising: creating a membership group to a spontaneous event of a gathering of people in a physical location; sharing, during the event, at least one of media content or text message to at least one other mobile device associated with a member of the group, wherein sharing or the media content further comprises enabling automatic posting of the media content to a website associated with the event independent of further actions by the mobile device; enabling a determination of an initial start time or an end time of the spontaneous event based on the sharing of the at least one media content or text message; and determining a revised start time as when a rate of sharing of messages exceeds a threshold during the spontaneous event, wherein the sharing of messages includes messages received from one member of the group that are distributed to other members of the group. | 8. A mobile device for sharing information, comprising: a memory component for storing data; and a processing component for executing data that enables actions, comprising: creating a membership group to a spontaneous event of a gathering of people in a physical location; sharing, during the event, at least one of media content or text message to at least one other mobile device associated with a member of the group, wherein sharing or the media content further comprises enabling automatic posting of the media content to a website associated with the event independent of further actions by the mobile device; enabling a determination of an initial start time or an end time of the spontaneous event based on the sharing of the at least one media content or text message; and determining a revised start time as when a rate of sharing of messages exceeds a threshold during the spontaneous event, wherein the sharing of messages includes messages received from one member of the group that are distributed to other members of the group. 13. The mobile device of claim 8 , wherein sharing the media content further comprises automatically annotating the media content based at least in part on a physical location of the mobile device, a time, an identity of member of the group. | 0.690231 |
8,667,005 | 17 | 18 | 17. The system of claim 16 , wherein a card sort method is used to perform the group assignments and the name assignments. | 17. The system of claim 16 , wherein a card sort method is used to perform the group assignments and the name assignments. 18. The system of claim 17 , wherein the group assignments performed by a first set of individuals is validated via a reverse card sort method. | 0.5 |
8,452,668 | 1 | 15 | 1. A system comprising: a) a processor; and b) a computer memory in communication with the processor, the memory containing one or more models utilized to process a customer interaction by software that is executed by the processor, said customer interaction comprising: i) one or more statements made by a customer; ii) one or more prompts played for said customer; c) a computer-readable storage medium storing a set of computer executable instructions and coupled to the processor, wherein the processor is configured to execute instructions to: i) coordinate processing of said customer interaction; ii) maintain a set of context information related to said customer interaction; iii) create a data record comprising the set of context information related to said customer interaction; iv) store the set of context information from said data record in said computer memory; v) utilize the set of context information stored in said computer memory to automatically create one or more model updates without human intervention; and vi) automatically update one or more of said models using one or more of said model updates. | 1. A system comprising: a) a processor; and b) a computer memory in communication with the processor, the memory containing one or more models utilized to process a customer interaction by software that is executed by the processor, said customer interaction comprising: i) one or more statements made by a customer; ii) one or more prompts played for said customer; c) a computer-readable storage medium storing a set of computer executable instructions and coupled to the processor, wherein the processor is configured to execute instructions to: i) coordinate processing of said customer interaction; ii) maintain a set of context information related to said customer interaction; iii) create a data record comprising the set of context information related to said customer interaction; iv) store the set of context information from said data record in said computer memory; v) utilize the set of context information stored in said computer memory to automatically create one or more model updates without human intervention; and vi) automatically update one or more of said models using one or more of said model updates. 15. The system of claim 1 wherein said processor is further configured to execute instructions to automatically update one or more of said models using one or more of said model updates in response to a trigger, wherein the trigger is a usage milestone. | 0.863538 |
10,102,194 | 1 | 4 | 1. A computer storage media storing computer-readable instructions that when executed cause a computing device to: receive a request from a web browser for an anchored annotation associated with particular content; retrieve anchored annotations associated with the particular content; provide the retrieved anchored annotations; and provide a visual indication about content change of anchoring text within the particular content when a match score is less than a threshold, wherein the visual indication comprises stored original text displayed with the anchored annotation. | 1. A computer storage media storing computer-readable instructions that when executed cause a computing device to: receive a request from a web browser for an anchored annotation associated with particular content; retrieve anchored annotations associated with the particular content; provide the retrieved anchored annotations; and provide a visual indication about content change of anchoring text within the particular content when a match score is less than a threshold, wherein the visual indication comprises stored original text displayed with the anchored annotation. 4. The computer storage media of claim 1 , storing further computer-readable instructions that when executed cause the computing device to: filter the retrieved anchored annotations based on a user identifier associated with an annotation author. | 0.515748 |
8,494,835 | 11 | 20 | 11. A post-editing method for correcting translation errors, comprising: estimating translation errors using an error-specific language model suitable for a type of error desired to be corrected from translation result obtained using a translation system; determining an order of correction of the translation errors; generating error-corrected word candidates, executed by a processing apparatus, for respective estimated translation errors on a basis of an analysis of original text by the translation system; and selecting a final corrected word from among the error-corrected word candidates using the error-specific language model suitable for the type of error desired to be corrected, and incorporating the final corrected word in the translation result, thus correcting the translation errors. | 11. A post-editing method for correcting translation errors, comprising: estimating translation errors using an error-specific language model suitable for a type of error desired to be corrected from translation result obtained using a translation system; determining an order of correction of the translation errors; generating error-corrected word candidates, executed by a processing apparatus, for respective estimated translation errors on a basis of an analysis of original text by the translation system; and selecting a final corrected word from among the error-corrected word candidates using the error-specific language model suitable for the type of error desired to be corrected, and incorporating the final corrected word in the translation result, thus correcting the translation errors. 20. The post-editing method of claim 11 , wherein said correcting the errors includes: calculating probabilities of sentences in which an erroneous word in each erroneous sentence is replaced with relevant error-corrected word candidate by using the error-specific language model; and selecting a word having a highest probability, from among the corrected word candidates, as a corrected word. | 0.5 |
