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15. A system for storing ontologies in a relational database, comprising: a processor storing to a non-transitory computer readable storage medium one or more instances as a first entity in a first table of the relational database, storing to the non-transitory computer readable storage medium one or more concepts as a second entity in a second table of the relational database, storing to the non-transitory computer readable storage medium one or more relationship definitions for defining one or more relationships between one or more entities in a third table of the relational database, each of the one or more relationship definitions being stored independent of any other entities, storing to the non-transitory computer readable storage medium one or more type entities with which each of the one or more of concepts and instances are associated in a fourth table of the relational database, each type entity defining one or more formats of entities associated therewith, storing to the non-transitory computer readable storage medium one or more cloud entities in a fifth table of the relational database, each cloud entity comprising one or more attributes with which all entities associated therewith also comprise, storing to the non-transitory computer readable storage medium one or more behavior entities in a sixth table of the relational database, each behavior entity comprising one or more behavior definitions with which all entities associated therewith also comprise, and defining domain entity table records of valid combinations of one or more of instance entities, concept entities, type entities and relationship entities in accordance with knowledgebase associated with the one or more defined domains; wherein one or more documents of unstructured content may be referenced by one or more of the domain entity table if a record in the domain entity table matches a portion of the knowledge representation of the unstructured content. | 15. A system for storing ontologies in a relational database, comprising: a processor storing to a non-transitory computer readable storage medium one or more instances as a first entity in a first table of the relational database, storing to the non-transitory computer readable storage medium one or more concepts as a second entity in a second table of the relational database, storing to the non-transitory computer readable storage medium one or more relationship definitions for defining one or more relationships between one or more entities in a third table of the relational database, each of the one or more relationship definitions being stored independent of any other entities, storing to the non-transitory computer readable storage medium one or more type entities with which each of the one or more of concepts and instances are associated in a fourth table of the relational database, each type entity defining one or more formats of entities associated therewith, storing to the non-transitory computer readable storage medium one or more cloud entities in a fifth table of the relational database, each cloud entity comprising one or more attributes with which all entities associated therewith also comprise, storing to the non-transitory computer readable storage medium one or more behavior entities in a sixth table of the relational database, each behavior entity comprising one or more behavior definitions with which all entities associated therewith also comprise, and defining domain entity table records of valid combinations of one or more of instance entities, concept entities, type entities and relationship entities in accordance with knowledgebase associated with the one or more defined domains; wherein one or more documents of unstructured content may be referenced by one or more of the domain entity table if a record in the domain entity table matches a portion of the knowledge representation of the unstructured content. 18. The system of claim 15 , wherein the one or more instances are associated with one or more data storage locations containing linked data. | 0.527962 |
6. The method of claim 5 and further comprising: calculating the maximum likelihood estimation score from previously classified phrasal translation pairs. | 6. The method of claim 5 and further comprising: calculating the maximum likelihood estimation score from previously classified phrasal translation pairs. 8. The method of claim 6 , wherein calculating maximum likelihood estimation score includes calculating the score based on invalid translations. | 0.949442 |
11. The method according to claim 1 , wherein the step of providing said machine-readable service description comprises the steps of: creating said machine-readable service description; and making available said machine-readable service description to the requesting entity. | 11. The method according to claim 1 , wherein the step of providing said machine-readable service description comprises the steps of: creating said machine-readable service description; and making available said machine-readable service description to the requesting entity. 13. The method according to claim 11 , wherein the step of making available said machine-readable service description comprises the steps of: publishing said machine-readable service description or a pointer thereto to a remote publication server; and retrieving said service description document directly at the remote publication server. | 0.865222 |
23. A computer-readable medium having computer-executable instructions, when executed by a computer configured to: receive an input schema, the input schema specifying how to represent one or more elements in one or more documents; receive one or more rules; analyze the input schema for conformance to the one or more rules; if the input schema does not conform to the one or more rules, generate a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the one or more documents in conformance with the one or more rules; validate a document against the modified schema; and generate a report if the document is not properly validated against the modified schema. | 23. A computer-readable medium having computer-executable instructions, when executed by a computer configured to: receive an input schema, the input schema specifying how to represent one or more elements in one or more documents; receive one or more rules; analyze the input schema for conformance to the one or more rules; if the input schema does not conform to the one or more rules, generate a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the one or more documents in conformance with the one or more rules; validate a document against the modified schema; and generate a report if the document is not properly validated against the modified schema. 24. The computer-readable medium of claim 23 , wherein the document is being transmitted from a first domain to a second domain, the instructions when executed further operable to halt the transmission of the document from the first domain to the second domain if the document is not properly validated against the modified schema. | 0.533816 |
8. A method for exploring complexity in a semiotic environment, the method comprising: receiving, through an interactive portal on a first computing system, a selection of a multi-level model framework of a complex system comprising a plurality of ontologically organized cells, each ontologically organized cell representing a variable of the complex system; receiving, through the interactive portal, a selection of a multi-scale representation defining instructions for generating a plurality of observable elements based on the multi-level model framework, each observable element having at least one attribute modifiable based on at least one of: (i) a value of an ontologically organized cell, (ii) the relationship between a first ontologically organized cell and a second ontologically organized cell, and (iii) a status of an ontologically organized cell in the context of the multi-level model framework; receiving, through the interactive portal, an indication of an objective; dynamically generating an output comprising a plurality of cells based on the plurality of observable elements of the multi-scale representation, on a display of the first computing system or on a display of a second computing system; and dynamically updating the generated output in response to a received setting configuration. | 8. A method for exploring complexity in a semiotic environment, the method comprising: receiving, through an interactive portal on a first computing system, a selection of a multi-level model framework of a complex system comprising a plurality of ontologically organized cells, each ontologically organized cell representing a variable of the complex system; receiving, through the interactive portal, a selection of a multi-scale representation defining instructions for generating a plurality of observable elements based on the multi-level model framework, each observable element having at least one attribute modifiable based on at least one of: (i) a value of an ontologically organized cell, (ii) the relationship between a first ontologically organized cell and a second ontologically organized cell, and (iii) a status of an ontologically organized cell in the context of the multi-level model framework; receiving, through the interactive portal, an indication of an objective; dynamically generating an output comprising a plurality of cells based on the plurality of observable elements of the multi-scale representation, on a display of the first computing system or on a display of a second computing system; and dynamically updating the generated output in response to a received setting configuration. 10. The method of claim 8 , wherein the objective is to make a decision. | 0.656743 |
1. A system implemented in hardware, comprising: a computer operable to: receive, from a document owner via a social media network, a portion of a document and an identification of at least one social media network contact to be notified for reviewing the portion of the document; store the portion of the document and the identification of the at least one social media network contact, as a reviewer of the portion of the document, into a memory; assign, by the document owner, forwarding rights to the at least one reviewer with respect to the portion of the document, the forwarding rights configured to selectively enable and prevent the ability of the at least one reviewer to forward the portion of the document to other individuals through the social media network; generate a link referencing the portion of the document stored in the memory; publish the link to the reviewer for the reviewer to access the portion of the document for reviewing via the social media network; receive a proposed edit associated with the portion of the document from the reviewer, wherein the received proposed edit is accessible to the document owner; and receive, from the document owner, an indication of one of an acceptance of the proposed edit and a rejection of the proposed edit; determine reviewers whose proposed edits are more frequently accepted by the document owner; and indicate the determined reviewers to the document owner; wherein the acceptance causes the computer to automatically update the portion of the document to include the proposed edit, and the rejection causes the computer to maintain the portion of the document without the proposed edit; wherein receiving the identification of the at least one social media network contact includes receiving a user-selected, pre-defined category of social media network contacts, the computer further configured to: receive a level of confidentiality indicator from the document owner for assignment to the portion of the document; and apply a filter to the social media network contacts listed in the category based on the level of confidentiality indicator and a social media network profile for each of the social media network contacts in the category; wherein publishing the link to the reviewer comprises publishing the link for only those social media network contacts that meet criteria of the filter. | 1. A system implemented in hardware, comprising: a computer operable to: receive, from a document owner via a social media network, a portion of a document and an identification of at least one social media network contact to be notified for reviewing the portion of the document; store the portion of the document and the identification of the at least one social media network contact, as a reviewer of the portion of the document, into a memory; assign, by the document owner, forwarding rights to the at least one reviewer with respect to the portion of the document, the forwarding rights configured to selectively enable and prevent the ability of the at least one reviewer to forward the portion of the document to other individuals through the social media network; generate a link referencing the portion of the document stored in the memory; publish the link to the reviewer for the reviewer to access the portion of the document for reviewing via the social media network; receive a proposed edit associated with the portion of the document from the reviewer, wherein the received proposed edit is accessible to the document owner; and receive, from the document owner, an indication of one of an acceptance of the proposed edit and a rejection of the proposed edit; determine reviewers whose proposed edits are more frequently accepted by the document owner; and indicate the determined reviewers to the document owner; wherein the acceptance causes the computer to automatically update the portion of the document to include the proposed edit, and the rejection causes the computer to maintain the portion of the document without the proposed edit; wherein receiving the identification of the at least one social media network contact includes receiving a user-selected, pre-defined category of social media network contacts, the computer further configured to: receive a level of confidentiality indicator from the document owner for assignment to the portion of the document; and apply a filter to the social media network contacts listed in the category based on the level of confidentiality indicator and a social media network profile for each of the social media network contacts in the category; wherein publishing the link to the reviewer comprises publishing the link for only those social media network contacts that meet criteria of the filter. 7. The system of claim 1 , wherein the link provides a web based access to the portion of the document to the reviewer for reviewing. | 0.551804 |
6. The method of claim 3 , further comprising determining that the difference in length between the first and second portions is equal to the difference in length between the alternate first and alternate second portions and, responsive to said determining, outputting the solution and the alternate solution in descending order of priority by obtaining at least a first frequency value of at least a first frequency object for each of the solution and the alternate solution and outputting the solution and the alternate solution in descending order of frequency value. | 6. The method of claim 3 , further comprising determining that the difference in length between the first and second portions is equal to the difference in length between the alternate first and alternate second portions and, responsive to said determining, outputting the solution and the alternate solution in descending order of priority by obtaining at least a first frequency value of at least a first frequency object for each of the solution and the alternate solution and outputting the solution and the alternate solution in descending order of frequency value. 7. The method of claim 6 , further comprising obtaining as the at least a first frequency value for the solution a first frequency value of a first frequency object associated with the first language object summed with a second frequency value of a second frequency object associated with the second language object, and further comprising obtaining as the at least a first frequency value for the alternate solution an alternate first frequency value of an alternate first frequency object associated with the alternate first language object summed with an alternate second frequency value of an alternate second frequency object associated with the alternate second language object. | 0.721287 |
6. The computer of claim 5 , further comprising a touch screen, wherein the processor is further configured to receive input selecting one of the plurality of theme templates wherein the user's finger touches a thumbnail image on the touch screen corresponding to the thumbnail image, and apply a corresponding theme of the selected theme template to the slide. | 6. The computer of claim 5 , further comprising a touch screen, wherein the processor is further configured to receive input selecting one of the plurality of theme templates wherein the user's finger touches a thumbnail image on the touch screen corresponding to the thumbnail image, and apply a corresponding theme of the selected theme template to the slide. 7. The computer of claim 6 , wherein the processor is further configured to: receive further input selecting a theme variation template displayed in the theme gallery; and apply another corresponding theme of the selected theme variation template to the slide. | 0.868525 |
36. A system for speaker identification, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a spoken utterance; generating a first phoneme-independent representation based on the spoken utterance; decomposing the first phoneme-independent representation into at least one content-independent characteristic unit; comparing the at least one content-independent characteristic unit to at least one content-independent recognition distribution value associated with a registered user of the device, the at least one content-independent recognition distribution value previously generated by: generating a second phoneme-independent representation based on speech from the registered user; and decomposing the second phoneme-independent representation into a content-independent recognition unit, the at least one content-independent recognition distribution value based on the content-independent recognition unit; and determining that the spoken utterance is spoken by the registered user if the at least one content-independent characteristic unit is within a threshold limit of the at least one content-independent recognition distribution value. | 36. A system for speaker identification, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a spoken utterance; generating a first phoneme-independent representation based on the spoken utterance; decomposing the first phoneme-independent representation into at least one content-independent characteristic unit; comparing the at least one content-independent characteristic unit to at least one content-independent recognition distribution value associated with a registered user of the device, the at least one content-independent recognition distribution value previously generated by: generating a second phoneme-independent representation based on speech from the registered user; and decomposing the second phoneme-independent representation into a content-independent recognition unit, the at least one content-independent recognition distribution value based on the content-independent recognition unit; and determining that the spoken utterance is spoken by the registered user if the at least one content-independent characteristic unit is within a threshold limit of the at least one content-independent recognition distribution value. 38. The system of claim 36 , wherein decomposing the first phoneme-independent representation further comprises decomposing the first phoneme-independent representation into at least one content input sequence, and wherein determining that the spoken utterance is spoken by the registered user further comprises determining that the spoken utterance is spoken by the registered user if the at least one content input sequence is similar to at least one content reference sequence previously trained by the registered speaker. | 0.502945 |
33. The method of claim 23 , further comprising: determining a most likely context for the natural language utterances; comparing one or more text combinations against one or more grammar expression entries in a context description grammar to identify one or more contexts that completely or partially match the one or more text combinations; providing a relevance score for each of identified matching contexts; selecting the matching context having a highest score as the most likely context for the natural language utterance, wherein the domain agent is associated with the selected context; communicating the request to the domain agent associated with the selected context; and generating the response to the request using content gathered as a result of the domain agent processing the request, wherein the response arranges the content in an order based on the relevance scores for the identified matching contexts. | 33. The method of claim 23 , further comprising: determining a most likely context for the natural language utterances; comparing one or more text combinations against one or more grammar expression entries in a context description grammar to identify one or more contexts that completely or partially match the one or more text combinations; providing a relevance score for each of identified matching contexts; selecting the matching context having a highest score as the most likely context for the natural language utterance, wherein the domain agent is associated with the selected context; communicating the request to the domain agent associated with the selected context; and generating the response to the request using content gathered as a result of the domain agent processing the request, wherein the response arranges the content in an order based on the relevance scores for the identified matching contexts. 37. The method of claim 33 , further comprising: applying prior probabilities or fuzzy possibilities to at least one of keyword matching, user profiles, or a dialog history to identify the one or more contexts. | 0.750976 |
16. A computer-implemented method comprising: providing a file as a long-query to a decomposition model, wherein the decomposition model: partitions the file into at least three separate parts; identifies a first part of the at least three separate parts as file-specific words; represents a second part of the at least three separate parts as topic-related words; and discards a third part of the at least three separate parts as background words; and storing a representation of the file indexed by a representation of the topic-related words and by a separate representation of the file-specific words. | 16. A computer-implemented method comprising: providing a file as a long-query to a decomposition model, wherein the decomposition model: partitions the file into at least three separate parts; identifies a first part of the at least three separate parts as file-specific words; represents a second part of the at least three separate parts as topic-related words; and discards a third part of the at least three separate parts as background words; and storing a representation of the file indexed by a representation of the topic-related words and by a separate representation of the file-specific words. 19. A computer-readable medium having computer-executable instructions encoded thereon to program the computer to implement the method of claim 16 upon execution. | 0.93954 |
1. A method for monitoring the emotional states of conversation participants, the method comprising: monitoring a conversation between a plurality of participants; determining a first emotional state of a first participant of the plurality of participants during a first segment of the monitored conversation; determining a second emotional state of the first participant during a second segment of the monitored conversation; displaying a timeline of the monitored conversation, wherein the timeline indicates the determined first emotional state of the first participant during the first segment of the monitored conversation and further indicates the determined second emotional state of the first participant during the second segment of the monitored conversation, and wherein the displayed timeline is operable by a user to initially display indications of the first emotional state during the first segment and to subsequently display indications of the second emotional state during the second segment. | 1. A method for monitoring the emotional states of conversation participants, the method comprising: monitoring a conversation between a plurality of participants; determining a first emotional state of a first participant of the plurality of participants during a first segment of the monitored conversation; determining a second emotional state of the first participant during a second segment of the monitored conversation; displaying a timeline of the monitored conversation, wherein the timeline indicates the determined first emotional state of the first participant during the first segment of the monitored conversation and further indicates the determined second emotional state of the first participant during the second segment of the monitored conversation, and wherein the displayed timeline is operable by a user to initially display indications of the first emotional state during the first segment and to subsequently display indications of the second emotional state during the second segment. 9. The method of claim 1 , wherein the determined first emotional state is indicated using a first emotionally indicative icon, and wherein the second determined emotional state is indicated using a second emotionally indicative icon. | 0.598092 |
1. A method of cataloguing media files for event-centric organization, comprising: scanning media files for atomic events; applying feature extraction techniques to the atomic events to obtain context information and content information for each atomic event; classifying the atomic events into predetermined classes based on the extracted context and content information; presenting, to a user, the classified atomic events for a user's ratification or rejection; assembling composite events from the ratified atomic events; querying for retrieval of qualified ones of the assembled composite events; assigning an event type to the assembled composite events; and populating parameters defined for the assigned event type with values extracted from atomic events of the assembled composite events; comparing time difference and dissimilarity between two successive events and combining them together; and automatically creating clusters of the atomic events with a plurality of levels of granularity. | 1. A method of cataloguing media files for event-centric organization, comprising: scanning media files for atomic events; applying feature extraction techniques to the atomic events to obtain context information and content information for each atomic event; classifying the atomic events into predetermined classes based on the extracted context and content information; presenting, to a user, the classified atomic events for a user's ratification or rejection; assembling composite events from the ratified atomic events; querying for retrieval of qualified ones of the assembled composite events; assigning an event type to the assembled composite events; and populating parameters defined for the assigned event type with values extracted from atomic events of the assembled composite events; comparing time difference and dissimilarity between two successive events and combining them together; and automatically creating clusters of the atomic events with a plurality of levels of granularity. 8. The method of cataloguing media files for event-centric organization claim 1 , further comprising: grouping atomic events into composite events using color histogram and visual characteristic event detection of the media files scanning for and comparing time and visual information; and arranging media files of the atomic events based on a structure of the assembled composite events. | 0.539833 |