8,180,804 | 1 | 8 | 1. A method comprising: maintaining, by one or more computing systems, access to a data store of information corresponding to one or more of a plurality of users of a social network environment and one or more of a plurality of concepts and comprising: a plurality of nodes including a set of user nodes that each correspond to a respective user, and a set of concept nodes that each correspond to a respective concept, each node of the sets of nodes being associated with a corresponding structured document; and a plurality of edges that each define a connection between a corresponding pair of nodes from the plurality of nodes; receiving, by the one or more computing systems, a request from a first user corresponding to a first user node for a structured document corresponding to a first concept node; determining, by the one or more computing systems, a first data set that identifies concept nodes connected by respective edges with one or more user nodes that are each connected by respective edges with both the first user node and the first concept node; determining, by the one or more computing systems, a second data set that identifies concept nodes connected by respective edges with the first concept node and one or more user nodes that are each connected to the first user node; generating, by the one or more computing systems, a score for each concept node in the first and second data sets based at least in part on the number of user nodes connected to both the first user node and to the respective concept nodes in the first and second data sets; selecting, by the one or more computing systems, one or more concept nodes based on their respective scores as recommended nodes; and transmitting to the client device, by the one or more computing systems, the structured document corresponding to the first concept node, wherein the structured document comprises code executable by a client application to render node names or other identifiers of the recommended nodes for display. | 1. A method comprising: maintaining, by one or more computing systems, access to a data store of information corresponding to one or more of a plurality of users of a social network environment and one or more of a plurality of concepts and comprising: a plurality of nodes including a set of user nodes that each correspond to a respective user, and a set of concept nodes that each correspond to a respective concept, each node of the sets of nodes being associated with a corresponding structured document; and a plurality of edges that each define a connection between a corresponding pair of nodes from the plurality of nodes; receiving, by the one or more computing systems, a request from a first user corresponding to a first user node for a structured document corresponding to a first concept node; determining, by the one or more computing systems, a first data set that identifies concept nodes connected by respective edges with one or more user nodes that are each connected by respective edges with both the first user node and the first concept node; determining, by the one or more computing systems, a second data set that identifies concept nodes connected by respective edges with the first concept node and one or more user nodes that are each connected to the first user node; generating, by the one or more computing systems, a score for each concept node in the first and second data sets based at least in part on the number of user nodes connected to both the first user node and to the respective concept nodes in the first and second data sets; selecting, by the one or more computing systems, one or more concept nodes based on their respective scores as recommended nodes; and transmitting to the client device, by the one or more computing systems, the structured document corresponding to the first concept node, wherein the structured document comprises code executable by a client application to render node names or other identifiers of the recommended nodes for display. 8. The method of claim 1 , wherein generating a score for each concept node comprises generating and summing or otherwise combining: one or more coefficient scores between each concept node in the first and second data sets and each of the user nodes connected with the user node corresponding to the first user; one or more coefficient scores between each concept node in the first and second data sets and the node corresponding to the first user; one or more coefficient scores between each concept node in the first and second data sets and the first concept node; or one or more coefficient scores between the node corresponding to the first user and each of the user nodes connected with a concept node in the first or second data sets. | 0.683177 |
9,165,064 | 7 | 8 | 7. A computer system for providing context aware prompts and alerts, the computer system comprising: an application computer server, wherein a plurality of users are communicatively connected to the application computer server to create one or more notes, and wherein a plurality of services are communicatively connected to the application computer server; and a computer database for storing the notes created by the users, wherein the application computer server operates a plurality of functions each executable by the computer server, the functions comprising: (a) a note taking function for allowing each of the users to create one or more of the note, wherein each of the notes comprises text, audio media, visual media, audio-visual media, recorded data, a weblink, a pointer to an information source, or any combination thereof; (b) note enriching function for enriching the note by associating a local contextual trait with the note, wherein the local contextual trait is automatically gathered at the user device while the user creates the note on the user device; (c) binding function for establishing one or more binding rules for the note, wherein the binding rules determine one or more of the plurality of services where the note is to be bound, and wherein the binding rules are changeable; (d) a prompt or alert assigning function for assigning prompts or alerts to the note, wherein the assigning function comprises assigning the local contextual trait associated with the note to the one or more prompts or alerts; (e) a registering function for allowing users to register to prompts or alerts assigned to the note, wherein the registering comprises a defining function to define one or more of the contextual traits for receiving the prompt or alert; and (f) a receiving function for receiving prompts or alerts based on the defined and registered contextual traits. | 7. A computer system for providing context aware prompts and alerts, the computer system comprising: an application computer server, wherein a plurality of users are communicatively connected to the application computer server to create one or more notes, and wherein a plurality of services are communicatively connected to the application computer server; and a computer database for storing the notes created by the users, wherein the application computer server operates a plurality of functions each executable by the computer server, the functions comprising: (a) a note taking function for allowing each of the users to create one or more of the note, wherein each of the notes comprises text, audio media, visual media, audio-visual media, recorded data, a weblink, a pointer to an information source, or any combination thereof; (b) note enriching function for enriching the note by associating a local contextual trait with the note, wherein the local contextual trait is automatically gathered at the user device while the user creates the note on the user device; (c) binding function for establishing one or more binding rules for the note, wherein the binding rules determine one or more of the plurality of services where the note is to be bound, and wherein the binding rules are changeable; (d) a prompt or alert assigning function for assigning prompts or alerts to the note, wherein the assigning function comprises assigning the local contextual trait associated with the note to the one or more prompts or alerts; (e) a registering function for allowing users to register to prompts or alerts assigned to the note, wherein the registering comprises a defining function to define one or more of the contextual traits for receiving the prompt or alert; and (f) a receiving function for receiving prompts or alerts based on the defined and registered contextual traits. 8. The system as set forth in claim 7 , wherein the functions operated by the application computer server comprises a login function, wherein the login function provides login information for one of the users to one of the services, and wherein the login information is provided when one of the notes of the same of the users is bound to the same of the services. | 0.5 |
10,037,313 | 1 | 4 | 1. A method for smoothed captioning of non-speech sounds in an audio stream, comprising: accessing the audio stream; inputting portions of the audio stream into one or more non-speech classifiers for classification; generating, by the non-speech classifiers, for one or more of the portions of the audio stream, a set of raw scores representing likelihoods that a respective portion of the audio stream includes an occurrence of a particular class of the non-speech sounds associated with each of the non-speech classifiers; generating a set of binary scores for each of the sets of raw scores, each set of binary scores generated based on a smoothing of a respective set of raw scores, the smoothing of the respective set of raw scores determined based on the raw scores of the same class of non-speech sounds from neighboring portions of the audio stream in time, wherein for each of the one or more of the portions, a first binary value indicates that a first class of the non-speech sounds occurs in the respective portion, and a second binary value indicates that the first class of the non-speech sounds does not occur in the respective portion, the generating the set of binary scores for each of the sets of raw scores portion, the generating the set of binary scores for each of the sets of raw scores comprises: determining, using transition probabilities and a sequence of emission probabilities, a sequence of most likely binary scores for each set of raw scores, the sequence of binary scores corresponding to a sequence of on states and off states, the sequence of emission probabilities of the on states corresponding to the raw scores of the set of raw scores and the sequence of emission probabilities of the off states corresponding to a function of the raw scores, and the transition probabilities predefined such that a probability of a transition between different states is lower than a probability of transitioning between the same states; and applying a set of non-speech captions to portions of the audio stream in time, each of the sets of non-speech captions based on a different one of the set binary scores of the corresponding portion of the audio stream. | 1. A method for smoothed captioning of non-speech sounds in an audio stream, comprising: accessing the audio stream; inputting portions of the audio stream into one or more non-speech classifiers for classification; generating, by the non-speech classifiers, for one or more of the portions of the audio stream, a set of raw scores representing likelihoods that a respective portion of the audio stream includes an occurrence of a particular class of the non-speech sounds associated with each of the non-speech classifiers; generating a set of binary scores for each of the sets of raw scores, each set of binary scores generated based on a smoothing of a respective set of raw scores, the smoothing of the respective set of raw scores determined based on the raw scores of the same class of non-speech sounds from neighboring portions of the audio stream in time, wherein for each of the one or more of the portions, a first binary value indicates that a first class of the non-speech sounds occurs in the respective portion, and a second binary value indicates that the first class of the non-speech sounds does not occur in the respective portion, the generating the set of binary scores for each of the sets of raw scores portion, the generating the set of binary scores for each of the sets of raw scores comprises: determining, using transition probabilities and a sequence of emission probabilities, a sequence of most likely binary scores for each set of raw scores, the sequence of binary scores corresponding to a sequence of on states and off states, the sequence of emission probabilities of the on states corresponding to the raw scores of the set of raw scores and the sequence of emission probabilities of the off states corresponding to a function of the raw scores, and the transition probabilities predefined such that a probability of a transition between different states is lower than a probability of transitioning between the same states; and applying a set of non-speech captions to portions of the audio stream in time, each of the sets of non-speech captions based on a different one of the set binary scores of the corresponding portion of the audio stream. 4. The method of claim 1 , wherein applying a set of non-speech captions to portions of the audio stream in time further comprises: identifying a plurality of non-speech captions for a plurality of classes of non-speech sounds by: for each non-speech caption, identifying the set of binary scores associated with the class of non-speech sound for the non-speech caption; and determining one or more start and end timestamps for each set of binary scores based on the timestamps of the portions in time associated with each binary score; identifying a plurality of labels corresponding to the plurality of non-speech captions based on the class of non-speech sound associated with each non-speech caption; and applying the plurality of labels corresponding to each non-speech caption based on the start and end timestamps for each non-speech caption. | 0.524636 |
8,103,510 | 13 | 14 | 13. The device control device according to claim 1 so constructed as to be mountable on a vehicle having an on-vehicle device mounted thereon, wherein the process extension means specifies a content of control to be performed on the on-vehicle device based on the specified content of the uttered speech, and performs the specified control. | 13. The device control device according to claim 1 so constructed as to be mountable on a vehicle having an on-vehicle device mounted thereon, wherein the process extension means specifies a content of control to be performed on the on-vehicle device based on the specified content of the uttered speech, and performs the specified control. 14. The device control device according to claim 13 , further comprising: information acquisition means which acquires information via predetermined communication means; and speech output means which outputs a speech based on the information acquired by the information acquisition means, whereby when the control specified by the process execution means is to output the information acquired by the information acquisition means, the speech output means outputs a speech based on the information. | 0.5 |