1. A method of offering a service provided by a server computer in a communication network, comprising: sending, from the server computer that provides the service to a client computer, a service description document in a language for describing web services, which is independent of any client or user characteristic, the service description document comprising a description defining the type, content and sequencing of data exchanged between said server and any client when said service is executed, and comprising a description of a processing functionality implemented during a preprocessing or post-processing of data in XML format of a message exchanged during the execution of said service on the communication network, wherein the description of said processing functionality comprises a list of properties supported by said processing functionality, said properties defining at least respectively, the node in the communication network adapted to execute said processing, and the type of processing, wherein the description of said processing functionality comprises a property adapted to specify whether the processing to be carried out is obligatory or optional, and wherein said processing functionality also comprises a property adapted to specify whether said pre-processing is carried out on the reception of said message before executing said service or whether said post-processing is carried out on the sending of said message after executing said service. | 1. A method of offering a service provided by a server computer in a communication network, comprising: sending, from the server computer that provides the service to a client computer, a service description document in a language for describing web services, which is independent of any client or user characteristic, the service description document comprising a description defining the type, content and sequencing of data exchanged between said server and any client when said service is executed, and comprising a description of a processing functionality implemented during a preprocessing or post-processing of data in XML format of a message exchanged during the execution of said service on the communication network, wherein the description of said processing functionality comprises a list of properties supported by said processing functionality, said properties defining at least respectively, the node in the communication network adapted to execute said processing, and the type of processing, wherein the description of said processing functionality comprises a property adapted to specify whether the processing to be carried out is obligatory or optional, and wherein said processing functionality also comprises a property adapted to specify whether said pre-processing is carried out on the reception of said message before executing said service or whether said post-processing is carried out on the sending of said message after executing said service. 11. A computer-readable storage medium on which is stored a computer executable program to implement the method of offering a service according to claim 1 . | 0.524374 |
21. A method, comprising: receiving content to display on a smart sign, the content is in a default language; receiving, from the smart sign, an indication of a mobile device that is in proximity to the smart sign, a preferred language of a user of the mobile device, and a location of the mobile device relative to the smart sign; translating the content into the preferred language of the user; determining at least one visual characteristic for the translated content based on the location of the mobile device; providing the translated content to the smart sign for display based on the at least one visual characteristic; receiving, from the smart sign, an indication that a plurality of mobile devices are now in proximity to the smart sign and a total number of preferred languages of users of the plurality of mobile devices; and providing a non-text version of the content to the smart sign for display in response to the number of preferred languages exceeds a predetermined threshold. | 21. A method, comprising: receiving content to display on a smart sign, the content is in a default language; receiving, from the smart sign, an indication of a mobile device that is in proximity to the smart sign, a preferred language of a user of the mobile device, and a location of the mobile device relative to the smart sign; translating the content into the preferred language of the user; determining at least one visual characteristic for the translated content based on the location of the mobile device; providing the translated content to the smart sign for display based on the at least one visual characteristic; receiving, from the smart sign, an indication that a plurality of mobile devices are now in proximity to the smart sign and a total number of preferred languages of users of the plurality of mobile devices; and providing a non-text version of the content to the smart sign for display in response to the number of preferred languages exceeds a predetermined threshold. 25. The method of claim 21 , further comprising: receiving, from the smart sign, a movement of the mobile device; determining that the mobile device is moving towards a second smart sign; translating other content for the second smart sign into the preferred language of the user; and providing the translated other content to the second smart sign for display before the mobile device enters a proximity of the second smart sign. | 0.725311 |
14. A system, comprising: a data processing apparatus; and a memory apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving text captured from a rendered document during a text capture operation; receiving supplemental information including information relating to circumstances under which the text capture operation was performed, the information relating to circumstances under which the text capture operation was performed comprising a geographic location at which the text capture operation was performed to capture the text from the rendered document; determining, based on the supplemental information including the geographic location at which the text capture operation was performed to capture the text from the rendered document, an action to be performed on the captured text; and causing the action to be performed on the captured text. | 14. A system, comprising: a data processing apparatus; and a memory apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving text captured from a rendered document during a text capture operation; receiving supplemental information including information relating to circumstances under which the text capture operation was performed, the information relating to circumstances under which the text capture operation was performed comprising a geographic location at which the text capture operation was performed to capture the text from the rendered document; determining, based on the supplemental information including the geographic location at which the text capture operation was performed to capture the text from the rendered document, an action to be performed on the captured text; and causing the action to be performed on the captured text. 19. The system of claim 14 , wherein the information relating to the circumstances under which the text capture operation was performed comprises information describing an environment in which the text capture operation was performed. | 0.500953 |
15. The medium of claim 13 further comprising instructions for generalizing the dependency tree to evaluate added terms comprising at least one of a non-fixed-value literal, a multi-valued literal, an in-list, and a variant table, by translating and integrating each added term into the sequence of aggregations. | 15. The medium of claim 13 further comprising instructions for generalizing the dependency tree to evaluate added terms comprising at least one of a non-fixed-value literal, a multi-valued literal, an in-list, and a variant table, by translating and integrating each added term into the sequence of aggregations. 16. The medium of claim 15 further comprising instructions for evaluating the added terms separately at each leaf level of the generalized dependency tree. | 0.916107 |
1. A sewing machine, comprising: a display that displays information; an obtaining device that obtains display data from outside of the sewing machine; a determining device that determines if the display data includes language change information; a nonvolatile storing device that stores the display data rewritably in a nonvolatile condition; a writing device that writes display data obtained by the obtaining device into the nonvolatile storing device when the determining device determines that the display data includes language change information; and a display controller that displays information on the display based on the display data stored in the nonvolatile storing device. | 1. A sewing machine, comprising: a display that displays information; an obtaining device that obtains display data from outside of the sewing machine; a determining device that determines if the display data includes language change information; a nonvolatile storing device that stores the display data rewritably in a nonvolatile condition; a writing device that writes display data obtained by the obtaining device into the nonvolatile storing device when the determining device determines that the display data includes language change information; and a display controller that displays information on the display based on the display data stored in the nonvolatile storing device. 7. The sewing machine according to claim 1, further comprising an instructing device that instructs the obtaining device to obtain display data. | 0.562838 |
1. A system, comprising: a memory storing a plurality of instructions; and one or more processors configured to access the memory, wherein the one or more processors are further configured to execute the plurality of instructions to at least: receive event data from an event stream; identify a continuous query language query for querying the event data of the event stream; generate a first logical plan comprising one or more logical operators of the continuous language query; determine, based at least in part on the one or more logical operators of the continuous query language query in the first logical plan, a first instruction for enabling evaluation of a subset of the one or more logical operators of the continuous query language query; generate, based at least in part on the first instruction in the first logical plan, a second logical plan for implementing the continuous query language query, the second logical plan comprising at least one conditional instruction for skipping evaluation of at least one or more expressions associated with the one or more logical operators after a first expression comprising the one or more expressions has been evaluated; compile at least the second logical plan into machine-readable instructions for implementing the subset of the logical operators of the continuous query language query in the first logical plan; and execute the machine-readable instructions, the machine-readable instructions comprising the conditional instruction for skipping evaluation, at a runtime, of the one or more expressions associated with the subset of the logical operators of the continuous query language query, the conditional instruction identifying, at the runtime, a function comprising a list of input arguments, and the list of input arguments comprising at least one of an input operand indicating a result of execution of a previous instruction in the second logical plan, a storage parameter indicating a storage location to jump to if an expression represented by the input operand satisfies a condition, or a result parameter indicating a result location of execution of the conditional instruction. | 1. A system, comprising: a memory storing a plurality of instructions; and one or more processors configured to access the memory, wherein the one or more processors are further configured to execute the plurality of instructions to at least: receive event data from an event stream; identify a continuous query language query for querying the event data of the event stream; generate a first logical plan comprising one or more logical operators of the continuous language query; determine, based at least in part on the one or more logical operators of the continuous query language query in the first logical plan, a first instruction for enabling evaluation of a subset of the one or more logical operators of the continuous query language query; generate, based at least in part on the first instruction in the first logical plan, a second logical plan for implementing the continuous query language query, the second logical plan comprising at least one conditional instruction for skipping evaluation of at least one or more expressions associated with the one or more logical operators after a first expression comprising the one or more expressions has been evaluated; compile at least the second logical plan into machine-readable instructions for implementing the subset of the logical operators of the continuous query language query in the first logical plan; and execute the machine-readable instructions, the machine-readable instructions comprising the conditional instruction for skipping evaluation, at a runtime, of the one or more expressions associated with the subset of the logical operators of the continuous query language query, the conditional instruction identifying, at the runtime, a function comprising a list of input arguments, and the list of input arguments comprising at least one of an input operand indicating a result of execution of a previous instruction in the second logical plan, a storage parameter indicating a storage location to jump to if an expression represented by the input operand satisfies a condition, or a result parameter indicating a result location of execution of the conditional instruction. 3. The system of claim 1 , wherein the subset includes less than all of the logical operators of the continuous query language query. | 0.567787 |
9. The media of claim 8 wherein the programming instructions, when loaded in the computer system, also cause the computer system, in response to user commands, to perform the following steps: comparing a family of specimen text documents; identifying one paragraph of text within one of the family of specimen text documents that most closely matches a paragraph of text in all of the other specimen text documents, as compared to all of the other paragraphs in the one specimen text document; and generating one of the text templates containing at least the one identified paragraph of text. | 9. The media of claim 8 wherein the programming instructions, when loaded in the computer system, also cause the computer system, in response to user commands, to perform the following steps: comparing a family of specimen text documents; identifying one paragraph of text within one of the family of specimen text documents that most closely matches a paragraph of text in all of the other specimen text documents, as compared to all of the other paragraphs in the one specimen text document; and generating one of the text templates containing at least the one identified paragraph of text. 10. The media of claim 9 wherein the identifying the paragraph that most closely matches uses an edit distance algorithm. | 0.890165 |
1. An online learning dialog system comprising: one or more processing units; memory communicatively coupled to the one or more processing units, the memory having stored instructions that, when executed by the one or more processing units, configure the online learning dialog system to implement: a speech model that receives a speech input and provides speech events; a decision engine model that receives the speech events from the speech model and selects an action based, at least in part, upon a probability distribution, the probability distribution being associated with uncertainty regarding a plurality of parameters of the decision engine model applied to the speech input, wherein the probability distribution is: defined by an influence diagram that is configured to maximize long term expected utility and apply the Thompson strategy; and expressed as: p ( U , V | D , Θ ) = ∏ X ∈ U ⋃ V p ( X | Pa ( X ) , Θ X ) where U denotes chance variables, D denotes decision variables, and V denotes value variables; where Pa(X) denotes a set of parents for node X; and where Θ X denotes a subset of parameters related to the applied speech input in Θ that define local distribution of X; and, a learning component that in an online manner modifies at least one of the parameters of the decision engine model based upon feedback associated with the selected action, wherein the feedback comprises a lack of verbal input from a user of the system or an environment within a predefined period of time. | 1. An online learning dialog system comprising: one or more processing units; memory communicatively coupled to the one or more processing units, the memory having stored instructions that, when executed by the one or more processing units, configure the online learning dialog system to implement: a speech model that receives a speech input and provides speech events; a decision engine model that receives the speech events from the speech model and selects an action based, at least in part, upon a probability distribution, the probability distribution being associated with uncertainty regarding a plurality of parameters of the decision engine model applied to the speech input, wherein the probability distribution is: defined by an influence diagram that is configured to maximize long term expected utility and apply the Thompson strategy; and expressed as: p ( U , V | D , Θ ) = ∏ X ∈ U ⋃ V p ( X | Pa ( X ) , Θ X ) where U denotes chance variables, D denotes decision variables, and V denotes value variables; where Pa(X) denotes a set of parents for node X; and where Θ X denotes a subset of parameters related to the applied speech input in Θ that define local distribution of X; and, a learning component that in an online manner modifies at least one of the parameters of the decision engine model based upon feedback associated with the selected action, wherein the feedback comprises a lack of verbal input from a user of the system or an environment within a predefined period of time. 7. The system of claim 1 , wherein the speech model is configured to: ignore the speech input, execute corresponding to a most likely command associated with the speech input, request to repeat the speech input, and provide information associated with a plurality of likely commands along with a request to confirm the speech input. | 0.5 |
49. The system of claim 48 , where, when formulating the search query refinement suggestion, the processor is further to: compare the computed scores of the unique search queries of the named clusters to a threshold; and select those cluster names with the computed score that exceeds the threshold to obtain the search query refinement suggestions. | 49. The system of claim 48 , where, when formulating the search query refinement suggestion, the processor is further to: compare the computed scores of the unique search queries of the named clusters to a threshold; and select those cluster names with the computed score that exceeds the threshold to obtain the search query refinement suggestions. 50. The system of claim 49 , where, when sorting the formulated search query refinement suggestion, the processor is further to: sort the formulated search query refinement suggestion among a group of search query refinement suggestions based on a relevance score assigned to each of the search result documents corresponding to the identified search documents associated with the named clusters and a number of the identified search documents in the named clusters to obtain a sorted set of search query refinement suggestions. | 0.851575 |
3. The method of claim 1 , wherein the taxonomy is globally managed for a plurality of online marketing campaigns for a plurality of distinct businesses. | 3. The method of claim 1 , wherein the taxonomy is globally managed for a plurality of online marketing campaigns for a plurality of distinct businesses. 6. The method of claim 3 , wherein the plurality of distinct businesses comprises at least one thousand businesses. | 0.97591 |
1. A computer-implemented method of entropy coding for video coding comprising: receiving image data comprising a syntax having a sequence of symbols to be entropy coded; and updating a previous probability from a previous frame relative to a current frame being entropy encoded that a symbol will occur in one of the sequences comprising: setting a search range among a set of possible update probabilities comprising: setting a first candidate probability as one end of the search range by using a count of a syntax counter and without regard to bit-cost to update the previous probability, and; setting another end of the search range as the previous probability; selecting one of the candidate probabilities on a look-up table and within the search range to update the previous probability for coding of the symbol, and selecting based on, at least in part, the bit-cost associated with updating the previous probability with at least one of the candidate probabilities; and updating the previous probability by using the selected candidate probability. | 1. A computer-implemented method of entropy coding for video coding comprising: receiving image data comprising a syntax having a sequence of symbols to be entropy coded; and updating a previous probability from a previous frame relative to a current frame being entropy encoded that a symbol will occur in one of the sequences comprising: setting a search range among a set of possible update probabilities comprising: setting a first candidate probability as one end of the search range by using a count of a syntax counter and without regard to bit-cost to update the previous probability, and; setting another end of the search range as the previous probability; selecting one of the candidate probabilities on a look-up table and within the search range to update the previous probability for coding of the symbol, and selecting based on, at least in part, the bit-cost associated with updating the previous probability with at least one of the candidate probabilities; and updating the previous probability by using the selected candidate probability. 14. The method of claim 1 wherein the search range is determined by using a syntax counter that counts the number of 0s and number of 1s used to code a single bit of a syntax after the syntax has been binarized; the method comprising generating the look-up table by associating one or more potential candidate probabilities with each update probability value of a plurality of the update probability values, wherein the update probability values form an index for the look-up table; wherein the search range is set by associating the previous probability and the first candidate probability with respective update probability values indexing the look-up table; the method comprising: generating the look up table by establishing a range of update probabilities as an index of the look-up table by using initial previous probabilities and corresponding initial first candidate probabilities; generating the look-up table by selecting the candidate probabilities for each update probability indexing the look-up table by selecting the probabilities from an initial range of probabilities for placement on the look-up table, wherein the selected candidate probabilities assigned to an update probability (1) each have different probability update costs relative to each other, and (2) have a probability value closest to the update candidate value that is an initial first candidate probability; limiting the searching to a maximum of three candidate probabilities in addition to the first candidate probability and for each single bit of a syntax; selecting candidate probabilities based on, at least in part, comparing a new probability based value to a previous probability based value; selecting candidate probabilities, at least in part, depending on the results of one of: (1) determining the difference between the new probability based value and a candidate probability from the look up table selected by using the new probability based value as an index number to look up the candidate probability, and (2) determining the difference between (a) a change value based on, at least in part, the difference between the new probability and the previous probability, and (b) a candidate probability from the look up table selected by using the change value as an index number to look up the candidate probability; adjusting an initial value of a probability candidate from the look up table depending on a comparison between the initial value and the previous probability based value, and setting the value of the probability candidate by using the difference in a calculation; and performing an early exit comprising using the first candidate probability for updating when a second probability candidate being the first probability candidate selected from the look-up table has a bit-cost larger than or equal to the bit-cost of the first probability candidate; wherein the bit-cost comprises the bit cost to perform the update or the bit-cost to indicate an update is to be performed or both, and in the bitstream. | 0.529901 |
8. The method of claim 1 , wherein detecting that a media asset includes the given language spoken with the accent includes determining an accent level, the accent level indicating how slight the accent is, the method further comprising: comparing the accent level to the user specific level of difficulty to determine if the user specific level of difficulty is greater than the accent level; and wherein automatically generating for display subtitles for the media asset is further based on determining that the user specific level of difficulty is greater than the accent level. | 8. The method of claim 1 , wherein detecting that a media asset includes the given language spoken with the accent includes determining an accent level, the accent level indicating how slight the accent is, the method further comprising: comparing the accent level to the user specific level of difficulty to determine if the user specific level of difficulty is greater than the accent level; and wherein automatically generating for display subtitles for the media asset is further based on determining that the user specific level of difficulty is greater than the accent level. 9. The method of claim 8 , wherein detecting that a media asset includes the given language spoken with the accent comprises: receiving, from a media source, the media asset and a third data structure indicating a first portion of the media asset during which a specific actor appears; receiving, from the remote source, a fourth data structure associating the specific actor with the accent and with the accent level; and wherein automatically generating for display subtitles for the media asset comprises automatically generating for display subtitles for the media asset during the first portion of the media asset. | 0.915966 |
1. A framework for binding data viewers with one to many objects, comprising: a plurality of classes for associating and synchronizing GUI components and business object (BO) attributes, including: an inspector class; a selection class; and a plurality of editor classes; wherein: the inspector class includes inspector methods and data structures that enable a set of GUI components to be bound to the attributes of a selection of at least one business object (BO); the editor classes include editor methods and data structures that interact with the GUI components and an inspector class instance, each of the editor classes being configured to work with GUI components of a respective component type; and the selection class includes selection methods and data structures that interact with the selection and the inspector class instance; such that an instance of the selection class communicates events involving the selection to the inspector class instance, which responsively triggers instances of the editors to update the GUI components accordingly; and the instances of the editor classes communicate events involving the GUI components to the inspector class instance, which responsively triggers the selection class instance to update the selection accordingly. | 1. A framework for binding data viewers with one to many objects, comprising: a plurality of classes for associating and synchronizing GUI components and business object (BO) attributes, including: an inspector class; a selection class; and a plurality of editor classes; wherein: the inspector class includes inspector methods and data structures that enable a set of GUI components to be bound to the attributes of a selection of at least one business object (BO); the editor classes include editor methods and data structures that interact with the GUI components and an inspector class instance, each of the editor classes being configured to work with GUI components of a respective component type; and the selection class includes selection methods and data structures that interact with the selection and the inspector class instance; such that an instance of the selection class communicates events involving the selection to the inspector class instance, which responsively triggers instances of the editors to update the GUI components accordingly; and the instances of the editor classes communicate events involving the GUI components to the inspector class instance, which responsively triggers the selection class instance to update the selection accordingly. 4. The system of claim 1, wherein each of the editor class instances is associated with a respective GUI component. | 0.608491 |