9,965,545 | 14 | 15 | 14. An apparatus for processing parse tree data, the apparatus comprising: a memory having computer readable instructions; and a processor configured to execute the computer readable instructions, the instructions comprising: receiving, a parse tree data structure, wherein the parse tree data structure is representative of a document object model (DOM) tree data structure; concomitant to receiving the parse tree data structure, receiving an assignment of index values for the DOM nodes consisting of distinct index values for each existing DOM node; receiving a request to manipulate the parse tree data structure, wherein the request comprises an insert DOM node request for a new DOM node; concomitant to receiving the request to manipulate the parse tree data structure, receiving an indication of a parse tree insert location for the new DOM node to be inserted; responsive to receiving the indication of the parse tree insert location: assigning a distinguishable index value to the new DOM node to be inserted; and inserting the new DOM node at the indicated parse tree insert location; receiving a document order comparison request to determine an earlier of a first given DOM node and a second given DOM node; responsive to receiving the document order comparison request, determining whether the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node; responsive to determining that the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node based on the comparison of the index values of the first given DOM node and the second given DOM node; responsive to a determination that the document order comparison request cannot be satisfied by the comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node using a secondary comparison method; performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node; subsequent to receiving the parse tree data structure, storing an initially empty projection containing no associations of DOM nodes to binary tree nodes; responsive to receiving, by the processor, a delete DOM node request, deleting from the binary tree structure a corresponding binary tree node associated with the DOM node for which deletion was requested only when the DOM node has an associated binary tree node; responsive to receiving, by the processor, an insert DOM node request for a new DOM node, the processor identifies the binary tree insertion point location for the corresponding binary tree node associated with the new DOM node by: obtaining a pre-order traversal predecessor DOM node, denoted P, of the new DOM node; responsive to a determination P has an associated binary tree node, identifying a binary tree successor insertion location of the binary tree node associated with P; and responsive to a determination P does not have an associated binary tree node, determining the binary tree insertion point location using a specialized binary tree search using a value of the index of P; and subsequent to performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node, returning the projection and the binary tree data structure to an empty state. | 14. An apparatus for processing parse tree data, the apparatus comprising: a memory having computer readable instructions; and a processor configured to execute the computer readable instructions, the instructions comprising: receiving, a parse tree data structure, wherein the parse tree data structure is representative of a document object model (DOM) tree data structure; concomitant to receiving the parse tree data structure, receiving an assignment of index values for the DOM nodes consisting of distinct index values for each existing DOM node; receiving a request to manipulate the parse tree data structure, wherein the request comprises an insert DOM node request for a new DOM node; concomitant to receiving the request to manipulate the parse tree data structure, receiving an indication of a parse tree insert location for the new DOM node to be inserted; responsive to receiving the indication of the parse tree insert location: assigning a distinguishable index value to the new DOM node to be inserted; and inserting the new DOM node at the indicated parse tree insert location; receiving a document order comparison request to determine an earlier of a first given DOM node and a second given DOM node; responsive to receiving the document order comparison request, determining whether the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node; responsive to determining that the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node based on the comparison of the index values of the first given DOM node and the second given DOM node; responsive to a determination that the document order comparison request cannot be satisfied by the comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node using a secondary comparison method; performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node; subsequent to receiving the parse tree data structure, storing an initially empty projection containing no associations of DOM nodes to binary tree nodes; responsive to receiving, by the processor, a delete DOM node request, deleting from the binary tree structure a corresponding binary tree node associated with the DOM node for which deletion was requested only when the DOM node has an associated binary tree node; responsive to receiving, by the processor, an insert DOM node request for a new DOM node, the processor identifies the binary tree insertion point location for the corresponding binary tree node associated with the new DOM node by: obtaining a pre-order traversal predecessor DOM node, denoted P, of the new DOM node; responsive to a determination P has an associated binary tree node, identifying a binary tree successor insertion location of the binary tree node associated with P; and responsive to a determination P does not have an associated binary tree node, determining the binary tree insertion point location using a specialized binary tree search using a value of the index of P; and subsequent to performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node, returning the projection and the binary tree data structure to an empty state. 15. The apparatus of claim 14 , wherein: the distinct index values for each existing DOM node are non-negative integers; the distinguishable index value assigned to the new DOM node to be inserted is a constant negative integer; the processor determines whether the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node by determining that the index values of the first given DOM node and the second given DOM node are both non-negative; and responsive to a determination that the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node by selecting the given DOM node with the lesser assigned distinct index value. | 0.720681 |
8,265,778 | 1 | 2 | 1. A computer-implemented method of controlling an apparatus comprising: monitoring a stream of events occurring at the apparatus and, for each event, detecting a plurality of features describing the event, at least some of which are related in a hierarchical manner; creating and storing in memory a graphical data structure comprising a plurality of variable nodes connected by edges, wherein the features describing the event are represented by variable nodes and the variable nodes are connected such that sequences of connected variable nodes represent the hierarchical relations between features; storing at each variable node of the graphical data structure, statistics describing a probability distribution representing a latent event score; arranging a training engine to update the statistics on the basis of the monitored event by using a Bayesian machine learning process and also such that latent event score information is propagated along the sequences of variable nodes which represent the hierarchical relations; predicting an event using the graphical data structure and using the predicted event to control the apparatus. | 1. A computer-implemented method of controlling an apparatus comprising: monitoring a stream of events occurring at the apparatus and, for each event, detecting a plurality of features describing the event, at least some of which are related in a hierarchical manner; creating and storing in memory a graphical data structure comprising a plurality of variable nodes connected by edges, wherein the features describing the event are represented by variable nodes and the variable nodes are connected such that sequences of connected variable nodes represent the hierarchical relations between features; storing at each variable node of the graphical data structure, statistics describing a probability distribution representing a latent event score; arranging a training engine to update the statistics on the basis of the monitored event by using a Bayesian machine learning process and also such that latent event score information is propagated along the sequences of variable nodes which represent the hierarchical relations; predicting an event using the graphical data structure and using the predicted event to control the apparatus. 2. A method as claimed in claim 1 wherein creating and storing the graphical data structure comprises creating and storing a tree-based graphical data structure comprising layers of parent and child variable nodes. | 0.696884 |