4. A non-transitory computer-readable medium comprising code that, when executed by at least one computer causes the at least one computer to: receive an audio query; recognize that the audio query matches an audio reference; follow a link between the audio reference and promotional content; deliver the promotional content; and bill a campaign manager user for the delivered promotional content. | 4. A non-transitory computer-readable medium comprising code that, when executed by at least one computer causes the at least one computer to: receive an audio query; recognize that the audio query matches an audio reference; follow a link between the audio reference and promotional content; deliver the promotional content; and bill a campaign manager user for the delivered promotional content. 11. The non-transitory computer-readable medium of claim 4 , further comprising code that causes the at least one computer to: determine a bid amount associated with the promotional content; determine a multiplicity of other bid amounts for the audio reference; and compare the bid amount associated with the promotional content to the multiplicity of other bid amounts. | 0.627757 |
1. A computer-implemented document collaboration system for managing the input of reviewers connected over a network of computers, the document collaboration system comprising: a processor; and a memory coupled to the processor, the memory including instructions that, when executed by the processor, cause the processor to: store a master data file including a document having content created by an owner; create a hierarchical distribution file for tracking access to the document, the hierarchical distribution file including: first data identifying the owner of the document, second data identifying a first level reviewer designated by the owner, third data identifying a second level reviewer designated by the first level reviewer, and fourth data identifying an access level to a designated portion of the document for the first level reviewer, wherein the designated portion of the document is less than the entirety of the document; create a first data file associated with the first level reviewer comprising: first edit data reflecting a first edit made to the content of the document by the first level reviewer within the designated portion of the document, and first index data reflecting a first index to a location of the first edit in the document; and create a second data file associated with the second level reviewer comprising: second edit data reflecting a second edit made to the content of the document by the second level reviewer, and second index data reflecting a second index to a location of the second edit in the document; modify the first data file to include the second edit data and the second index data within the first data file in response to input reflecting that the first level reviewer accepts the second edit data, without modifying the master data file; modify the master data file to include the first edit data and the first index data in response to input reflecting that the owner accepts the first edit data; and modify the master data file to include the second edit data and the second index data incorporated within the first data file in response to input reflecting that the owner accepts the second edit data incorporated within the first data file. | 1. A computer-implemented document collaboration system for managing the input of reviewers connected over a network of computers, the document collaboration system comprising: a processor; and a memory coupled to the processor, the memory including instructions that, when executed by the processor, cause the processor to: store a master data file including a document having content created by an owner; create a hierarchical distribution file for tracking access to the document, the hierarchical distribution file including: first data identifying the owner of the document, second data identifying a first level reviewer designated by the owner, third data identifying a second level reviewer designated by the first level reviewer, and fourth data identifying an access level to a designated portion of the document for the first level reviewer, wherein the designated portion of the document is less than the entirety of the document; create a first data file associated with the first level reviewer comprising: first edit data reflecting a first edit made to the content of the document by the first level reviewer within the designated portion of the document, and first index data reflecting a first index to a location of the first edit in the document; and create a second data file associated with the second level reviewer comprising: second edit data reflecting a second edit made to the content of the document by the second level reviewer, and second index data reflecting a second index to a location of the second edit in the document; modify the first data file to include the second edit data and the second index data within the first data file in response to input reflecting that the first level reviewer accepts the second edit data, without modifying the master data file; modify the master data file to include the first edit data and the first index data in response to input reflecting that the owner accepts the first edit data; and modify the master data file to include the second edit data and the second index data incorporated within the first data file in response to input reflecting that the owner accepts the second edit data incorporated within the first data file. 2. The document collaboration system of claim 1 , wherein the processor generates information that is used to display the document adjacent to at least one of the first edit and the second edit. | 0.515371 |
1. A speech recognition circuit comprising: a circuit for providing state identifiers which identify states corresponding to nodes or groups of adjacent nodes in a lexical tree, and for providing scores corresponding to said state identifiers, the lexical tree comprising a model of words; a memory structure for receiving and storing state identifiers identified by a node identifier identifying a node or group of adjacent nodes, said memory structure being adapted to allow lookup to identify particular state identifiers, reading of the scores corresponding to the state identifiers, and writing back of the scores to the memory structure after modification of the scores; an accumulator for receiving score updates corresponding to particular state identifiers from a score update generating circuit which generates the score updates using audio input, for receiving scores from the memory structure, and for modifying said scores by adding said score updates to said scores; and a selector circuit for selecting at least one node or group of adjacent nodes of the lexical tree according to said scores. | 1. A speech recognition circuit comprising: a circuit for providing state identifiers which identify states corresponding to nodes or groups of adjacent nodes in a lexical tree, and for providing scores corresponding to said state identifiers, the lexical tree comprising a model of words; a memory structure for receiving and storing state identifiers identified by a node identifier identifying a node or group of adjacent nodes, said memory structure being adapted to allow lookup to identify particular state identifiers, reading of the scores corresponding to the state identifiers, and writing back of the scores to the memory structure after modification of the scores; an accumulator for receiving score updates corresponding to particular state identifiers from a score update generating circuit which generates the score updates using audio input, for receiving scores from the memory structure, and for modifying said scores by adding said score updates to said scores; and a selector circuit for selecting at least one node or group of adjacent nodes of the lexical tree according to said scores. 6. The speech recognition circuit of claim 1 , further comprising a counter for sequentially generating state identifiers, and using said generated state identifiers to sequentially lookup said states in the memory structure. | 0.64807 |
22. The method of claim 21 wherein said step of forming a set of possibility regions for a selected one of said classes, comprises the steps of: selecting one of said classes; and selecting a number of said reference feature vectors belonging to said selected class such that each reference feature vector of said number of reference feature vectors form the center of one of said possibility regions of said set of possibility regions associated with said selected class and such that each reference feature vector of said selected class is contained in a possibility region for said selected class. | 22. The method of claim 21 wherein said step of forming a set of possibility regions for a selected one of said classes, comprises the steps of: selecting one of said classes; and selecting a number of said reference feature vectors belonging to said selected class such that each reference feature vector of said number of reference feature vectors form the center of one of said possibility regions of said set of possibility regions associated with said selected class and such that each reference feature vector of said selected class is contained in a possibility region for said selected class. 25. The method as in claim 22 wherein N is defined as the number of features contained in each said reference feature vector. | 0.824751 |
1. A computer-implemented method comprising: determining a parameter of a first microphone and a parameter of a second microphone, wherein the first microphone and the second microphone are associated with a computing device and wherein the parameter of the first microphone and the parameter of the second microphone is a magnitude spectrum parameter; generating a reference parameter based upon, at least in part, at least one of the parameter of the first microphone and the parameter of the second microphone; adjusting a tolerance of at least one of the first microphone and the second microphone, based upon, at least in part, the reference parameter; receiving, at the first microphone, a first speech signal corresponding to an utterance of a speaker, the first speech signal having a first speech signal magnitude; receiving, at the second microphone, a second speech signal corresponding to the utterance of the speaker, the second speech signal having a second speech signal magnitude; comparing at least one of the first speech signal magnitude and the second speech signal magnitude with a third speech signal magnitude, wherein comparing at least one of the first speech signal magnitude and the second speech signal magnitude with the third speech signal magnitude occurs after adjusting the tolerance of at least one of the first microphone and the second microphone; detecting an obstructed microphone based upon, at least in part, comparing at least one of the first speech signal magnitude and the second speech signal magnitude with the third speech signal magnitude; and in response to detecting the obstructed microphone, deactivating a beamforming setting associated with the computing device. | 1. A computer-implemented method comprising: determining a parameter of a first microphone and a parameter of a second microphone, wherein the first microphone and the second microphone are associated with a computing device and wherein the parameter of the first microphone and the parameter of the second microphone is a magnitude spectrum parameter; generating a reference parameter based upon, at least in part, at least one of the parameter of the first microphone and the parameter of the second microphone; adjusting a tolerance of at least one of the first microphone and the second microphone, based upon, at least in part, the reference parameter; receiving, at the first microphone, a first speech signal corresponding to an utterance of a speaker, the first speech signal having a first speech signal magnitude; receiving, at the second microphone, a second speech signal corresponding to the utterance of the speaker, the second speech signal having a second speech signal magnitude; comparing at least one of the first speech signal magnitude and the second speech signal magnitude with a third speech signal magnitude, wherein comparing at least one of the first speech signal magnitude and the second speech signal magnitude with the third speech signal magnitude occurs after adjusting the tolerance of at least one of the first microphone and the second microphone; detecting an obstructed microphone based upon, at least in part, comparing at least one of the first speech signal magnitude and the second speech signal magnitude with the third speech signal magnitude; and in response to detecting the obstructed microphone, deactivating a beamforming setting associated with the computing device. 3. The method of claim 1 , further comprising: deactivating the obstructed microphone. | 0.616834 |
2. A method for using an emergent self-organization characteristic in a natural language for establishing a collaborative content relevance between users and items in a context space, implemented using the computer system of claim 1 , the method comprising the steps of: identifying a plurality of items in the context space with unique item identifiers, one of the plurality of items capable of being independently annotated in the context space by one or more of a plurality of users operating independently of one another without knowledge of each other's activities or existence, the annotating being done in the context space with unique user identifiers using an annotation of at least one keyword from the natural language during an annotation event, the annotation including an association between the at least one keyword, one of the unique item identifiers associated with the one of the plurality of items being independently annotated, and one of the unique user identifiers associated with the independently annotating one of the plurality of users, performed using the means for identifying; copying each of the annotations generated during ones of the annotation event to the at least one computer-readable media for storage therein, performed using the means for copying, the stored annotations containing the ones of the unique user identifier of the independently annotating ones of the plurality of users, the ones of the unique item identifier of the ones of the items being independently annotated, and the at least one keyword, ones of the plurality of users capable of using a different keyword to annotate the same one of the plurality of items; aggregating the stored annotations based on a correlation between users, items and keywords, the correlation associated with the emergent self organization characteristics to form the collaborative content relevance between the plurality of items and the plurality of users, performed using the means for aggregating the stored annotations; and associating, using the collaborative content relevance, one of: ones of the plurality of users with other ones of the plurality of users; and ones of the plurality of items with ones of the plurality of users such that the ones of the plurality of users are capable of discovering the other ones of the plurality of users, and the ones of the plurality of items are capable of discovering the ones of the plurality of users, based on the associated collaborative content relevance, performed using the means for associating. | 2. A method for using an emergent self-organization characteristic in a natural language for establishing a collaborative content relevance between users and items in a context space, implemented using the computer system of claim 1 , the method comprising the steps of: identifying a plurality of items in the context space with unique item identifiers, one of the plurality of items capable of being independently annotated in the context space by one or more of a plurality of users operating independently of one another without knowledge of each other's activities or existence, the annotating being done in the context space with unique user identifiers using an annotation of at least one keyword from the natural language during an annotation event, the annotation including an association between the at least one keyword, one of the unique item identifiers associated with the one of the plurality of items being independently annotated, and one of the unique user identifiers associated with the independently annotating one of the plurality of users, performed using the means for identifying; copying each of the annotations generated during ones of the annotation event to the at least one computer-readable media for storage therein, performed using the means for copying, the stored annotations containing the ones of the unique user identifier of the independently annotating ones of the plurality of users, the ones of the unique item identifier of the ones of the items being independently annotated, and the at least one keyword, ones of the plurality of users capable of using a different keyword to annotate the same one of the plurality of items; aggregating the stored annotations based on a correlation between users, items and keywords, the correlation associated with the emergent self organization characteristics to form the collaborative content relevance between the plurality of items and the plurality of users, performed using the means for aggregating the stored annotations; and associating, using the collaborative content relevance, one of: ones of the plurality of users with other ones of the plurality of users; and ones of the plurality of items with ones of the plurality of users such that the ones of the plurality of users are capable of discovering the other ones of the plurality of users, and the ones of the plurality of items are capable of discovering the ones of the plurality of users, based on the associated collaborative content relevance, performed using the means for associating. 53. The method according to claim 2 , wherein the identifiers are globally unique. | 0.746248 |
6. The one or more hardware storage devices of claim 1 , further comprising: uploading the one or more graphical elements and the selected annotation as a medical file to a clearinghouse. | 6. The one or more hardware storage devices of claim 1 , further comprising: uploading the one or more graphical elements and the selected annotation as a medical file to a clearinghouse. 7. The one or more hardware storage devices of claim 6 , wherein the medical file is accessed from the clearinghouse and displayed with a selectable graphical indicator of proximate areas of the selected annotation which, when selected, render the selected annotation. | 0.923077 |
1. An identity verification system, comprising: a sound input device; a processing device operatively coupled to said sound input device; and a display operatively coupled to said processing device; wherein: said processing device executes computer readable code to create a first visual representation of frequency relationships within a spoken word sensed by the sound input device for output on the display; wherein: said first visual representation is evaluated to determine the identity of the person speaking said spoken word; and wherein: said first visual representation is generated according to a method comprising the steps of: (a) placing twelve labels in a pattern of a circle, said twelve labels corresponding to twelve respective frequencies, such that moving clockwise or counter-clockwise between adjacent ones of said labels represents a first frequency interval; (b) identifying an occurrence of a first frequency within the spoken word; (c) identifying an occurrence of a second frequency within the spoken word; (d) identifying a first label corresponding to the first frequency; (e) identifying a second label corresponding to the second frequency; (f) creating a first line connecting the first label and the second label; and wherein: (1) the first line is a first color if the first frequency and the second frequency are separated by the first frequency interval; (2) the first line is a second color if the first frequency and the second frequency are separated by a first multiple of the first frequency interval; (3) the first line is a third color if the first frequency and the second frequency are separated by a second multiple of the first frequency interval; (4) the first line is a fourth color if the first frequency and the second frequency are separated by a third multiple of the first frequency interval; (5) the first line is a fifth color if the first frequency and the second frequency are separated by a fourth multiple of the first frequency interval; and (6) the first line is a sixth color if the first frequency and the second frequency are separated by a fifth multiple of the first frequency interval. | 1. An identity verification system, comprising: a sound input device; a processing device operatively coupled to said sound input device; and a display operatively coupled to said processing device; wherein: said processing device executes computer readable code to create a first visual representation of frequency relationships within a spoken word sensed by the sound input device for output on the display; wherein: said first visual representation is evaluated to determine the identity of the person speaking said spoken word; and wherein: said first visual representation is generated according to a method comprising the steps of: (a) placing twelve labels in a pattern of a circle, said twelve labels corresponding to twelve respective frequencies, such that moving clockwise or counter-clockwise between adjacent ones of said labels represents a first frequency interval; (b) identifying an occurrence of a first frequency within the spoken word; (c) identifying an occurrence of a second frequency within the spoken word; (d) identifying a first label corresponding to the first frequency; (e) identifying a second label corresponding to the second frequency; (f) creating a first line connecting the first label and the second label; and wherein: (1) the first line is a first color if the first frequency and the second frequency are separated by the first frequency interval; (2) the first line is a second color if the first frequency and the second frequency are separated by a first multiple of the first frequency interval; (3) the first line is a third color if the first frequency and the second frequency are separated by a second multiple of the first frequency interval; (4) the first line is a fourth color if the first frequency and the second frequency are separated by a third multiple of the first frequency interval; (5) the first line is a fifth color if the first frequency and the second frequency are separated by a fourth multiple of the first frequency interval; and (6) the first line is a sixth color if the first frequency and the second frequency are separated by a fifth multiple of the first frequency interval. 8. The method of claim 1 , further comprising the steps of: (g) identifying an occurrence of a third frequency within said spoken word; (h) identifying a third label corresponding to the third frequency; (i) creating a second line connecting the second label and the third label; and (j) creating a third line connecting the third label and the first label. | 0.598738 |
22. The method of claim 21 , further comprising: recalculating mutual information values for remaining pairs of syllable-like units in the training dictionary; selecting a new pair of syllable-like units based on the recalculated mutual information values; and removing the new pair of syllable-like units and substituting a second new syllable-like unit in place of the new pair of syllable-like units in the training dictionary. | 22. The method of claim 21 , further comprising: recalculating mutual information values for remaining pairs of syllable-like units in the training dictionary; selecting a new pair of syllable-like units based on the recalculated mutual information values; and removing the new pair of syllable-like units and substituting a second new syllable-like unit in place of the new pair of syllable-like units in the training dictionary. 23. The method of claim 22 , further comprising using the training dictionary to generate a language model of syllable-like units. | 0.853117 |
3. The method according to claim 1 , further comprising: receiving, by the security module, a management message comprising a command to force the selection of one of the at least two different control words. | 3. The method according to claim 1 , further comprising: receiving, by the security module, a management message comprising a command to force the selection of one of the at least two different control words. 5. The method according to claim 3 , wherein the management message further comprises an indication of a time at which the command is to be executed. | 0.966277 |
20. A computer-implemented method of providing a graphical user interface for electronically displaying search results and related information, the method comprising: under the control of one or more computer systems configured with executable instructions, providing for electronic display a presentation surface of an application, the presentation surface comprising at least a first region and a second region, the first region being arranged for display of search results and the second region including a whiteboard; updating for display at least the second region to include information corresponding to one or more first search results of the first region; detecting, in connection with one or more second search results displayed in the first region, a drag and drop operation, between the first region and the second region, for adding information corresponding to the one or more second search results; and responsive to detection of the drag and drop operation, when the drag and drop operation is from the first region to the second region, updating for display at least the whiteboard of the second region to include the information corresponding to the one or more second search results simultaneously with the information corresponding to the one or more first search results of the first region, wherein the information corresponding to the one or more first search results and the information corresponding to the one or more second search results collectively represent two or more information resources represented by corresponding search result of the first region; and when the drag and drop operation is from the second region to the first region, updating at least the first region with search results associated with content of the second region corresponding with the drag and drop operation. | 20. A computer-implemented method of providing a graphical user interface for electronically displaying search results and related information, the method comprising: under the control of one or more computer systems configured with executable instructions, providing for electronic display a presentation surface of an application, the presentation surface comprising at least a first region and a second region, the first region being arranged for display of search results and the second region including a whiteboard; updating for display at least the second region to include information corresponding to one or more first search results of the first region; detecting, in connection with one or more second search results displayed in the first region, a drag and drop operation, between the first region and the second region, for adding information corresponding to the one or more second search results; and responsive to detection of the drag and drop operation, when the drag and drop operation is from the first region to the second region, updating for display at least the whiteboard of the second region to include the information corresponding to the one or more second search results simultaneously with the information corresponding to the one or more first search results of the first region, wherein the information corresponding to the one or more first search results and the information corresponding to the one or more second search results collectively represent two or more information resources represented by corresponding search result of the first region; and when the drag and drop operation is from the second region to the first region, updating at least the first region with search results associated with content of the second region corresponding with the drag and drop operation. 22. The computer-implemented method of claim 20 , wherein the user input corresponds to a drag and drop operation. | 0.547236 |
9. A knowledge management computing system comprising: a computer storage coupled to a database computing device for storing a plurality of documents in a documents database; a plurality of document collections collected from said documents database by a query engine executed by an application server device, each said document collection being a subset of said plurality of documents having non-unique values on a shared attribute; a founder identification feature of the query engine that identifies one or more founders of said plurality of document collections by: rating one or more individuals first associated with one or more documents of said plurality of document collections, wherein the rating is based on a frequency of workflow actions of the individual, performed on the plurality of documents, evaluated over a fixed period of time following a creation of a first created document of said one or more documents, wherein the workflow actions include editing, responding to, creating, and approving said one or more documents of said plurality of document collections authored by another individual; adding the one or more founders to a list of founders until a number of founders are in the list, the number of founders being a tunable parameter; applying weighting factors to the one or more founders to determine a degree of foundership; ranking the one or more founders based upon, at least in part, the degree of foundership; and a visualization engine executed by a client computing device to display said list of one or more founders on a client display apparatus. | 9. A knowledge management computing system comprising: a computer storage coupled to a database computing device for storing a plurality of documents in a documents database; a plurality of document collections collected from said documents database by a query engine executed by an application server device, each said document collection being a subset of said plurality of documents having non-unique values on a shared attribute; a founder identification feature of the query engine that identifies one or more founders of said plurality of document collections by: rating one or more individuals first associated with one or more documents of said plurality of document collections, wherein the rating is based on a frequency of workflow actions of the individual, performed on the plurality of documents, evaluated over a fixed period of time following a creation of a first created document of said one or more documents, wherein the workflow actions include editing, responding to, creating, and approving said one or more documents of said plurality of document collections authored by another individual; adding the one or more founders to a list of founders until a number of founders are in the list, the number of founders being a tunable parameter; applying weighting factors to the one or more founders to determine a degree of foundership; ranking the one or more founders based upon, at least in part, the degree of foundership; and a visualization engine executed by a client computing device to display said list of one or more founders on a client display apparatus. 10. The system of claim 9 wherein said one or more founders are identified category creators associated with a category, wherein the category is a collection of knowledge resources of similar content associated with at least one of the plurality of document collections. | 0.658484 |
10. The computer-implemented method of claim 9 , wherein auto-completing commands further comprises providing context-sensitive lists that contain code and scripting elements relating to the referenced component, wherein the list box is populated with parameter type signatures, and wherein the corresponding type signature is read from an assembly that corresponds to an assembly reference. | 10. The computer-implemented method of claim 9 , wherein auto-completing commands further comprises providing context-sensitive lists that contain code and scripting elements relating to the referenced component, wherein the list box is populated with parameter type signatures, and wherein the corresponding type signature is read from an assembly that corresponds to an assembly reference. 12. The computer-implemented method of claim 10 , and further comprising compiling the application in the application development environment into application components managed by an application runtime environment to verify type information of external objects corresponding to the referenced component and created using an external runtime environment, and providing a verified application after verification of the type information. | 0.864424 |
3. The method of claim 2 , wherein the dashboard displays at least one of sentiment analysis, messaging activity over a time period, and content type. | 3. The method of claim 2 , wherein the dashboard displays at least one of sentiment analysis, messaging activity over a time period, and content type. 5. The method of claim 3 , in which a filter criteria is created for the search, where the filter criteria corresponds to the portion of the analysis results that is selected for theme analysis. | 0.968308 |
1. A computer-implemented method, the method comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client. | 1. A computer-implemented method, the method comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client. 8. The method of claim 1 wherein the one or more interactive fields are user-editable fields presented in the graphical user interface. | 0.774834 |
5. The method as claimed in claim 1, further including the step of challenging the matching step of another participant by disputing that the part of speech for which the word can be used in a sentence is correct. | 5. The method as claimed in claim 1, further including the step of challenging the matching step of another participant by disputing that the part of speech for which the word can be used in a sentence is correct. 6. The method as claimed in claim 5 further including the step of using a dictionary to determine whether the part of speech for which the word can be used in a sentence is correct. | 0.845667 |
1. A computer-implemented method of criteria-based message publication control and feedback in a publish/subscribe messaging environment, comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic and classification criteria, the classification criteria specifying requirements for determining whether publication of the message is successful; consulting, by the message broker, a subscription registry to locate registered subscriptions of a plurality of message subscribers that have registered with the message broker to receive published messages having the topic, each of the registered subscriptions further specifying subscriber classification information pertaining to the topic; selecting, by the message broker from the located subscriptions, each of at least one of the located subscriptions for which the registered subscriber classification information matches the classification criteria associated with the message, wherein the registered subscriber classification information for at least one of the located subscriptions does not match the classification criteria associated with the message; identifying, for each of the at least one selected subscription, the subscriber that registered the selected subscription; sending the message, by the message broker, to the each identified subscriber; comparing, by the message broker, the subscriber classification information in the at least one selected subscription to the classification criteria associated with the message to determine whether the requirements specified in the classification criteria are met by the at least one selected subscription; and responsive to determining, by the comparing, that the requirements are not met, performing controlled failure handling, the controlled failure handling comprising: responsive to determining that a mode of failure handling applicable for the message indicates a warning mode, sending the message, by the message broker, to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting and warning the message publisher that publication of the message was not successful; and responsive to determining that the mode of failure handling indicates a failure mode, notifying the message publisher that publication of the message failed while omitting the sending of the message to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting. | 1. A computer-implemented method of criteria-based message publication control and feedback in a publish/subscribe messaging environment, comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic and classification criteria, the classification criteria specifying requirements for determining whether publication of the message is successful; consulting, by the message broker, a subscription registry to locate registered subscriptions of a plurality of message subscribers that have registered with the message broker to receive published messages having the topic, each of the registered subscriptions further specifying subscriber classification information pertaining to the topic; selecting, by the message broker from the located subscriptions, each of at least one of the located subscriptions for which the registered subscriber classification information matches the classification criteria associated with the message, wherein the registered subscriber classification information for at least one of the located subscriptions does not match the classification criteria associated with the message; identifying, for each of the at least one selected subscription, the subscriber that registered the selected subscription; sending the message, by the message broker, to the each identified subscriber; comparing, by the message broker, the subscriber classification information in the at least one selected subscription to the classification criteria associated with the message to determine whether the requirements specified in the classification criteria are met by the at least one selected subscription; and responsive to determining, by the comparing, that the requirements are not met, performing controlled failure handling, the controlled failure handling comprising: responsive to determining that a mode of failure handling applicable for the message indicates a warning mode, sending the message, by the message broker, to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting and warning the message publisher that publication of the message was not successful; and responsive to determining that the mode of failure handling indicates a failure mode, notifying the message publisher that publication of the message failed while omitting the sending of the message to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting. 5. The method according to claim 1 , wherein the classification criteria associated with the message is specified as one or more parameters, which together specify the requirements for the successful publication of the message. | 0.641204 |
18. The computer storage media of claim 15 , wherein the source binary is configured to be executed by a source processing architecture, and wherein the first translated binary and the second translated binary are configured to be executed by a target processing architecture. | 18. The computer storage media of claim 15 , wherein the source binary is configured to be executed by a source processing architecture, and wherein the first translated binary and the second translated binary are configured to be executed by a target processing architecture. 20. The computer storage media of claim 18 , wherein the target processing architecture executes the instruction without runtime interpretation of the source binary. | 0.945308 |
1. A data learning apparatus comprising: first learning means for deriving a temporary self-organizing map in which classes are associated with respective vector points of reference feature vectors by learning first learning data including a plurality of first sample feature vectors for each of which a corresponding class is known; and second learning means for modifying the temporary self-organizing map and deriving a final self-organizing map by learning second learning data including a plurality of second sample feature vectors for each of which a corresponding class is known; wherein the second learning means includes: second vector specifying means for reading one of the second sample feature vectors out of the second learning data and specifying a second learning winner vector on the temporary self-organizing map which has the highest similarity to said one of the second sample feature vectors; modification means for comparing a class associated with a vector point of the second learning winner vector to a corresponding class of said one of the second sample feature vectors indicated by the second learning data and, when the class associated with the vector point of the second learning winner vector is not identical to the corresponding class indicated by the second learning data, modifying the second learning winner vector and a plurality of reference feature vectors distributed in a second learning vicinity of the second learning winner vector on the temporary self-organizing map so as to reduce the similarity thereof to said one of the second sample feature vectors; and means for deriving the final self-organizing map by operating each of the second vector specifying means and the modification means once or repeatedly more than once for each of said plurality of second sample feature vectors. | 1. A data learning apparatus comprising: first learning means for deriving a temporary self-organizing map in which classes are associated with respective vector points of reference feature vectors by learning first learning data including a plurality of first sample feature vectors for each of which a corresponding class is known; and second learning means for modifying the temporary self-organizing map and deriving a final self-organizing map by learning second learning data including a plurality of second sample feature vectors for each of which a corresponding class is known; wherein the second learning means includes: second vector specifying means for reading one of the second sample feature vectors out of the second learning data and specifying a second learning winner vector on the temporary self-organizing map which has the highest similarity to said one of the second sample feature vectors; modification means for comparing a class associated with a vector point of the second learning winner vector to a corresponding class of said one of the second sample feature vectors indicated by the second learning data and, when the class associated with the vector point of the second learning winner vector is not identical to the corresponding class indicated by the second learning data, modifying the second learning winner vector and a plurality of reference feature vectors distributed in a second learning vicinity of the second learning winner vector on the temporary self-organizing map so as to reduce the similarity thereof to said one of the second sample feature vectors; and means for deriving the final self-organizing map by operating each of the second vector specifying means and the modification means once or repeatedly more than once for each of said plurality of second sample feature vectors. 4. The data learning apparatus according to claim 1 , wherein each of said plurality of first sample feature vectors and said plurality of second sample feature vectors is a vector having feature quantities indicating features of an image as components thereof, and each of the corresponding classes indicated by the first learning data and the second learning data is a class indicating a meaning of an image. | 0.717042 |
1. A method for assisting a user to develop a query in a natural language, comprising: storing logs comprising information derived from prior user search sessions in which user queries were input to a search engine for retrieving responsive instances from a knowledge base; storing a collection of query suggestions, each of the query suggestions formulated to retrieve at least one responsive instance in the knowledge base, each query suggestion being constructed from an index of the knowledge base and comprising a linguistically coherent expression which includes one or a group of syntactically related words, the query suggestion having a surface form which is presented to a user and an underlying form, and wherein at least one instance of each query suggestion is present in the knowledge base; ranking the query suggestions in the collection, based at least in part on the stored logs and the frequency of instances of the query suggestion in the knowledge base; receiving a user's query in a natural language; and while the user's query is being entered, with a computer processor, generating a subset of the ranked collection of query suggestions and presenting at least one of the subset to the user as a candidate for a user query, the subset being based on that portion of the user's query already entered, the presentation of query suggestions in the subset of query suggestions being based on their respective rankings in the collection, whereby at least some of the presented query suggestions are alternate queries rather than extensions of the user's query. | 1. A method for assisting a user to develop a query in a natural language, comprising: storing logs comprising information derived from prior user search sessions in which user queries were input to a search engine for retrieving responsive instances from a knowledge base; storing a collection of query suggestions, each of the query suggestions formulated to retrieve at least one responsive instance in the knowledge base, each query suggestion being constructed from an index of the knowledge base and comprising a linguistically coherent expression which includes one or a group of syntactically related words, the query suggestion having a surface form which is presented to a user and an underlying form, and wherein at least one instance of each query suggestion is present in the knowledge base; ranking the query suggestions in the collection, based at least in part on the stored logs and the frequency of instances of the query suggestion in the knowledge base; receiving a user's query in a natural language; and while the user's query is being entered, with a computer processor, generating a subset of the ranked collection of query suggestions and presenting at least one of the subset to the user as a candidate for a user query, the subset being based on that portion of the user's query already entered, the presentation of query suggestions in the subset of query suggestions being based on their respective rankings in the collection, whereby at least some of the presented query suggestions are alternate queries rather than extensions of the user's query. 18. A computer program product comprising a tangible computer-readable recording medium encoding instructions, which when executed on a computer causes the computer to perform the method of claim 1 . | 0.530928 |
9. A non-transitory computer readable storage medium, comprising instructions stored thereon, wherein, when being executed, the instructions cause the processor to implement a caption searching method comprising: obtaining characteristic information of a video file to be played, and searching for a caption, for the video file to be played, in a caption database according to the characteristic information, so as to generate a search result; performing, according to the search result, a voice textualization process on the video file to be played by extracting audio information of the video file to be played, and converting the audio information into a textualized caption; and updating the caption database according to the textualized caption generated by the voice textualization process, and using an updated caption in the caption database as a caption of the video file to be played; wherein: the caption database comprises a standard caption database and a voice textualization database; the step of performing, according to the search result, the voice textualization process on the video file to be played comprises: performing the voice textualization process on the video file to be played if the caption of the video file to be played is not found in the caption database; and the step of updating the caption database according to the textualized caption generated, by the voice textualization process, and using the updated caption in the caption database as the caption of the video file to be played comprises: updating the voice textualization database according to the textualized caption generated by the voice textualization process, comparing the textualized caption generated by the voice textualization process with captions in the standard caption database, and if a caption is the same as the textualized caption generated by the voice textualization process and exists in the standard caption database, updating the standard caption database, and using an updated caption in the standard caption database as the caption of the video file to be played; or if no caption is the same as the textualized caption generated by the voice textualization process exists in the standard caption database, using the updated caption in the voice textualization database as the caption of the video file to be played. | 9. A non-transitory computer readable storage medium, comprising instructions stored thereon, wherein, when being executed, the instructions cause the processor to implement a caption searching method comprising: obtaining characteristic information of a video file to be played, and searching for a caption, for the video file to be played, in a caption database according to the characteristic information, so as to generate a search result; performing, according to the search result, a voice textualization process on the video file to be played by extracting audio information of the video file to be played, and converting the audio information into a textualized caption; and updating the caption database according to the textualized caption generated by the voice textualization process, and using an updated caption in the caption database as a caption of the video file to be played; wherein: the caption database comprises a standard caption database and a voice textualization database; the step of performing, according to the search result, the voice textualization process on the video file to be played comprises: performing the voice textualization process on the video file to be played if the caption of the video file to be played is not found in the caption database; and the step of updating the caption database according to the textualized caption generated, by the voice textualization process, and using the updated caption in the caption database as the caption of the video file to be played comprises: updating the voice textualization database according to the textualized caption generated by the voice textualization process, comparing the textualized caption generated by the voice textualization process with captions in the standard caption database, and if a caption is the same as the textualized caption generated by the voice textualization process and exists in the standard caption database, updating the standard caption database, and using an updated caption in the standard caption database as the caption of the video file to be played; or if no caption is the same as the textualized caption generated by the voice textualization process exists in the standard caption database, using the updated caption in the voice textualization database as the caption of the video file to be played. 10. The storage medium according to claim 9 , wherein: the step of obtaining the characteristic information of the video file to be played, and searching for the caption to generate a search result comprises: obtaining the characteristic information of the video file to be played, and searching for the caption for the video file to be played in the standard caption database according to the characteristic information; and searching for the caption, for the video file to be played in the voice textualization database if the caption of the video file to be played is not found in the standard caption database, so as to generate the search result. | 0.5 |
1. A method of displaying search results and usage metrics for a search of one or more documents that a user has opened and had in focus, the method comprising: monitoring documents that the user has opened and had in focus, wherein a document being opened by the user and in focus of the user includes a document relative to which an operation has been performed by the user within a predetermined time interval; storing, on a workstation of a user, an index that includes entries for only monitored documents that the user has opened and had in focus, wherein an index entry is created or modified for each of the monitored documents only in response to the user having opened and had in focus that monitored document, wherein only the user has performed an operation relative to that monitored document within the predetermined time interval; receiving, from the user, a request to search said index; presenting a user interface, said user interface displaying search results including a listing of documents from the monitored documents and one or more graphical visualizations characterizing the search results in the listing of documents, wherein documents in the listing includes documents relative to each of which an operation has been performed by the user within the predetermined time interval; receiving, from the user, an input instruction to display usage metrics for a selected one of said documents in the listing of documents; and updating said user interface to display said usage metrics, wherein said usage metrics include a total amount of time the user had a selected document opened and in focus, wherein the total amount of time the user has spent on the selected document when the selected document is open and in focus includes one or more instances when the user has performed an operation relative to the selected document within the predetermined time interval. | 1. A method of displaying search results and usage metrics for a search of one or more documents that a user has opened and had in focus, the method comprising: monitoring documents that the user has opened and had in focus, wherein a document being opened by the user and in focus of the user includes a document relative to which an operation has been performed by the user within a predetermined time interval; storing, on a workstation of a user, an index that includes entries for only monitored documents that the user has opened and had in focus, wherein an index entry is created or modified for each of the monitored documents only in response to the user having opened and had in focus that monitored document, wherein only the user has performed an operation relative to that monitored document within the predetermined time interval; receiving, from the user, a request to search said index; presenting a user interface, said user interface displaying search results including a listing of documents from the monitored documents and one or more graphical visualizations characterizing the search results in the listing of documents, wherein documents in the listing includes documents relative to each of which an operation has been performed by the user within the predetermined time interval; receiving, from the user, an input instruction to display usage metrics for a selected one of said documents in the listing of documents; and updating said user interface to display said usage metrics, wherein said usage metrics include a total amount of time the user had a selected document opened and in focus, wherein the total amount of time the user has spent on the selected document when the selected document is open and in focus includes one or more instances when the user has performed an operation relative to the selected document within the predetermined time interval. 11. The method of claim 1 , further comprising: specifying one or more documents that should not be monitored, or specifying one or more documents for which an index entry should not be created. | 0.547335 |