7,565,630 | 8 | 11 | 8. The method of claim 1 , further comprising: automatically generating the search customization profile by analysis of attributes of the third party website. | 8. The method of claim 1 , further comprising: automatically generating the search customization profile by analysis of attributes of the third party website. 11. The method of claim 8 , wherein automatically generating the search customization profile comprises: identifying outbound links on at least one page of the third party website; determining domains corresponding to the outbound links; and including the determined domains in the search customization profile. | 0.694499 |
9,063,924 | 20 | 26 | 20. A computer system comprising a processor coupled to a memory, wherein the memory is encoded with computer executable instructions that when executed cause the processor to: identify a propagating attribute associated with a parse item of a plurality of parse items, the plurality of parse items arranged in an ordered data structure; determine a direction of propagation of the propagating attribute within the ordered data structure; and selectively associate the propagating attribute with each parse item of the plurality of parse items located in the direction of propagation within the ordered data structure. | 20. A computer system comprising a processor coupled to a memory, wherein the memory is encoded with computer executable instructions that when executed cause the processor to: identify a propagating attribute associated with a parse item of a plurality of parse items, the plurality of parse items arranged in an ordered data structure; determine a direction of propagation of the propagating attribute within the ordered data structure; and selectively associate the propagating attribute with each parse item of the plurality of parse items located in the direction of propagation within the ordered data structure. 26. The computer system of claim 20 , wherein the instructions further cause the processor to replace the parse item with a merged parse item in the ordered data structure, the merged parse item based, at least in part, on the parse item. | 0.758621 |
8,380,507 | 11 | 12 | 11. The electronic device of claim 10 , the at least one program further comprising instructions for: identifying a default language associated with an electronic device providing the speech content; determining that the identified languages are speakable in the default language; and selecting the default language for generating the speech content. | 11. The electronic device of claim 10 , the at least one program further comprising instructions for: identifying a default language associated with an electronic device providing the speech content; determining that the identified languages are speakable in the default language; and selecting the default language for generating the speech content. 12. The electronic device of claim 11 , the at least one program further comprising instructions for: determining whether a minimum amount of speech content generated in the default language from a particular text string in a language other than the default language is understandable. | 0.5 |
9,311,301 | 11 | 20 | 11. A system, comprising: one or more processors; a memory device operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the system to perform functions that comprise: ingesting text data from a plurality of documents containing a plurality of mentions; locating, from the text data, for each of a selected plurality of chains of coreferent mentions, a particular context-based name from the respective chain, wherein the coreferent mentions correspond to entities and the context-based name is a longest name in the respective chain, a last name in the respective chain, or a most frequently occurring name in the respective chain; determining an entity category for each respective one of the plurality of chains; determining one or more entity attributes from structured data and unstructured data; based on the located particular context-based name, the entity category, and the one or more attributes, assigning high-probability coreferent chains to high-confidence buckets, such as to produce a power law probability distribution having a head region and a tail region; and resolving, based at least in part on the power law probability distribution, the coreferent mentions to identify corresponding real-world entities. | 11. A system, comprising: one or more processors; a memory device operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the system to perform functions that comprise: ingesting text data from a plurality of documents containing a plurality of mentions; locating, from the text data, for each of a selected plurality of chains of coreferent mentions, a particular context-based name from the respective chain, wherein the coreferent mentions correspond to entities and the context-based name is a longest name in the respective chain, a last name in the respective chain, or a most frequently occurring name in the respective chain; determining an entity category for each respective one of the plurality of chains; determining one or more entity attributes from structured data and unstructured data; based on the located particular context-based name, the entity category, and the one or more attributes, assigning high-probability coreferent chains to high-confidence buckets, such as to produce a power law probability distribution having a head region and a tail region; and resolving, based at least in part on the power law probability distribution, the coreferent mentions to identify corresponding real-world entities. 20. The system of claim 11 , wherein the stored instructions, when executed by the one or more processors, further cause to the system to perform functions that comprise: generating, based on the assigning of the high-probability coreferent chains to high-confidence buckets, candidates for structured entities; determining overlap between identified high-confidence buckets of both structured data and unstructured data; and for non-zero overlap, allotting structured entities to the tail region and, for trivial overlap, allotting structured entities in the head region such as to enhance a rate of the unstructured-structured data resolution. | 0.599876 |
9,569,537 | 29 | 40 | 29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a search engine server, including instructions configured to cause a data processing apparatus to: detect a request for a search for search results, wherein the request for the search includes topic data describing a search topic, and wherein the request does not include a request for an agent; perform a search for information associated with the search topic; determine a search result, wherein the search result includes the information associated with the search topic; process, by the search engine server, status data stored remotely within an agent search server, wherein the search engine server operates remotely from the agent search server and communicates with the agent search server over a network, wherein the status data corresponds to one or more active relevant agents, wherein the one or more active relevant agents are associated with one or more real-time interaction options, wherein agents are active or inactive, and wherein agents are relevant or irrelevant to the search topic; generate an agent search request using the topic data, wherein the agent search request is separate from the request for the search and includes the topic data describing the search topic, wherein the agent search request is used to determine the one or more active relevant agents associated with the search topic, and wherein agents are determined to be relevant by matching the search topic with a topic included in one or more profiles of the one or more active relevant agents; use the status data to determine whether to associate a real-time interactive element