1. A computer implemented method in a data processing system for determining and communicating biometrics of a recorded speaker in a voice transcription process, the computer implemented method comprising: receiving, by the data processing system, a request from a user for a transcription of a voice file stored in a memory of the data processing system; obtaining, by the data processing system, a profile associated with the requesting user, wherein the profile comprises biometric parameters and preferences defined by the user; analyzing, by the data processing system, the requested voice file for biometric elements according to the parameters specified in the user's profile; responsive to the data processing system detecting, in the voice file, biometric elements conforming to the parameters specified in the user's profile, modifying, by the data processing system, a transcription output of the voice file according to the preferences specified in the user's profile for the detected biometric elements to form a modified transcription output file; responsive to the data processing system determining that no preferences are specified in the user's profile, modifying, by the data processing system, the transcription output of the voice file according to default settings for the detected biometric elements to form the modified transcription output file; and providing, by the data processing system, the modified transcription output file to the requesting user. | 1. A computer implemented method in a data processing system for determining and communicating biometrics of a recorded speaker in a voice transcription process, the computer implemented method comprising: receiving, by the data processing system, a request from a user for a transcription of a voice file stored in a memory of the data processing system; obtaining, by the data processing system, a profile associated with the requesting user, wherein the profile comprises biometric parameters and preferences defined by the user; analyzing, by the data processing system, the requested voice file for biometric elements according to the parameters specified in the user's profile; responsive to the data processing system detecting, in the voice file, biometric elements conforming to the parameters specified in the user's profile, modifying, by the data processing system, a transcription output of the voice file according to the preferences specified in the user's profile for the detected biometric elements to form a modified transcription output file; responsive to the data processing system determining that no preferences are specified in the user's profile, modifying, by the data processing system, the transcription output of the voice file according to default settings for the detected biometric elements to form the modified transcription output file; and providing, by the data processing system, the modified transcription output file to the requesting user. 6. The computer implemented method of claim 1 , wherein modifying a transcription output of the voice file according to the preferences specified in the user's profile for the detected biometric elements to form a modified transcription output file includes at least one of shading, bolding, highlighting, rephrasing, or changing font or color of text. | 0.590764 |
1. A method for providing advertising in one or more search results, the method comprising: receiving at least one database on a computer system from at least one service provider via a network, the at least one database being one of a plurality of databases, each database in the plurality of databases comprising a plurality of items for recognition, each database in the plurality of databases being for a corresponding vertical application; processing the at least one database on the computer system based on the plurality of items for recognition; receiving on the computer system over the network a sound data input comprising a query for the processed at least one database; generating by the computer system phonetic data from the received query, the phonetic data comprising a sequence of phonemes, each phoneme representing a perceptually distinct unit of sound; determining one or more search results in the processed at least one database using the computer system based on the phonetic data; identifying one or more advertisement results in an advertisement database based on the phonetic data and the determined one or more search results using the computer system, the advertisement database being communicatively coupled to the computer system; and transmitting the one or more search results and the one or more advertisement results from the computer system to a remote computer system. | 1. A method for providing advertising in one or more search results, the method comprising: receiving at least one database on a computer system from at least one service provider via a network, the at least one database being one of a plurality of databases, each database in the plurality of databases comprising a plurality of items for recognition, each database in the plurality of databases being for a corresponding vertical application; processing the at least one database on the computer system based on the plurality of items for recognition; receiving on the computer system over the network a sound data input comprising a query for the processed at least one database; generating by the computer system phonetic data from the received query, the phonetic data comprising a sequence of phonemes, each phoneme representing a perceptually distinct unit of sound; determining one or more search results in the processed at least one database using the computer system based on the phonetic data; identifying one or more advertisement results in an advertisement database based on the phonetic data and the determined one or more search results using the computer system, the advertisement database being communicatively coupled to the computer system; and transmitting the one or more search results and the one or more advertisement results from the computer system to a remote computer system. 13. The method of claim 1 , wherein the query includes a command and the method further comprises performing a search action of the at least one database by the computer system based on the command. | 0.528405 |
10. A computer-implemented method of translating data, comprising: receiving one or more input data from one or more sensing sources, wherein the one or more sensing sources comprise at least one of audio, video, global positioning, or image sensing sources; generating context data of at least one of the one or more input data, the generating context data including: extracting text from at least one of the one or more input data to generate query terms and employing the query terms with a search engine to determine a first linguistic language; translating one or more results from the search engine into a translated output in a second linguistic language; presenting the translated output to a recipient in the second linguistic language that is understandable by the recipient; receiving a user feedback in the second linguistic language from the recipient, wherein the user feedback includes an indication that the translation is successful or unsuccessful; establishing the context of the at least one of the one or more input data based on the user feedback; and employing the established context as an additional input for translating the content. | 10. A computer-implemented method of translating data, comprising: receiving one or more input data from one or more sensing sources, wherein the one or more sensing sources comprise at least one of audio, video, global positioning, or image sensing sources; generating context data of at least one of the one or more input data, the generating context data including: extracting text from at least one of the one or more input data to generate query terms and employing the query terms with a search engine to determine a first linguistic language; translating one or more results from the search engine into a translated output in a second linguistic language; presenting the translated output to a recipient in the second linguistic language that is understandable by the recipient; receiving a user feedback in the second linguistic language from the recipient, wherein the user feedback includes an indication that the translation is successful or unsuccessful; establishing the context of the at least one of the one or more input data based on the user feedback; and employing the established context as an additional input for translating the content. 13. The method of claim 10 , further comprising an act of employing global positioning system (GPS) data included in the one or more input data to determine the first linguistic language. | 0.647207 |
32. A system comprising: a networked device and a client device to apply an automatic content recognition algorithm to determine a content identifier of an audio-visual data and to associate the content identifier with an advertisement data based on a semantic correlation between a meta-data of the advertisement provided by a content provider and the content identifier, the networked device executing a sandbox reachable service thereon and the client device executing a sandboxed application thereon; a capture infrastructure to annotate the audio-visual data with at least one of a brand name and a product name by comparing entries in a master database with at least one of a closed captioning data of the audio-visual data and through an application of an optical character recognition algorithm in the audio-visual data; and an advertising exchange server to generate an advertisement based on the content identifier of the audio-visual data and a public internet protocol address associated with an application requesting the advertisement data, wherein a communication session between the networked device and the client device is established by appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, wherein the header is either one of an origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the sandbox reachable service optionally verifies that the sandboxed application is in the common private network, wherein the sandbox reachable service communicates a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, wherein the sandboxed application communicates the MAC address and the unique identifier to a pairing server, and wherein the client device automatically regenerates a script embedded in at least one of the client device, a supply-side platform, and a data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and sandboxed application based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. | 32. A system comprising: a networked device and a client device to apply an automatic content recognition algorithm to determine a content identifier of an audio-visual data and to associate the content identifier with an advertisement data based on a semantic correlation between a meta-data of the advertisement provided by a content provider and the content identifier, the networked device executing a sandbox reachable service thereon and the client device executing a sandboxed application thereon; a capture infrastructure to annotate the audio-visual data with at least one of a brand name and a product name by comparing entries in a master database with at least one of a closed captioning data of the audio-visual data and through an application of an optical character recognition algorithm in the audio-visual data; and an advertising exchange server to generate an advertisement based on the content identifier of the audio-visual data and a public internet protocol address associated with an application requesting the advertisement data, wherein a communication session between the networked device and the client device is established by appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, wherein the header is either one of an origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the sandbox reachable service optionally verifies that the sandboxed application is in the common private network, wherein the sandbox reachable service communicates a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, wherein the sandboxed application communicates the MAC address and the unique identifier to a pairing server, and wherein the client device automatically regenerates a script embedded in at least one of the client device, a supply-side platform, and a data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and sandboxed application based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. 36. The system of claim 32 , wherein the client device: eliminates a communication through a centralized infrastructure when the sandboxed application and the sandbox reachable service communicate in a shared network common to the client device and the networked device when the communication session is established, wherein the shared network is at least one of a local area network, a multicast network, an anycast network, and a multilan network, minimizes a latency in the communication session when the sandboxed application and the sandbox reachable service communicate in the shared network common to the client device and the networked device when the communication session is established, and improves privacy in the communication session when the sandboxed application and the sandbox reachable service communicate in the shared network common to the client device and the networked device when the communication session is established. | 0.802404 |
1. A computer-implemented method comprising: defining, for an online conference session, a plurality of pages based on information received from a moderating participant having administrative privileges for the conference session, each page corresponding to a discussion topic of a text-based communication; selecting, by a request received from the moderating participant, one of the plurality of pages; synchronizing the selected page, such that the selected page is displayed to the moderating participant and each of one or more other participants in the online conference session; after selecting one of the plurality of pages, chronologically displaying, in the display of the selected page, an entirety of the text-based communication that is generated while the selected page remains selected until another page of the plurality of pages is selected; and receiving, from the moderating participant, commands to manage the online conference session, the commands including a command to add a new page corresponding to a new discussion topic, a command to delete at least one page of the plurality of pages, a command to modify the selected page, a command to search for a specific page of the plurality of pages, and a command to close the selected page. | 1. A computer-implemented method comprising: defining, for an online conference session, a plurality of pages based on information received from a moderating participant having administrative privileges for the conference session, each page corresponding to a discussion topic of a text-based communication; selecting, by a request received from the moderating participant, one of the plurality of pages; synchronizing the selected page, such that the selected page is displayed to the moderating participant and each of one or more other participants in the online conference session; after selecting one of the plurality of pages, chronologically displaying, in the display of the selected page, an entirety of the text-based communication that is generated while the selected page remains selected until another page of the plurality of pages is selected; and receiving, from the moderating participant, commands to manage the online conference session, the commands including a command to add a new page corresponding to a new discussion topic, a command to delete at least one page of the plurality of pages, a command to modify the selected page, a command to search for a specific page of the plurality of pages, and a command to close the selected page. 7. The computer-implemented method of claim 1 , wherein defining further comprises defining the plurality of pages prior to a beginning of the online conference session. | 0.615777 |
1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. 6. The computer implemented method of claim 1 wherein the first inference is further related to identifying at least one interaction of the drug with at least one additional drug. | 0.573441 |
1. A method, comprising: converting a plurality of feature vectors that represents a speech utterance into a plurality of log probability sets, the converting using a classifier ensemble including a plurality of classifiers; transforming the plurality of log probability sets into a plurality of output symbol sequences; combining the plurality of output symbol sequences, using an iterative a priori probability calculation algorithm, into a fusion output symbol sequence; and retrieving one or more speech utterances from a speech database using the plurality of output symbol sequences. | 1. A method, comprising: converting a plurality of feature vectors that represents a speech utterance into a plurality of log probability sets, the converting using a classifier ensemble including a plurality of classifiers; transforming the plurality of log probability sets into a plurality of output symbol sequences; combining the plurality of output symbol sequences, using an iterative a priori probability calculation algorithm, into a fusion output symbol sequence; and retrieving one or more speech utterances from a speech database using the plurality of output symbol sequences. 9. The method of claim 1 , further comprising: converting an input audio signal into the plurality of feature vectors and compensating for noise in the input audio signal using frequency bins in each of a plurality of frames that are included in the input audio signal. | 0.905263 |
10. A method comprising: receiving, by a computing device and from an entitlement control message (ECM) generator, a first set of ECMs as a batch; caching concurrently, by the computing device, a first set of control words and the first set of ECMs, the first set of ECMs being associated with the first set of control words for use with a first service; encrypting a transport stream, for the first service, using a first control word of the first set of control words during a first cryptographic period, using a second control word of the first set of control words different from the first control word during a second cryptographic period, and using the first control word during a third cryptographic period, wherein the second cryptographic period occurs after the first cryptographic period, and the third cryptographic period occurs after the second cryptographic period; inserting into the transport stream a first ECM, of the first set of ECMs, corresponding to the first control word; and sending, to a device downstream from the computing device, the transport stream. | 10. A method comprising: receiving, by a computing device and from an entitlement control message (ECM) generator, a first set of ECMs as a batch; caching concurrently, by the computing device, a first set of control words and the first set of ECMs, the first set of ECMs being associated with the first set of control words for use with a first service; encrypting a transport stream, for the first service, using a first control word of the first set of control words during a first cryptographic period, using a second control word of the first set of control words different from the first control word during a second cryptographic period, and using the first control word during a third cryptographic period, wherein the second cryptographic period occurs after the first cryptographic period, and the third cryptographic period occurs after the second cryptographic period; inserting into the transport stream a first ECM, of the first set of ECMs, corresponding to the first control word; and sending, to a device downstream from the computing device, the transport stream. 15. The method of claim 10 , further comprising: setting the second cryptographic period to a time period less than a latency time in requesting and receiving a new control word and associated new ECM from the ECM generator. | 0.678061 |
7. The method of claim 1 , wherein the inference model is a substitute inference model based on an initial inference model, the method further comprising: receiving test sensor data and associated training labels, the test sensor data associated with a set of mobile devices including the mobile device; and utilizing machine learning to determine the initial inference model based on the test sensor data and the associated training labels. | 7. The method of claim 1 , wherein the inference model is a substitute inference model based on an initial inference model, the method further comprising: receiving test sensor data and associated training labels, the test sensor data associated with a set of mobile devices including the mobile device; and utilizing machine learning to determine the initial inference model based on the test sensor data and the associated training labels. 8. The method of claim 7 , wherein the inferences are based on the associated training labels. | 0.908894 |
16. Logic encoded in non-transitory media for execution and when executed by a processor operable to: identify a root term from at least one of search results, one or more incident lists, or user-provided input; determine one or more other terms belonging to a group associated with the root term; select one or more of the terms from the group; convert the selected terms to regular expressions that are mapped to attributes according to an attribute map, wherein the attributes are associated with a concept; index a document using tags stored in a tag database, wherein if a predetermined number of the regular expressions occur in the document, the tags are associated with corresponding attributes by setting a field or position in an index in the tags where each corresponding attribute has a separate field in the tag indicating whether the attribute is present in the document, and wherein the tags include a pointer to a storage location where the document is stored; apply a concept based on the selected terms to a rule provided as part of a security policy that controls whether the document is permitted to be sent to a next destination as part of network traffic, wherein the rule is applied to the tags to determine if any of the selected terms occur in the document; and quarantine at least some of the network traffic based on the rule. | 16. Logic encoded in non-transitory media for execution and when executed by a processor operable to: identify a root term from at least one of search results, one or more incident lists, or user-provided input; determine one or more other terms belonging to a group associated with the root term; select one or more of the terms from the group; convert the selected terms to regular expressions that are mapped to attributes according to an attribute map, wherein the attributes are associated with a concept; index a document using tags stored in a tag database, wherein if a predetermined number of the regular expressions occur in the document, the tags are associated with corresponding attributes by setting a field or position in an index in the tags where each corresponding attribute has a separate field in the tag indicating whether the attribute is present in the document, and wherein the tags include a pointer to a storage location where the document is stored; apply a concept based on the selected terms to a rule provided as part of a security policy that controls whether the document is permitted to be sent to a next destination as part of network traffic, wherein the rule is applied to the tags to determine if any of the selected terms occur in the document; and quarantine at least some of the network traffic based on the rule. 21. The logic of claim 16 , wherein the concept is used to automatically mark one or more documents that relate to the concept. | 0.565 |
9. An interlayer video encoding method comprising: determining whether a second layer current block performs brightness compensation; determining whether a candidate of the second layer current block is usable as a merge candidate based on whether the second layer current block performs the brightness compensation and whether the candidate of the second layer current block performs time direction inter prediction; generating a merge candidate list including at least one merge candidate based on a result of the determining; and determining motion information of the second layer current block by using motion information of one of the at least one merge candidate. | 9. An interlayer video encoding method comprising: determining whether a second layer current block performs brightness compensation; determining whether a candidate of the second layer current block is usable as a merge candidate based on whether the second layer current block performs the brightness compensation and whether the candidate of the second layer current block performs time direction inter prediction; generating a merge candidate list including at least one merge candidate based on a result of the determining; and determining motion information of the second layer current block by using motion information of one of the at least one merge candidate. 11. The interlayer video encoding method of claim 9 , wherein the candidate is based on motion information of a corresponding block indicated by a disparity vector of the second layer current block from a location of the second layer current block. | 0.770718 |
13. The system of claim 12 , the behavior of the user is determined using the user's web page interaction data and the trained model is trained using other users' web page interaction data, the instructions further comprising instructions to: generate an incremental user scoring vector using the current item and an item cluster membership vector for the item in the trained model, the item cluster membership vector identifying the item's cluster score for each cluster identified in the trained model, the item's cluster score comprising a probability that the item belongs to the cluster; and generate the short-term cluster membership vector using the incremental user scoring vector. | 13. The system of claim 12 , the behavior of the user is determined using the user's web page interaction data and the trained model is trained using other users' web page interaction data, the instructions further comprising instructions to: generate an incremental user scoring vector using the current item and an item cluster membership vector for the item in the trained model, the item cluster membership vector identifying the item's cluster score for each cluster identified in the trained model, the item's cluster score comprising a probability that the item belongs to the cluster; and generate the short-term cluster membership vector using the incremental user scoring vector. 14. The system of claim 13 , the instructions further comprising instructions to: apply a decay factor to the incremental user scoring vector before generating the short-term cluster membership vector using the incremental user scoring vector. | 0.770619 |
1. A method for responding to a remote party in communication with an agent in a call center, comprising: recording a response script in a voice of the agent; processing a call by a call handler, the call involving a first call leg to the remote party, a second call leg to the agent, and a third call leg to a speech analytics component; processing speech from the remote party by the speech analytics component to detect a presence of a first keyword spoken by the remote party; providing an event notification from the speech analytics component to the call handler signifying detection of the first keyword in the speech from the remote party; and in response to receiving the event notification from the speech analytics component, presenting information on a computer screen for the agent to command the response script to be played to the remote party. | 1. A method for responding to a remote party in communication with an agent in a call center, comprising: recording a response script in a voice of the agent; processing a call by a call handler, the call involving a first call leg to the remote party, a second call leg to the agent, and a third call leg to a speech analytics component; processing speech from the remote party by the speech analytics component to detect a presence of a first keyword spoken by the remote party; providing an event notification from the speech analytics component to the call handler signifying detection of the first keyword in the speech from the remote party; and in response to receiving the event notification from the speech analytics component, presenting information on a computer screen for the agent to command the response script to be played to the remote party. 3. The method of claim 1 , further comprising: receiving a command from the agent to play the response script to the remote party; and playing the response script to the remote party in response to receiving the command. | 0.543415 |
1. A computer-implemented method for classifying an object, comprising: (a) constructing, by a processor, at least one quotient appearance manifold mapping based on a sample image to untangle appearance fiber bundles of different objects, wherein the at least one quotient appearance manifold mapping associates points of an appearance manifold to a quotient manifold; (b) reducing, by the processor, dimensionality of the quotient appearance manifold mapping to generate at least one feature characteristic of the sample image; and (c) training, by the processor, based on said feature, at least one classifier adapted for associating the object with an object class. | 1. A computer-implemented method for classifying an object, comprising: (a) constructing, by a processor, at least one quotient appearance manifold mapping based on a sample image to untangle appearance fiber bundles of different objects, wherein the at least one quotient appearance manifold mapping associates points of an appearance manifold to a quotient manifold; (b) reducing, by the processor, dimensionality of the quotient appearance manifold mapping to generate at least one feature characteristic of the sample image; and (c) training, by the processor, based on said feature, at least one classifier adapted for associating the object with an object class. 16. The method of claim 1 wherein the step (c) comprises performing adaptive boosting (AdaBoost) to train the classifier. | 0.602423 |
16. The system of claim 15 , wherein analysing the first collection of words to identify the homonym candidate is based on a comparison of each one of the words of the first collection of words with entries of a dictionary database. | 16. The system of claim 15 , wherein analysing the first collection of words to identify the homonym candidate is based on a comparison of each one of the words of the first collection of words with entries of a dictionary database. 18. The system of claim 16 , wherein the homonym candidate is identified upon determining that one of the entries of the dictionary database corresponding to the one of the words of the first collection of words is associated with a plurality of meanings including the first meaning and the second meaning. | 0.925145 |
10. A non-transitory computer-readable medium, excluding transitory propagating signals, storing instructions that, when executed by a computing device, which comprises one or more processors and computer memory, cause the computing device to perform operations for content indexing of data files being archived, the operations comprising: executing an indexer that, in the course of one or more data files being archived to respective archive copies, indexes the one or more data files according to content attributes, including at least one of: textual content, picture content, video content, and audio content, wherein each archive copy is stored offline relative to a user computing device that is distinct from the computing device executing the indexer; (a) associating by the indexer content attributes with respective smaller portions of each archive copy, (b) for the one or more data files being archived, generating by the indexer a searchable content index of associated content attributes relative to the smaller portions of each archive copy, and (c) associating by the indexer the content index with the respective archive copies; and executing a search filter that is configured to: (i) search in the content index for one or more search criteria received from the user computing device, (ii) cause only smaller portions of respective archive copies that satisfy the one or more search criteria, to be mounted to the user computing device, wherein archive copies and smaller portions thereof that do not satisfy the one or more search criteria are not mounted and remain offline relative to the user computing device, and (iii) present in response to the search criteria a fast-forward progression through the mounted smaller portions of respective archive copies that satisfy the one or more search criteria, without restoring the respective archive copies in their entireties to the user computing device. | 10. A non-transitory computer-readable medium, excluding transitory propagating signals, storing instructions that, when executed by a computing device, which comprises one or more processors and computer memory, cause the computing device to perform operations for content indexing of data files being archived, the operations comprising: executing an indexer that, in the course of one or more data files being archived to respective archive copies, indexes the one or more data files according to content attributes, including at least one of: textual content, picture content, video content, and audio content, wherein each archive copy is stored offline relative to a user computing device that is distinct from the computing device executing the indexer; (a) associating by the indexer content attributes with respective smaller portions of each archive copy, (b) for the one or more data files being archived, generating by the indexer a searchable content index of associated content attributes relative to the smaller portions of each archive copy, and (c) associating by the indexer the content index with the respective archive copies; and executing a search filter that is configured to: (i) search in the content index for one or more search criteria received from the user computing device, (ii) cause only smaller portions of respective archive copies that satisfy the one or more search criteria, to be mounted to the user computing device, wherein archive copies and smaller portions thereof that do not satisfy the one or more search criteria are not mounted and remain offline relative to the user computing device, and (iii) present in response to the search criteria a fast-forward progression through the mounted smaller portions of respective archive copies that satisfy the one or more search criteria, without restoring the respective archive copies in their entireties to the user computing device. 17. The non-transitory computer-readable medium of claim 10 wherein the content index is stored to a user computing device that is associated with the data files being archived. | 0.738155 |
41. The method of claim 40 , wherein each of the statistical information are determined by parsing the programming code using a regular expression pattern matching system which matches patterns specific to the programming language found in the programming code; and the index generation includes parsing the programming code using a regular expression system to find matches of each word using a pattern matching expression that is specific to the syntax of the particular programming language used in the programming code, and where a maintaining a table of words and their frequency in the programming code is generated and maintained by adding each new word found to the table with a frequency count of 1 and incrementing the frequency count in the table for each additional time the word is found in contents of the programming code. | 41. The method of claim 40 , wherein each of the statistical information are determined by parsing the programming code using a regular expression pattern matching system which matches patterns specific to the programming language found in the programming code; and the index generation includes parsing the programming code using a regular expression system to find matches of each word using a pattern matching expression that is specific to the syntax of the particular programming language used in the programming code, and where a maintaining a table of words and their frequency in the programming code is generated and maintained by adding each new word found to the table with a frequency count of 1 and incrementing the frequency count in the table for each additional time the word is found in contents of the programming code. 42. The method of claim 41 , wherein the patterns are determined for each programming language by the syntax specification for the programming language using a full-text based custom indexing process for each type of programming code. | 0.767874 |
1. A method of resolving uncoordinated person objects and person-related objects in a database, the method including: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object, and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. | 1. A method of resolving uncoordinated person objects and person-related objects in a database, the method including: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object, and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. 3. The method of claim 1 , wherein the lead active person object is identified as an oldest person object in the first person-related set. | 0.820413 |
8. A non-transitory data storage device having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to: present, via a graphical user interface, a plurality of fields including at least an input field to receive user-generated input, wherein the protocol to present the plurality of fields supports only a single format for the input field; receive the user-generated input with a computing platform providing the graphical user interface via the input field; parse the user-generated input based on formatting criteria, wherein the formatting criteria comprises N text formatting types to be applied to the user-generated input, wherein N is at least two; provide an underlay field for each of N−1 text formatting types; apply one of the text formatting types to each of the N−1 underlay fields and the input field; aligning the N−1 underlay fields and the input field, wherein in aligning comprises at least providing proper spacing between text characters and by superimposing a translucent field on top of a corresponding element with a text formatting type and in the one or more underlay fields only showing characters that are stylized in higher layers, replacing other characters with a space so non-space characters in the one or more underlay fields show through; display portions of the user-generated input within the corresponding fields while maintaining spacing of the user-generated input. | 8. A non-transitory data storage device having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to: present, via a graphical user interface, a plurality of fields including at least an input field to receive user-generated input, wherein the protocol to present the plurality of fields supports only a single format for the input field; receive the user-generated input with a computing platform providing the graphical user interface via the input field; parse the user-generated input based on formatting criteria, wherein the formatting criteria comprises N text formatting types to be applied to the user-generated input, wherein N is at least two; provide an underlay field for each of N−1 text formatting types; apply one of the text formatting types to each of the N−1 underlay fields and the input field; aligning the N−1 underlay fields and the input field, wherein in aligning comprises at least providing proper spacing between text characters and by superimposing a translucent field on top of a corresponding element with a text formatting type and in the one or more underlay fields only showing characters that are stylized in higher layers, replacing other characters with a space so non-space characters in the one or more underlay fields show through; display portions of the user-generated input within the corresponding fields while maintaining spacing of the user-generated input. 9. The data storage device of claim 8 wherein the protocol comprises a HyperText Markup Language (HTML)-compliant protocol. | 0.555756 |
3. The method of claim 2 , the method further comprising: characterizing a set of authors, specifying a mapping from the first and second set identifiers to the targeted unrefinement, and using an unrefinement rule that restricts the second audience to the second reference for the set of authors. | 3. The method of claim 2 , the method further comprising: characterizing a set of authors, specifying a mapping from the first and second set identifiers to the targeted unrefinement, and using an unrefinement rule that restricts the second audience to the second reference for the set of authors. 4. The method of claim 3 , the method further comprising a default unrefinement. | 0.938149 |
7. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement an algorithm utilization controller for utilizing algorithm components based on categories in a question answering system, wherein the computer readable program causes the computing device to: capture, by a question answering engine executing within the question answering system, a history of performance and correctness metrics for identifying efficiency of respective algorithms for finding answers to a plurality of training questions in respective question categories in the question answering system, wherein the algorithms comprise specialized software components that perform portions of analysis performed by the question answering engine; determine, by the algorithm utilization controller, sets of algorithms to use for respective question categories according to efficiency and correctness analysis, wherein the algorithm utilization controller comprises a logical grouping component, a learning analyzer component, a machine learning component, and an algorithm execution broker component working together to dynamically adjust algorithms to answer questions while minimizing resources, wherein determining the sets of algorithms comprises classifying each given training question into a question category by the logical grouping component, profiling resources to produce a performance profile for the question category for output value contributions to produce a final answer by the learning analyzer component, utilizing the performance profile for the question category as training data by the machine learning component considering confidence of answers as a weighting, and generating a machine learning model for classifying questions and adjusting algorithms dynamically by the algorithm execution broker according to a criteria adjusted for resource availability and answer correctness criteria; for a given input question, determine, by the algorithm utilization controller, a question category of the given input question using the machine learning model; determining, by the algorithm utilization controller, a set of algorithms corresponding to the question category of the given input question that meet an efficiency threshold to contribute to finding a correct answer for the given input question using the machine learning model; and execute, by the question answering engine, the set of algorithms corresponding to the question category of the given input question to find an answer to the given input question. | 7. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement an algorithm utilization controller for utilizing algorithm components based on categories in a question answering system, wherein the computer readable program causes the computing device to: capture, by a question answering engine executing within the question answering system, a history of performance and correctness metrics for identifying efficiency of respective algorithms for finding answers to a plurality of training questions in respective question categories in the question answering system, wherein the algorithms comprise specialized software components that perform portions of analysis performed by the question answering engine; determine, by the algorithm utilization controller, sets of algorithms to use for respective question categories according to efficiency and correctness analysis, wherein the algorithm utilization controller comprises a logical grouping component, a learning analyzer component, a machine learning component, and an algorithm execution broker component working together to dynamically adjust algorithms to answer questions while minimizing resources, wherein determining the sets of algorithms comprises classifying each given training question into a question category by the logical grouping component, profiling resources to produce a performance profile for the question category for output value contributions to produce a final answer by the learning analyzer component, utilizing the performance profile for the question category as training data by the machine learning component considering confidence of answers as a weighting, and generating a machine learning model for classifying questions and adjusting algorithms dynamically by the algorithm execution broker according to a criteria adjusted for resource availability and answer correctness criteria; for a given input question, determine, by the algorithm utilization controller, a question category of the given input question using the machine learning model; determining, by the algorithm utilization controller, a set of algorithms corresponding to the question category of the given input question that meet an efficiency threshold to contribute to finding a correct answer for the given input question using the machine learning model; and execute, by the question answering engine, the set of algorithms corresponding to the question category of the given input question to find an answer to the given input question. 12. The computer program product of claim 7 , wherein the computer readable program is stored in a computer readable storage medium in a data processing system and wherein the computer readable program was downloaded over a network from a remote data processing system. | 0.513036 |
1. An integrated customer communications computer system, comprising: at least one computer database; and a communications computer system, in communication with said at least one database and at least one component of an account opening system, and configured to provide outbound customer communications, wherein the communications computer system generates documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from said at least one component of the account opening system, and static content for the templates received from a content repository, and wherein the communications computer system includes: a communication manager, comprising: a communication controller receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; a document manager managing documents associated with the communications; and a communication history component maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; a plurality of transmission channels for transmitting the communications; an interface for managing the templates and the content; and a document repository storing, retrieving, and managing storage of the documents wherein the interface for managing the templates is configured to provide a user functionality to create, preview, edit, maintain and delete communication templates for different channels, define what data items are included in the communication, insert dynamic variables that vary by at least one of channel and communication type, define a source of the dynamic data for the communication, and make deployments to various environments for validation. | 1. An integrated customer communications computer system, comprising: at least one computer database; and a communications computer system, in communication with said at least one database and at least one component of an account opening system, and configured to provide outbound customer communications, wherein the communications computer system generates documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from said at least one component of the account opening system, and static content for the templates received from a content repository, and wherein the communications computer system includes: a communication manager, comprising: a communication controller receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; a document manager managing documents associated with the communications; and a communication history component maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; a plurality of transmission channels for transmitting the communications; an interface for managing the templates and the content; and a document repository storing, retrieving, and managing storage of the documents wherein the interface for managing the templates is configured to provide a user functionality to create, preview, edit, maintain and delete communication templates for different channels, define what data items are included in the communication, insert dynamic variables that vary by at least one of channel and communication type, define a source of the dynamic data for the communication, and make deployments to various environments for validation. 25. The integrated customer communications computer system of claim 1 , wherein said interface for managing the templates and the content is configured to be accessible to a user based on entitlements. | 0.627868 |
22. A method of keyword extraction from at least one natural language text using a graph, comprising: selecting, using a processing unit, a plurality of text units from said at least one natural language text; associating, using the processing unit, the plurality of text units with a plurality of graph nodes so that each graph node is associated with one of the plurality of text units selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of text units; associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that are associated with one of the text units selected from said at least one natural language text and said at least one graph edge; ranking, using the processing unit, the plurality of graph nodes by applying a graph-based ranking algorithm to the graph; and determine, using the processing unit, at least one keyword based on the plurality of text units and the plurality of rankings. | 22. A method of keyword extraction from at least one natural language text using a graph, comprising: selecting, using a processing unit, a plurality of text units from said at least one natural language text; associating, using the processing unit, the plurality of text units with a plurality of graph nodes so that each graph node is associated with one of the plurality of text units selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of text units; associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that are associated with one of the text units selected from said at least one natural language text and said at least one graph edge; ranking, using the processing unit, the plurality of graph nodes by applying a graph-based ranking algorithm to the graph; and determine, using the processing unit, at least one keyword based on the plurality of text units and the plurality of rankings. 27. The method of claim 22 , wherein ranking the plurality of graph nodes comprises: assigning a plurality of first scores to the plurality of graph nodes; defining a relationship between a second score of each graph node and second scores of graph nodes coupled each graph node by a graph edge; and determining a second plurality of scores associated with the plurality of graph nodes by applying an iterative recursive algorithm starting with the plurality of first scores and iterating until the relationship is satisfied. | 0.582156 |
7. A computer-implemented method comprising: using a processor to provide a web page from a first source; providing a web browser readable code component from a second source different from the first source, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page. | 7. A computer-implemented method comprising: using a processor to provide a web page from a first source; providing a web browser readable code component from a second source different from the first source, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page. 12. The method as claimed in claim 7 wherein the dynamically selectable characteristics of the web browser readable code component include at least one characteristic from the group: shape, color, text, and category. | 0.60401 |
10. A method of employing a multiple output relaxation (MOR) machine learning model to predict multiple interdependent output components of a multiple output dependency (MOD) output decision, each output component having multiple possible values, the method comprising: training a first classifier to predict a first of two interdependent output components of an MOD output decision based on an input and based on the second output component; training a second classifier to predict the second of the two output components of the MOD output decision based on the input and based on the first output component; initializing each of the possible values for each of the output components to a predetermined output value; running relaxation iterations on each of the classifiers to update the output value of each possible value for each of the output components until a relaxation state reaches an equilibrium or a maximum number of relaxation iterations is reached; and retrieving an optimal output component from each of the classifiers. | 10. A method of employing a multiple output relaxation (MOR) machine learning model to predict multiple interdependent output components of a multiple output dependency (MOD) output decision, each output component having multiple possible values, the method comprising: training a first classifier to predict a first of two interdependent output components of an MOD output decision based on an input and based on the second output component; training a second classifier to predict the second of the two output components of the MOD output decision based on the input and based on the first output component; initializing each of the possible values for each of the output components to a predetermined output value; running relaxation iterations on each of the classifiers to update the output value of each possible value for each of the output components until a relaxation state reaches an equilibrium or a maximum number of relaxation iterations is reached; and retrieving an optimal output component from each of the classifiers. 11. The method as recited in claim 10 , where the first and second classifiers each comprises a multilayer perceptron (MLP) neural network, another multilayer neural network, a decision tree, or a support vector machine. | 0.832344 |