with the search result; associate a real-time interactive element with the search result, wherein the real-time interactive element is separate from the search result, and wherein the real-time interactive element is displayed concurrently with the search result; and detect data corresponding to a selection of the real-time interactive element associated with the search result, wherein the real-time interactive element is associated with one or more agents based on the status data, wherein the selection of the real-time interactive element facilitates a real-time interaction option among two or more devices, and wherein at least one device is associated with an active relevant agent associated with the search topic. | 29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a search engine server, including instructions configured to cause a data processing apparatus to: detect a request for a search for search results, wherein the request for the search includes topic data describing a search topic, and wherein the request does not include a request for an agent; perform a search for information associated with the search topic; determine a search result, wherein the search result includes the information associated with the search topic; process, by the search engine server, status data stored remotely within an agent search server, wherein the search engine server operates remotely from the agent search server and communicates with the agent search server over a network, wherein the status data corresponds to one or more active relevant agents, wherein the one or more active relevant agents are associated with one or more real-time interaction options, wherein agents are active or inactive, and wherein agents are relevant or irrelevant to the search topic; generate an agent search request using the topic data, wherein the agent search request is separate from the request for the search and includes the topic data describing the search topic, wherein the agent search request is used to determine the one or more active relevant agents associated with the search topic, and wherein agents are determined to be relevant by matching the search topic with a topic included in one or more profiles of the one or more active relevant agents; use the status data to determine whether to associate a real-time interactive element with the search result; associate a real-time interactive element with the search result, wherein the real-time interactive element is separate from the search result, and wherein the real-time interactive element is displayed concurrently with the search result; and detect data corresponding to a selection of the real-time interactive element associated with the search result, wherein the real-time interactive element is associated with one or more agents based on the status data, wherein the selection of the real-time interactive element facilitates a real-time interaction option among two or more devices, and wherein at least one device is associated with an active relevant agent associated with the search topic. 40. The computer-program product of claim 29 , wherein data corresponding to a agent is stored in multiple databases. | 0.80303 |
8,788,586 | 18 | 21 | 18. A non-transitory computer readable storage medium storing instructions for creating a website, the instructions executable on a processor and comprising functionality for: receiving, from a business, a request for a website creation recommendation for content of the website; generating, in response to receiving the request, a post comprising a name of the business, a business owner name, and a link to a recommendation page; publishing, using a social network application, the post to a newsfeed in a social network, wherein a plurality of users in the social network subscribe to the newsfeed; receiving, in response to publishing the post and from the plurality of users, a plurality of recommendations comprising recommended content for the website from the recommendation page, wherein the plurality of recommendations are manually input by the plurality of users; presenting, to the business, the plurality of recommendations; receiving, from the business, a selection of one or more website creation recommendations from the plurality of recommendations; selecting a subset of the plurality of recommendations; presenting, to the business, the subset; receiving, from the business, a selection of one or more additional website creation recommendations from the subset; receiving, from the business, a plurality of content items; generating the website creation recommendation page comprising the plurality of content items; receiving, from the plurality of users, a plurality of votes for the plurality of content items; ordering the plurality of content items according to the plurality of votes to generate a plurality of ordered content items; generating a list comprising a plurality of content types relating to the plurality of ordered content items, the plurality of ordered content items, and a plurality of ranks relating to the plurality of ordered content items; presenting, to the business, the list; receiving, from the business, a selection of a content item from the list; extracting, from the selection of website creation recommendations, the one or more additional website creation recommendations, and the content item, the recommended content; generating the website comprising the recommended content to obtain a generated website; and publishing the generated website. | 18. A non-transitory computer readable storage medium storing instructions for creating a website, the instructions executable on a processor and comprising functionality for: receiving, from a business, a request for a website creation recommendation for content of the website; generating, in response to receiving the request, a post comprising a name of the business, a business owner name, and a link to a recommendation page; publishing, using a social network application, the post to a newsfeed in a social network, wherein a plurality of users in the social network subscribe to the newsfeed; receiving, in response to publishing the post and from the plurality of users, a plurality of recommendations comprising recommended content for the website from the recommendation page, wherein the plurality of recommendations are manually input by the plurality of users; presenting, to the business, the plurality of recommendations; receiving, from the business, a selection of one or more website creation recommendations from the plurality of recommendations; selecting a subset of the plurality of recommendations; presenting, to the business, the subset; receiving, from the business, a selection of one or more additional website creation recommendations from the subset; receiving, from the business, a plurality of content items; generating the website creation recommendation page comprising the plurality of content items; receiving, from the plurality of users, a plurality of votes for the plurality of content items; ordering the plurality of content items according to the plurality of votes to generate a plurality of ordered content items; generating a list comprising a plurality of content types relating to the plurality of ordered content items, the plurality of ordered content items, and a plurality of ranks relating to the plurality of ordered content items; presenting, to the business, the list; receiving, from the business, a selection of a content item from the list; extracting, from the selection of website creation recommendations, the one or more additional website creation recommendations, and the content item, the recommended content; generating the website comprising the recommended content to obtain a generated website; and publishing the generated website. 21. The non-transitory computer readable storage of claim 18 , the instructions further comprising functionality for: receiving, from the business, an approval to publish the website without an intervention from the business; and generating, after receiving the approval, a second recommendation based on the plurality of recommendations, wherein the generated website is published without the invention from the business, and wherein the recommended content is further extracted from the second recommendation. | 0.622041 |