11. A system comprising: a candidate term module, executing on a computing device, configured to obtain a corpus of candidate terms from a received seed term, each candidate term in the corpus comprising the seed term; a network traffic module, executing on the computing device, configured to obtain network traffic information comprising a count of the events that occur respectively for each candidate term in the corpus of candidate terms; and a domain name set module, executing on the computing device, configured to, for each of the corpus of candidate terms whose respective traffic information satisfies a condition, identify a set of domain names associated with the respective candidate term, determine whether an actively hosted web page resolves to each of the set of domain names, wherein the set of domain names is owned by an owner of the seed term; notify an owner of the seed term to serve content on a site associated with a particular one of the set of domain names if the particular domain name does not resolve to an actively hosted web page and adjust the set of domain names associated with the respective candidate term based on an attempt to recover a domain name in a previously compiled set of domain names. | 11. A system comprising: a candidate term module, executing on a computing device, configured to obtain a corpus of candidate terms from a received seed term, each candidate term in the corpus comprising the seed term; a network traffic module, executing on the computing device, configured to obtain network traffic information comprising a count of the events that occur respectively for each candidate term in the corpus of candidate terms; and a domain name set module, executing on the computing device, configured to, for each of the corpus of candidate terms whose respective traffic information satisfies a condition, identify a set of domain names associated with the respective candidate term, determine whether an actively hosted web page resolves to each of the set of domain names, wherein the set of domain names is owned by an owner of the seed term; notify an owner of the seed term to serve content on a site associated with a particular one of the set of domain names if the particular domain name does not resolve to an actively hosted web page and adjust the set of domain names associated with the respective candidate term based on an attempt to recover a domain name in a previously compiled set of domain names. 17. The domain name set generation system of claim 11 wherein the domain name set module is further configured to determine that each domain name is owned by a registrant. | 0.501949 |
7. A system for automatically generating content for an electronic document, the system comprising: an electronic data store that stores one or more templates for the electronic documents, wherein the one or more templates comprise: a plurality of paragraph templates for a document paragraph, each paragraph template comprising one or more sentence types, wherein the plurality of paragraph templates are ranked at least according to a desirability of using each paragraph template to generate content describing items of interest, a plurality of sentence templates, each sentence template corresponding to at least one of the one or more sentence types and comprising one or more variables, wherein the plurality of sentence templates are ranked at least according to a desirability of using each sentence template to generate content describing, items of interest; and a content generation service implemented by one or more processors in communication with the electronic data store, the content generation service operative to: obtain data regarding an item of interest to be described in the electronic document, the data comprising a set of attributes associated with the item of interest; select a paragraph template which is to be employed for content generation from the data store based at least in part on the set of attributes and on rankings of the paragraph templates, wherein the ranking of the plurality of paragraph templates is independent of the set of attributes; for each sentence type of the selected paragraph template, identify a sentence template of the plurality of sentence templates that corresponds to said sentence type based at least in part on a rank of the identified sentence template and on the set of attributes, wherein each of the variables of the identified sentence template correspond to at least one attribute of the set of attributes, and wherein the ranking of the plurality of sentence templates is independent of the set of attributes; and generate the electronic document based at least in part on processing the selected paragraph template with at least a portion of the set of attributes. | 7. A system for automatically generating content for an electronic document, the system comprising: an electronic data store that stores one or more templates for the electronic documents, wherein the one or more templates comprise: a plurality of paragraph templates for a document paragraph, each paragraph template comprising one or more sentence types, wherein the plurality of paragraph templates are ranked at least according to a desirability of using each paragraph template to generate content describing items of interest, a plurality of sentence templates, each sentence template corresponding to at least one of the one or more sentence types and comprising one or more variables, wherein the plurality of sentence templates are ranked at least according to a desirability of using each sentence template to generate content describing, items of interest; and a content generation service implemented by one or more processors in communication with the electronic data store, the content generation service operative to: obtain data regarding an item of interest to be described in the electronic document, the data comprising a set of attributes associated with the item of interest; select a paragraph template which is to be employed for content generation from the data store based at least in part on the set of attributes and on rankings of the paragraph templates, wherein the ranking of the plurality of paragraph templates is independent of the set of attributes; for each sentence type of the selected paragraph template, identify a sentence template of the plurality of sentence templates that corresponds to said sentence type based at least in part on a rank of the identified sentence template and on the set of attributes, wherein each of the variables of the identified sentence template correspond to at least one attribute of the set of attributes, and wherein the ranking of the plurality of sentence templates is independent of the set of attributes; and generate the electronic document based at least in part on processing the selected paragraph template with at least a portion of the set of attributes. 8. The system of claim 7 , wherein the item of interest comprises at least one of flights, lodging properties, ground transportation, and cruises. | 0.524547 |
1. A computer implemented method for responding to hypertext requests, the computer implemented method comprising: a server receiving a hypertext request from a client; responsive to receiving the hypertext request from the client, looking up a hypertext document, wherein looking up comprises obtaining a first HyperText Markup Language (HTML) element and a second HTML element and combining the first HTML element and second HTML element into a hypertext document; parsing the hypertext document for timeliness tags, wherein a first at least one expire-date tag is a first timeliness tag associated with the first HTML element, the first at least one expire-date tag is expired, and a second at least one expire-date tag is a second timeliness tag associated with the second HTML element, the second at least one expire-date tag is not expired; determining if at least one of the first and second at least one expire-date tags is expired; and responsive to a determination that at least one of the first and second at least one expire-date tags is expired, looking up a timeliness tag rule corresponding to an at least one expired tag, wherein looking up further comprises determining that the first at least one expire-date tag is among the at least one expired tag, and in response, transmitting the second HTML element to the client and excluding transmitting the first HTML element. | 1. A computer implemented method for responding to hypertext requests, the computer implemented method comprising: a server receiving a hypertext request from a client; responsive to receiving the hypertext request from the client, looking up a hypertext document, wherein looking up comprises obtaining a first HyperText Markup Language (HTML) element and a second HTML element and combining the first HTML element and second HTML element into a hypertext document; parsing the hypertext document for timeliness tags, wherein a first at least one expire-date tag is a first timeliness tag associated with the first HTML element, the first at least one expire-date tag is expired, and a second at least one expire-date tag is a second timeliness tag associated with the second HTML element, the second at least one expire-date tag is not expired; determining if at least one of the first and second at least one expire-date tags is expired; and responsive to a determination that at least one of the first and second at least one expire-date tags is expired, looking up a timeliness tag rule corresponding to an at least one expired tag, wherein looking up further comprises determining that the first at least one expire-date tag is among the at least one expired tag, and in response, transmitting the second HTML element to the client and excluding transmitting the first HTML element. 2. The computer implemented method of claim 1 , wherein the computer implemented method further comprises: responsive to receiving the hypertext request from the client, the server determining that a web server module is enabled, wherein looking up the hypertext document is in response to a determination that the web server module is enabled. | 0.587632 |
1. A computer-based method of processing a document having a plurality of input controls, the method comprising: a) in response to a command to display the plurality of input controls, attaching the plurality of input controls to the document; b) in response to a command to hide the plurality of input controls, detaching the plurality of input controls from the document; c) inserting a substitute control in the document and displaying the substitute control in response to the command to hide the plurality of input controls, the command to display the plurality of input controls is invoked by a user selection of the substitute control; and d) sending a value of each input control to a server. | 1. A computer-based method of processing a document having a plurality of input controls, the method comprising: a) in response to a command to display the plurality of input controls, attaching the plurality of input controls to the document; b) in response to a command to hide the plurality of input controls, detaching the plurality of input controls from the document; c) inserting a substitute control in the document and displaying the substitute control in response to the command to hide the plurality of input controls, the command to display the plurality of input controls is invoked by a user selection of the substitute control; and d) sending a value of each input control to a server. 2. The computer-based method of claim 1 , further comprising, in response to rendering the document, detaching the plurality of input controls from the document. | 0.782236 |
24. A method comprising: performing a first-stage processing operation on an audio signal, the first stage processing operation including a windowed signal analysis that derives a raw feature vector; performing a second stage statistical processing operation on the raw feature vector to derive a reduced feature vector; performing a third stage processing operation on the reduced feature vector to derive at least one sound object label that refers to the original audio signal; and mapping the at least one sound object label into a stream of control events sent to a sound-object-driven, multimedia-aware software application, wherein the sound-object-driven multimedia-aware software application is responsive to the stream of control events to configure processing for the audio signal, and wherein any of the processing operations of the first through third stages are configurable. | 24. A method comprising: performing a first-stage processing operation on an audio signal, the first stage processing operation including a windowed signal analysis that derives a raw feature vector; performing a second stage statistical processing operation on the raw feature vector to derive a reduced feature vector; performing a third stage processing operation on the reduced feature vector to derive at least one sound object label that refers to the original audio signal; and mapping the at least one sound object label into a stream of control events sent to a sound-object-driven, multimedia-aware software application, wherein the sound-object-driven multimedia-aware software application is responsive to the stream of control events to configure processing for the audio signal, and wherein any of the processing operations of the first through third stages are configurable. 29. The method of claim 24 , wherein the method is executable to identify an environment surrounding a source of the audio signal, and a functionality of a mobile device is configured in response to identification of the environment. | 0.669113 |
1. An application development system operable on a computer processor, said application development environment comprising: a test code execution system that executes test code against application code to generate test results, said test code having a plurality of test code components, each of said test code components being separately executable; a test code evaluator that determines a qualitative test code health metric for each of said test code components, said test code evaluator evaluating assertion defined in said test code by: determining a block of application code covered by a first test code component; identifying each output from said block to determine a number of outputs; examining said first test code component to determine a number of assertions corresponding to said outputs; using said number of assertions and said number of outputs to determine a qualitative test code health metric; a user interface on which said test code components are displayed with an indicator for said qualitative test code health metric; a code editor capable of editing said test code and said application code; and an automated test code generator that examines said application code and generates at least a portion of said test code components. | 1. An application development system operable on a computer processor, said application development environment comprising: a test code execution system that executes test code against application code to generate test results, said test code having a plurality of test code components, each of said test code components being separately executable; a test code evaluator that determines a qualitative test code health metric for each of said test code components, said test code evaluator evaluating assertion defined in said test code by: determining a block of application code covered by a first test code component; identifying each output from said block to determine a number of outputs; examining said first test code component to determine a number of assertions corresponding to said outputs; using said number of assertions and said number of outputs to determine a qualitative test code health metric; a user interface on which said test code components are displayed with an indicator for said qualitative test code health metric; a code editor capable of editing said test code and said application code; and an automated test code generator that examines said application code and generates at least a portion of said test code components. 4. The system of claim 1 , said test code evaluator further determining a test result metric comprising said test code health metric. | 0.543964 |
1. A method comprising: receiving a task flow that describes operations of a dialog system that provides synthesized speech responses to spoken user input by a caller; generating a script that is a formal description of the task flow; automatically generating a graphical user interface (GUI) from the script, the GUI consisting of templates for control of the dialog system, generation of context-dependent synthesized speech prompts, and real-time collection and annotating of dialog data during a live dialog between only the dialog system and the caller to the dialog system, the GUI comprising a first portion for input of caller provided information, a second portion comprising an output control panel for control of the synthesized speech prompts by a human operator, a third portion providing status of a current task within the task flow, and a fourth portion providing an graphical representation of the task flow; and detecting the presence of an abnormality in speech processing during the task flow and automatically switching control to the human operator to allow direct interaction with the caller to correct the abnormality. | 1. A method comprising: receiving a task flow that describes operations of a dialog system that provides synthesized speech responses to spoken user input by a caller; generating a script that is a formal description of the task flow; automatically generating a graphical user interface (GUI) from the script, the GUI consisting of templates for control of the dialog system, generation of context-dependent synthesized speech prompts, and real-time collection and annotating of dialog data during a live dialog between only the dialog system and the caller to the dialog system, the GUI comprising a first portion for input of caller provided information, a second portion comprising an output control panel for control of the synthesized speech prompts by a human operator, a third portion providing status of a current task within the task flow, and a fourth portion providing an graphical representation of the task flow; and detecting the presence of an abnormality in speech processing during the task flow and automatically switching control to the human operator to allow direct interaction with the caller to correct the abnormality. 10. The method of claim 1 , wherein the formal description includes memory allocations for maintaining state of the interactive system. | 0.676751 |
8. A method for managing user profiles stored in association with business information for user-selected businesses and for identifying additional businesses at least partially based on social graph information and affinity group information, the method comprising: aggregating, via one or more network interfaces of a server system, social graph information, user preference information relating to the business information, and affinity group information from one or more remote data sources; identifying a first user having a first user profile stored in one or more databases of the server system, the first user profile associated with a first set of business information for a first set of businesses previously selected by the first user for saving in association with the first user profile; determining a location corresponding to the first user; searching for one or more additional businesses relevant to the location, to identify at least one of the one or more additional businesses to the first user with an option to add the at least one of the one or more additional businesses to the first set of businesses previously selected by the first user, the searching comprising: processing the social graph information relating to a set of users to identify information about one or more networks of social relationships between two or more users of the set of users, the one or more networks of social relationships being associated with one or more social networking websites, wherein the set of users comprises the first user; processing the user preference information relating to a second set of businesses, the user preference information indicating that, for one or more businesses of the second set of businesses, one or more users of the set of users have indicated one or more preferences for the one or more businesses of the second set of businesses; process the affinity group information to identify whether the one or more users of the set of users correspond to one or more affinity groups; and selecting the at least one of the one or more additional businesses based at least in part on the location, the processing the social graph information, the processing the user preference information, and the processing the affinity group information; transmitting, via the one or more network interfaces, to an end-user device an indication of the at least one of the one or more additional businesses, causing a user-selectable option to add the at least one of the one or more additional businesses to the first set of businesses previously selected by the first user; and responsive to a selection of the user-selectable option, save additional business information corresponding to the at least one of the one or more additional businesses in association with the first user profile in the one or more databases. | 8. A method for managing user profiles stored in association with business information for user-selected businesses and for identifying additional businesses at least partially based on social graph information and affinity group information, the method comprising: aggregating, via one or more network interfaces of a server system, social graph information, user preference information relating to the business information, and affinity group information from one or more remote data sources; identifying a first user having a first user profile stored in one or more databases of the server system, the first user profile associated with a first set of business information for a first set of businesses previously selected by the first user for saving in association with the first user profile; determining a location corresponding to the first user; searching for one or more additional businesses relevant to the location, to identify at least one of the one or more additional businesses to the first user with an option to add the at least one of the one or more additional businesses to the first set of businesses previously selected by the first user, the searching comprising: processing the social graph information relating to a set of users to identify information about one or more networks of social relationships between two or more users of the set of users, the one or more networks of social relationships being associated with one or more social networking websites, wherein the set of users comprises the first user; processing the user preference information relating to a second set of businesses, the user preference information indicating that, for one or more businesses of the second set of businesses, one or more users of the set of users have indicated one or more preferences for the one or more businesses of the second set of businesses; process the affinity group information to identify whether the one or more users of the set of users correspond to one or more affinity groups; and selecting the at least one of the one or more additional businesses based at least in part on the location, the processing the social graph information, the processing the user preference information, and the processing the affinity group information; transmitting, via the one or more network interfaces, to an end-user device an indication of the at least one of the one or more additional businesses, causing a user-selectable option to add the at least one of the one or more additional businesses to the first set of businesses previously selected by the first user; and responsive to a selection of the user-selectable option, save additional business information corresponding to the at least one of the one or more additional businesses in association with the first user profile in the one or more databases. 10. The method for managing user profiles stored in association with business information for user-selected businesses and for identifying additional businesses at least partially based on social graph information and affinity group information of claim 8 , wherein the aggregating the social graph information, the user preference information relating to the business information, and the affinity group information from one or more remote data sources comprises: processing transmissions from user devices, the transmissions indicative of user selections of businesses via browser-enabled options facilitated by browser plug-ins. | 0.587299 |
1. A method for providing a document comprising: processing, by one or more processors, a graphical document to identify one or more ideas associated with the graphical document including processing documents that are linked to the graphical document to derive at least one of the one or more ideas; receiving, by the one or more processors, a request for a document where the document is associated with a concept; comparing, by the one or more processors, the one or more ideas with the concept; and responsive to the request, delivering, by the one or more processors, the graphical document based on the comparison if the one or more ideas match the concept. | 1. A method for providing a document comprising: processing, by one or more processors, a graphical document to identify one or more ideas associated with the graphical document including processing documents that are linked to the graphical document to derive at least one of the one or more ideas; receiving, by the one or more processors, a request for a document where the document is associated with a concept; comparing, by the one or more processors, the one or more ideas with the concept; and responsive to the request, delivering, by the one or more processors, the graphical document based on the comparison if the one or more ideas match the concept. 9. The method of claim 1 , wherein processing the graphical document to identify one or more ideas associated with the graphical document comprises: identifying, using an image processor, at least one image in the graphical document; and associating at least one of the one or more ideas with the graphical document based on the at least one identified image. | 0.58296 |
1. A method of data caching for compliance and storage systems that provides keyword search query based access to documents, the method comprising: searching documents from a storage device by a keyword based interface; staging from a cache documents that are read and that are expected to be needed again from the storage device; computing a document weight for each of the documents read and expected to be needed again, wherein the document weight is based on a document information retrieval (IR) relevancy metric for user keyword queries and a recency and a frequency of each query and the document weight models a probability of a particular document being accessed again through a query, and wherein the document weight is based on a relevance of each document for queries in a query history; placing a processor and a disk in data communication with a First In First Out queue and a cache; and if the document being accessed again was not already in the cache, evicting another document from the cache to make room for the document being accessed again to be placed in the cache by packing elements in the order of a document weight-to-size ratio, highest to smallest, and evicting documents with a smallest document weight-to-size ratio first; maintaining a query history of recent queries from a user in a query history first-in first-out queue; assigning each query from a user a query weight based on a position of the query from a user in the First In First Out queue, wherein the query weight models a probability of a query or a related query being invoked again; wherein each one of the document weight is recomputed by the processor when a document to be retrieved was not previously cached; updating the query history First-in First-Out queue and each of the document weights when a new query has been entered; adapting each of the document weights to changing query frequencies and popularities; and selecting and evicting documents from the cache according to a knapsack solution. | 1. A method of data caching for compliance and storage systems that provides keyword search query based access to documents, the method comprising: searching documents from a storage device by a keyword based interface; staging from a cache documents that are read and that are expected to be needed again from the storage device; computing a document weight for each of the documents read and expected to be needed again, wherein the document weight is based on a document information retrieval (IR) relevancy metric for user keyword queries and a recency and a frequency of each query and the document weight models a probability of a particular document being accessed again through a query, and wherein the document weight is based on a relevance of each document for queries in a query history; placing a processor and a disk in data communication with a First In First Out queue and a cache; and if the document being accessed again was not already in the cache, evicting another document from the cache to make room for the document being accessed again to be placed in the cache by packing elements in the order of a document weight-to-size ratio, highest to smallest, and evicting documents with a smallest document weight-to-size ratio first; maintaining a query history of recent queries from a user in a query history first-in first-out queue; assigning each query from a user a query weight based on a position of the query from a user in the First In First Out queue, wherein the query weight models a probability of a query or a related query being invoked again; wherein each one of the document weight is recomputed by the processor when a document to be retrieved was not previously cached; updating the query history First-in First-Out queue and each of the document weights when a new query has been entered; adapting each of the document weights to changing query frequencies and popularities; and selecting and evicting documents from the cache according to a knapsack solution. 3. The method of claim 1 , wherein if all document sizes are the same, the ordering is done according to cached values of said document weight. | 0.819549 |