8,825,627 | 10 | 12 | 10. The computer-implemented method of claim 9 , wherein utilizing the identified keywords to identify a product category comprises comparing the keywords associated with the requested page to keywords associated with the product categories to identify the product category. | 10. The computer-implemented method of claim 9 , wherein utilizing the identified keywords to identify a product category comprises comparing the keywords associated with the requested page to keywords associated with the product categories to identify the product category. 12. The computer-implemented method of claim 10 , further comprising storing an association between one or more of the products and at least one of the themes. | 0.75 |
9,141,602 | 1 | 11 | 1. A method of identifying a proposed spelling correction for a word that has been determined to at least potentially be misspelled, the method comprising: receiving a group of characters of a candidate spelling correction; determining a canonical version of the word by mapping each character in the word to a corresponding input key assigned to that character and generating, for each corresponding input key, a character set, including character assigned to that corresponding input key, wherein the canonical version of the word comprises a string of the character sets in a same order as the characters in the word; determining for each character of at least a portion of the group of characters of the candidate spelling correction that at least one of: the character validly corresponds with a predetermined portion of the canonical version of the word, and the character is, according to at least one spell check algorithm from among a number of spell check algorithms, within a predetermined edit distance from a predetermined portion of the canonical version of the word; and outputting at least a portion of the candidate spelling correction as a proposed spelling correction. | 1. A method of identifying a proposed spelling correction for a word that has been determined to at least potentially be misspelled, the method comprising: receiving a group of characters of a candidate spelling correction; determining a canonical version of the word by mapping each character in the word to a corresponding input key assigned to that character and generating, for each corresponding input key, a character set, including character assigned to that corresponding input key, wherein the canonical version of the word comprises a string of the character sets in a same order as the characters in the word; determining for each character of at least a portion of the group of characters of the candidate spelling correction that at least one of: the character validly corresponds with a predetermined portion of the canonical version of the word, and the character is, according to at least one spell check algorithm from among a number of spell check algorithms, within a predetermined edit distance from a predetermined portion of the canonical version of the word; and outputting at least a portion of the candidate spelling correction as a proposed spelling correction. 11. The method of claim 1 , further comprising: outputting a proposed spelling correction differing from the misspelled word at most by replacements of characters with equivalent characters and resolutions of incorrect numbers of sequential actuations of particular keys at a position of priority with respect to a proposed spelling correction differing from the misspelled word by an INSERT, a SWAP, a REPLACE, or a DELETE operation with respect to a nonequivalent character. | 0.689295 |
7,644,360 | 32 | 38 | 32. A computer readable medium having instructions for causing a computer to create an interactive graphic user interface (GUI) for providing a diagram of patent claims, the diagram comprising: an interactive graphical user interface (GUI) viewable on an electronic display, the GUI including a diagram of at least part of a patent claims series; wherein the claims are parsed hierarchically wherein the diagram comprises graphical claim structure and textual claim content associated with each patent claim and wherein, for each patent claim, the graphical claim structure fully includes the textual claim content, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim; and the claims, including both the graphical claim structure and the fully included textual claim content, are dynamically compressible hierarchically; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim, and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. | 32. A computer readable medium having instructions for causing a computer to create an interactive graphic user interface (GUI) for providing a diagram of patent claims, the diagram comprising: an interactive graphical user interface (GUI) viewable on an electronic display, the GUI including a diagram of at least part of a patent claims series; wherein the claims are parsed hierarchically wherein the diagram comprises graphical claim structure and textual claim content associated with each patent claim and wherein, for each patent claim, the graphical claim structure fully includes the textual claim content, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim; and the claims, including both the graphical claim structure and the fully included textual claim content, are dynamically compressible hierarchically; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim, and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. 38. The computer readable medium having instructions for causing a computer to create an interactive GUI of claim 32 , wherein the imported claims are an entire patent's claims. | 0.601351 |
8,356,044 | 1 | 9 | 1. A computer-implemented method for providing default hierarchical training for social indexing, comprising: maintaining articles of digital information for social indexing; specifying a hierarchically-structured tree of topics, which each comprise a label comprising one or more words; identifying hard constraints based on the labels comprised in the topic tree and the topic tree's hierarchical structure, and defining the hard constraints to include immutable rules comprising at least one of: requiring that a topic model comprises a single term comprised from a label that is duplicated within the topic tree; requiring that a topic model includes no term from the label for the topic to which the topic model belongs; and when the label is duplicated within the topic tree, requiring that a topic model includes no term from the label of a parent topic for the topic to which the topic model belongs; for each topic in the topic tree, creating a topic model subject to the hard constraints, the topic model comprising a finite state pattern that comprises a pattern evaluable against the articles; evaluating the topic models for the topic tree against the hard constraints and disfavoring those topic models that violate one or more of the immutable rules; and identifying for each topic, the topic model, which best satisfies the constraints. | 1. A computer-implemented method for providing default hierarchical training for social indexing, comprising: maintaining articles of digital information for social indexing; specifying a hierarchically-structured tree of topics, which each comprise a label comprising one or more words; identifying hard constraints based on the labels comprised in the topic tree and the topic tree's hierarchical structure, and defining the hard constraints to include immutable rules comprising at least one of: requiring that a topic model comprises a single term comprised from a label that is duplicated within the topic tree; requiring that a topic model includes no term from the label for the topic to which the topic model belongs; and when the label is duplicated within the topic tree, requiring that a topic model includes no term from the label of a parent topic for the topic to which the topic model belongs; for each topic in the topic tree, creating a topic model subject to the hard constraints, the topic model comprising a finite state pattern that comprises a pattern evaluable against the articles; evaluating the topic models for the topic tree against the hard constraints and disfavoring those topic models that violate one or more of the immutable rules; and identifying for each topic, the topic model, which best satisfies the constraints. 9. A method according to claim 1 , wherein each topic model comprises one of a conjunction and an n-gram, which are both comprised of the same terms as in the label for the topic to which the topic model belongs. | 0.772532 |