7. A data processing system comprising: a bus; a storage device connected to the bus, wherein computer usable code is located in the storage device; a communication unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to install a rules engine among a plurality of rules engines in an object grid, wherein the rules engine is executable code executing using computer resources; initialize the rules engine in the object grid; update a business mapper; receive a business rule definition to form a business rule; determine that business terms are present in the business rule; convert the business terms to technical terms using the rules engine selected among the plurality of rules engines to look up a technical term from an array to find a corresponding business term from, responsive to a determination that business terms are present; determine that the business rule comprises a temporal rule; receive rule criteria, wherein the rule criteria is at least one selected from the group consisting of frequency, delay and timing dependency, responsive to the determination that the business rule is the temporal rule; store the business rule to the rules engine; and publish the business rule to a publish-subscribe topic. | 7. A data processing system comprising: a bus; a storage device connected to the bus, wherein computer usable code is located in the storage device; a communication unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to install a rules engine among a plurality of rules engines in an object grid, wherein the rules engine is executable code executing using computer resources; initialize the rules engine in the object grid; update a business mapper; receive a business rule definition to form a business rule; determine that business terms are present in the business rule; convert the business terms to technical terms using the rules engine selected among the plurality of rules engines to look up a technical term from an array to find a corresponding business term from, responsive to a determination that business terms are present; determine that the business rule comprises a temporal rule; receive rule criteria, wherein the rule criteria is at least one selected from the group consisting of frequency, delay and timing dependency, responsive to the determination that the business rule is the temporal rule; store the business rule to the rules engine; and publish the business rule to a publish-subscribe topic. 8. The data processing system of claim 7 , wherein the object grid is at least two processors in a network environment configured to execute distributed java objects that permit caching of data and java objects among several computer resources. | 0.579928 |
8. The method of claim 7 , further comprising determining a length of the first string. | 8. The method of claim 7 , further comprising determining a length of the first string. 10. The method of claim 8 , wherein the second end segment is determined based on the length of the first string. | 0.939555 |
10. The system of claim 7 , wherein the user search query comprises multiple visual media input files, and wherein the processor being configured to analyze the index of visual portions of the plurality of visual media files from the collection comprises the processor being configured to identify the at least one responsive visual media file from the collection that comprises visual portions associated with visual similarity scores to the visual portions of the multiple visual media input files that exceed a similarity threshold value. | 10. The system of claim 7 , wherein the user search query comprises multiple visual media input files, and wherein the processor being configured to analyze the index of visual portions of the plurality of visual media files from the collection comprises the processor being configured to identify the at least one responsive visual media file from the collection that comprises visual portions associated with visual similarity scores to the visual portions of the multiple visual media input files that exceed a similarity threshold value. 11. The system of claim 10 , wherein the processor being configured to provide the identifier of the at least one responsive visual media file from the collection of media files for display as responsive to the search query comprises the processor being configured to provide identifiers of a plurality of responsive visual media files from the collection of media files in response to the search query, wherein each of the plurality of responsive visual media files from the collection of media files is associated with a responsiveness score, and wherein the identifiers of the plurality of responsive visual media files are prioritized for display according to the corresponding responsiveness score of the corresponding responsive visual media file. | 0.87372 |
2. The method of claim 1 , further comprising sequentially for each consecutive note of the audio input, determining a probability of each alternative subsequent note following each respective note of the selected plurality of subsequent notes corresponding to the preceding note; and wherein selecting the best-match note for each note of the audio input is further based on the determined probabilities of all of the plurality of notes of the audio input. | 2. The method of claim 1 , further comprising sequentially for each consecutive note of the audio input, determining a probability of each alternative subsequent note following each respective note of the selected plurality of subsequent notes corresponding to the preceding note; and wherein selecting the best-match note for each note of the audio input is further based on the determined probabilities of all of the plurality of notes of the audio input. 3. The method of claim 2 , wherein the probability is determined based on an analysis of a selection of pre-existing musical compositions. | 0.875746 |
1. A method for identifying errors in software code in a multi-tenant environment comprising: calculating, by a host system, memory usage statistics of each of a group of objects that contributed to a current heap dump, the host system including a set of one or more processors and a memory system including one or more computer readable media by the set of one or more processors; identifying, by the host system, top consumers of memory by object of the current heap dump; determining, by the host system, how much memory a given one of the top consumers consumes with respect to how much memory top consumers other than the given one of the top consumers consume; computing, by the host system, a suspect score based on the determining; and determining, by the host system, whether the given one of the top consumers is likely to have caused memory issues based on the suspect score. | 1. A method for identifying errors in software code in a multi-tenant environment comprising: calculating, by a host system, memory usage statistics of each of a group of objects that contributed to a current heap dump, the host system including a set of one or more processors and a memory system including one or more computer readable media by the set of one or more processors; identifying, by the host system, top consumers of memory by object of the current heap dump; determining, by the host system, how much memory a given one of the top consumers consumes with respect to how much memory top consumers other than the given one of the top consumers consume; computing, by the host system, a suspect score based on the determining; and determining, by the host system, whether the given one of the top consumers is likely to have caused memory issues based on the suspect score. 11. The method of claim 1 , the host system having a plurality of servers on which the objects run. | 0.656734 |
1. A computer-implemented method comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. | 1. A computer-implemented method comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. 7. The method of claim 1 , wherein generating the presentation of highest-ranked first search results and second search results in the presentation order comprises generating the presentation including two or more of the first search results in a group among one or more second search results. | 0.616746 |
14. The non-transitory computer-readable storage medium as claimed in claim 9 , wherein classifying the text elements according to the available voice types further comprises finding the best match between the grouped text elements and the characteristics of the voice types. | 14. The non-transitory computer-readable storage medium as claimed in claim 9 , wherein classifying the text elements according to the available voice types further comprises finding the best match between the grouped text elements and the characteristics of the voice types. 16. The non-transitory computer-readable storage medium as claimed in claim 14 , wherein classifying the text elements according to the characteristics of the available voice types further comprises identifying similar intentions within the text elements and voice types. | 0.877441 |
3. A system according to claim 1 , further comprising: a population module to identify a second population of the trait to which the candidate agent shares voice characteristics. | 3. A system according to claim 1 , further comprising: a population module to identify a second population of the trait to which the candidate agent shares voice characteristics. 4. A system according to claim 3 , further comprising: an inclusion module to determine for each of the population and the further population, a percentage of inclusion with which the candidate agent shares voice characteristics for that population. | 0.920522 |
1. A method executed by a processor of a computing device, the method comprising: generating a graphical summary of a research document for presentment on a display of a computing device in response to receipt of user input that identifies the research document, the research document having a publication date assigned thereto that indicates a date upon which the research document was published, the graphical summary of the research document is based upon content from other research documents, the other research documents include citations to the research document, the other research documents having publication dates that are subsequent to the publication date of the research document, the graphical summary of the research document comprises: a node that is representative of the research document; and portions of sentences in the other research documents that include the citations to the research document; and presenting the graphical summary of the research document on the display of the computing device. | 1. A method executed by a processor of a computing device, the method comprising: generating a graphical summary of a research document for presentment on a display of a computing device in response to receipt of user input that identifies the research document, the research document having a publication date assigned thereto that indicates a date upon which the research document was published, the graphical summary of the research document is based upon content from other research documents, the other research documents include citations to the research document, the other research documents having publication dates that are subsequent to the publication date of the research document, the graphical summary of the research document comprises: a node that is representative of the research document; and portions of sentences in the other research documents that include the citations to the research document; and presenting the graphical summary of the research document on the display of the computing device. 11. The method of claim 1 , wherein the graphical summary of the research document further comprises: data that identifies an author of the research document; and data that identifies at least one other publication authored by the author of the research document. | 0.599845 |
17. A control method for a TV having a language selection function, comprising: receiving closed caption character information in a first language and contacting an appropriate translation site through a network interface if it is determined that the first language associated with the closed caption character information does not correspond to a selected language, comprising: selecting the appropriate translation site based on the selected language and contacting the appropriate translation site based on previously stored contact information related to a plurality of translation sites; requesting translation of the closed caption character information from the first language to the selected language by transmitting the closed caption character information to the appropriate translation site; and receiving closed caption character information which has been translated into the selected language from the translation site; and displaying the translated closed caption character information on a screen substantially in synch with corresponding audio information. | 17. A control method for a TV having a language selection function, comprising: receiving closed caption character information in a first language and contacting an appropriate translation site through a network interface if it is determined that the first language associated with the closed caption character information does not correspond to a selected language, comprising: selecting the appropriate translation site based on the selected language and contacting the appropriate translation site based on previously stored contact information related to a plurality of translation sites; requesting translation of the closed caption character information from the first language to the selected language by transmitting the closed caption character information to the appropriate translation site; and receiving closed caption character information which has been translated into the selected language from the translation site; and displaying the translated closed caption character information on a screen substantially in synch with corresponding audio information. 22. The control method of a TV having a language selection function according to claim 17 , wherein the translation site is selected from a plurality of previously stored translation sites. | 0.729782 |
1. A method, in an information handling system comprising a processor and a memory, for ingesting additional content in a knowledge base, the method comprising: mining, by the system, an interaction history comprising a plurality of questions and answer results to identify a first question by performing a natural language processing (NLP) analysis of the plurality of questions and answer results to detect the first question that meets specified answer deficiency criteria; generating, by the system, a second question which is correlated to the first question by extracting a text sentence from one or more documents correlated to the first question and parsing the text sentence to populate a defined question template used to construct the second question requesting additional answer information for answering the first question; selecting, by the system, at least one persona to post the second question; posting, by the system, the second question to a forum using the at least one persona; monitoring, by the system, the forum for responses to the second question; and ingesting, by the system, any response to the second question as additional content in the knowledge base. | 1. A method, in an information handling system comprising a processor and a memory, for ingesting additional content in a knowledge base, the method comprising: mining, by the system, an interaction history comprising a plurality of questions and answer results to identify a first question by performing a natural language processing (NLP) analysis of the plurality of questions and answer results to detect the first question that meets specified answer deficiency criteria; generating, by the system, a second question which is correlated to the first question by extracting a text sentence from one or more documents correlated to the first question and parsing the text sentence to populate a defined question template used to construct the second question requesting additional answer information for answering the first question; selecting, by the system, at least one persona to post the second question; posting, by the system, the second question to a forum using the at least one persona; monitoring, by the system, the forum for responses to the second question; and ingesting, by the system, any response to the second question as additional content in the knowledge base. 3. The method of claim 1 , wherein generating the second question comprises: retrieving, by the system, one or more documents associated with the identified first question; extracting, by the system, a text sentence from the one or more documents which is correlated to the first question; and generating, by the system, the second question by parsing the text sentence to populate a defined question template used to construct the second question. | 0.5 |
12. A system for identifying a preferred machine translation of a content item, comprising: a content item classification engine configured to classify the content item based on one or more categories, the categories including at least the topic of the content item; a user group defining engine configured to classify a plurality of users based on one or more categories, the one or more categories including at least an interest in one or more topics; a machine translation generation engine configured to generate multiple computer-generated translations of the content item-in a specified target language the multiple translations using configurable parameters and forming a set of translations; and a scoring engine configured to: perform one or more iterations each iteration comprising: selecting multiple groups of users based on a mapping between the one or more content item categories and the one or more user categories; submitting each translation in the set to one group of users; receiving, from each user in the group, a translation score for the reviewed translation; weighting the translation score received from each user by a user-importance factor calculated as a function of a deviation of the user's scores from average scores for previous translations; computing an aggregate score for each reviewed translation, based on the weighted scores from all users in the reviewing group; determining if the iteration has produced a preferred translation, the preferred translation being a translation from the set having an aggregate score above a predetermined threshold, or translation having an aggregate score higher than the aggregate score for all other translations in the group by predetermined threshold; and repeating the iteration if no preferred translation has been produced providing the preferred machine translation in response a subsequent request for a translation of the content item. | 12. A system for identifying a preferred machine translation of a content item, comprising: a content item classification engine configured to classify the content item based on one or more categories, the categories including at least the topic of the content item; a user group defining engine configured to classify a plurality of users based on one or more categories, the one or more categories including at least an interest in one or more topics; a machine translation generation engine configured to generate multiple computer-generated translations of the content item-in a specified target language the multiple translations using configurable parameters and forming a set of translations; and a scoring engine configured to: perform one or more iterations each iteration comprising: selecting multiple groups of users based on a mapping between the one or more content item categories and the one or more user categories; submitting each translation in the set to one group of users; receiving, from each user in the group, a translation score for the reviewed translation; weighting the translation score received from each user by a user-importance factor calculated as a function of a deviation of the user's scores from average scores for previous translations; computing an aggregate score for each reviewed translation, based on the weighted scores from all users in the reviewing group; determining if the iteration has produced a preferred translation, the preferred translation being a translation from the set having an aggregate score above a predetermined threshold, or translation having an aggregate score higher than the aggregate score for all other translations in the group by predetermined threshold; and repeating the iteration if no preferred translation has been produced providing the preferred machine translation in response a subsequent request for a translation of the content item. 15. The system of claim 12 , wherein the set of translations, in subsequent iterations, includes only a subset of the translations from the previous iteration, the subset including: a fixed number or percentage of the previous set of translations that have the highest computed aggregate scores; or translations, from the previous set of translations having aggregate scores that are higher than the computed aggregate scores for non-selected computer-generated translations and that do not differ from each other by a value greater than a threshold. | 0.5 |
1. A method for a database system, comprising: establishing a column-oriented in-memory database structure including a main store and a dictionary compressed delta store, wherein the delta store comprises a value identifier vector that includes each value of a record stored in a same row of a column of the database and a delta dictionary associated with the column of the database; receiving a transaction associated with the column; recording the transaction within the delta store; adding an entry associated with the transaction to a value log of the value identifier vector, the value log comprising a transaction identifier and a row identifier indicating a row in the value identifier vector; and adding an entry associated with the transaction to a dictionary log of the delta dictionary. | 1. A method for a database system, comprising: establishing a column-oriented in-memory database structure including a main store and a dictionary compressed delta store, wherein the delta store comprises a value identifier vector that includes each value of a record stored in a same row of a column of the database and a delta dictionary associated with the column of the database; receiving a transaction associated with the column; recording the transaction within the delta store; adding an entry associated with the transaction to a value log of the value identifier vector, the value log comprising a transaction identifier and a row identifier indicating a row in the value identifier vector; and adding an entry associated with the transaction to a dictionary log of the delta dictionary. 10. The method of claim 1 , wherein the delta dictionary comprises an unsorted array. | 0.723911 |
4. The method of claim 1 , wherein selecting the minimum colored subset of the nodes and leaves in the suffix tree comprises determining optimal conditional rules for each node and leaf in the suffix tree, and then selecting the minimum colored subset and the optimal canonical suffix-rewriting rule for each node and leaf in the subset according to the optimal conditional rules. | 4. The method of claim 1 , wherein selecting the minimum colored subset of the nodes and leaves in the suffix tree comprises determining optimal conditional rules for each node and leaf in the suffix tree, and then selecting the minimum colored subset and the optimal canonical suffix-rewriting rule for each node and leaf in the subset according to the optimal conditional rules. 5. The method of claim 4 , wherein: the optimal conditional rule for a node or leaf is the rule that is optimal for the condition that a parent node of the node or leaf is associated with a particular canonical suffix-rewriting rule; and selecting an optimal canonical suffix-rewriting rule for each node according to the optimal conditional rules for the node comprises: determining an optimal canonical suffix-rewriting rule for a root of the suffix tree; and determining an optimal canonical suffix-rewriting rule for each remaining node in the tree, wherein the optimal canonical suffix-rewriting rule for a node in the tree is the optimal conditional rule for the canonical suffix-rewriting rule associated with a parent of the node. | 0.809177 |
4. The method of claim 1 , wherein the improved query includes a reference to a denormalized table, wherein the denormalized table comprises data accessible by the tenant. | 4. The method of claim 1 , wherein the improved query includes a reference to a denormalized table, wherein the denormalized table comprises data accessible by the tenant. 5. The method of claim 4 , wherein the denormalized table comprises a search name lookup table. | 0.967271 |
2. The method of claim 1 , wherein updating the predictive text dictionary further comprises: determining whether to discard a second existing word from the predictive text dictionary; and discarding the second existing word from the predictive text dictionary. | 2. The method of claim 1 , wherein updating the predictive text dictionary further comprises: determining whether to discard a second existing word from the predictive text dictionary; and discarding the second existing word from the predictive text dictionary. 3. The method of claim 2 , wherein determining whether to discard the second existing word from the predictive text dictionary further comprises: receiving from the server a user preference associated with the computing device; and determining whether a word category is removed in the user preference. | 0.931355 |
1. A method for generating a protocol agent for a managed system, comprising: using a processor for: obtaining a protocol specification comprising a plurality of first mappings to an information model specification; and generating the protocol agent using the protocol specification, wherein the protocol agent comprises a plurality of second mappings to an implementation of a unified information model generated using the information model specification, wherein the second mappings are formed using the first mappings. | 1. A method for generating a protocol agent for a managed system, comprising: using a processor for: obtaining a protocol specification comprising a plurality of first mappings to an information model specification; and generating the protocol agent using the protocol specification, wherein the protocol agent comprises a plurality of second mappings to an implementation of a unified information model generated using the information model specification, wherein the second mappings are formed using the first mappings. 5. The method of claim 1 , wherein the implementation of the unified information model comprises a plurality of logical entities, wherein the logical entities represent a plurality of physical entities of the managed system. | 0.829027 |
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