7,853,577 | 1 | 4 | 1. A method, including: using a data processor to receive context data associated with a context and a user, the context data including information indicative of a category of offerings in a network-based marketplace, the context data identifying at least one category of products or services; automatically discovering context attributes associated with the context, the context attributes being automatically discovered by processing attribute data received from a plurality of other users, the attribute data being related to the at least one category of products or services; associating the context data and the context attributes with a user identifier corresponding to the user; retrieving data associated with the context; and filtering the data according to the context data and the context attributes to create result data relevant to the user identified by the user identifier, the filtering including filtering the result data according to one or more ratings associated with products or services included in the result data. | 1. A method, including: using a data processor to receive context data associated with a context and a user, the context data including information indicative of a category of offerings in a network-based marketplace, the context data identifying at least one category of products or services; automatically discovering context attributes associated with the context, the context attributes being automatically discovered by processing attribute data received from a plurality of other users, the attribute data being related to the at least one category of products or services; associating the context data and the context attributes with a user identifier corresponding to the user; retrieving data associated with the context; and filtering the data according to the context data and the context attributes to create result data relevant to the user identified by the user identifier, the filtering including filtering the result data according to one or more ratings associated with products or services included in the result data. 4. The method of claim 1 wherein the result data associated with the context includes at least one from a group including a review list, a recommendation list, research from other users, research from the user, a seller list, and a buyer list. | 0.515936 |
8,700,996 | 1 | 3 | 1. A method of processing a document using a computer, comprising: storing a version of the document in a memory of the computer; displaying a portion of the document on a display of the computer, the portion having an associated font face, an associated line spacing, an associated margin, an associated font color and an associated justification; providing a display of available commands for processing the document, the available commands including one or more of changing the associated font face, changing the associated line spacing, changing the associated margin, changing the associated font color and changing the associated justification; monitoring user actions associated with the displayed portion of the document, the user actions including identifying but not executing one of the available commands for processing the document; in response to the action of identifying but not executing one of the available commands being performed by the user, updating the display of the portion of the document on the display of the computer in accordance with the identified command. | 1. A method of processing a document using a computer, comprising: storing a version of the document in a memory of the computer; displaying a portion of the document on a display of the computer, the portion having an associated font face, an associated line spacing, an associated margin, an associated font color and an associated justification; providing a display of available commands for processing the document, the available commands including one or more of changing the associated font face, changing the associated line spacing, changing the associated margin, changing the associated font color and changing the associated justification; monitoring user actions associated with the displayed portion of the document, the user actions including identifying but not executing one of the available commands for processing the document; in response to the action of identifying but not executing one of the available commands being performed by the user, updating the display of the portion of the document on the display of the computer in accordance with the identified command. 3. The method of claim 1 , wherein identifying but not executing comprises hovering a cursor over the one of the available commands. | 0.833753 |
7,610,194 | 15 | 25 | 15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list. | 15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list. 25. The apparatus of claim 15 , further comprising: a module for resolving frequency collisions in said list when said user-defined word and said word from said LDB have equal frequency counts by ordering said user-defined word first. | 0.677686 |
5,465,327 | 7 | 10 | 7. A data processing system having a plurality of user locations for utilization in document administration, said data processing system comprising: a plurality of documents stored within said data processing system, each of said plurality of documents including an associated descriptive profile and being accessible by said plurality of user locations; means for creating an iconic representation of a selected document within said plurality of documents; means for storing said created iconic representation of said selected document within said data processing system at a first selected memory location; means for storing said selected document at a second selected memory location within said data processing system; and means for entering an indication of said first selected memory location within said descriptive profile associated with said selected document wherein upon a transfer of said selected document and said associated descriptive profile to one of said plurality of user locations a user thereat may elect to separately retrieve said iconic representation utilizing said stored indication of said first selected memory location within said descriptive profile. | 7. A data processing system having a plurality of user locations for utilization in document administration, said data processing system comprising: a plurality of documents stored within said data processing system, each of said plurality of documents including an associated descriptive profile and being accessible by said plurality of user locations; means for creating an iconic representation of a selected document within said plurality of documents; means for storing said created iconic representation of said selected document within said data processing system at a first selected memory location; means for storing said selected document at a second selected memory location within said data processing system; and means for entering an indication of said first selected memory location within said descriptive profile associated with said selected document wherein upon a transfer of said selected document and said associated descriptive profile to one of said plurality of user locations a user thereat may elect to separately retrieve said iconic representation utilizing said stored indication of said first selected memory location within said descriptive profile. 10. The data processing system according to claim 7, wherein said means for storing said selected document at a second selected memory location within said data processing system comprises means for storing said selected document as a text only document. | 0.5 |
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