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9,189,069 | 14 | 16 | 14. A mobile device comprising: one or more processors; one or more sensors configured to sense tilting movement of the mobile device and to sense linear acceleration of the mobile device; a user interface; and executable instructions, which when executed by the one or more processors, configure the one or more processors to: display a first application window in the user interface of the mobile device; receive first sensor signals from at least one of the sensors; determine that a tilting gesture has been made with the mobile device based on the first sensor signals, the tilting gesture comprising rotation of the mobile device about at least one axis; alter an image within the displayed first application window based on the stilting gesture: receive a second sensor signal from at least one of the sensors indicating a rapid linear acceleration of the mobile device upon which the mobile device experiences a bulk translation in a substantially linear direction; determine that a flinging gesture has been made with the mobile device, as if the mobile device is being thrown, by utilizing the second sensor signal to distinguish the linear acceleration of the mobile device from the tilting gesture and from a shaking gesture with the mobile device; and based on determining that the flinging gesture has been made with the mobile device, switch from displaying the first application window in the user interface to displaying a second application window in the user interface. | 14. A mobile device comprising: one or more processors; one or more sensors configured to sense tilting movement of the mobile device and to sense linear acceleration of the mobile device; a user interface; and executable instructions, which when executed by the one or more processors, configure the one or more processors to: display a first application window in the user interface of the mobile device; receive first sensor signals from at least one of the sensors; determine that a tilting gesture has been made with the mobile device based on the first sensor signals, the tilting gesture comprising rotation of the mobile device about at least one axis; alter an image within the displayed first application window based on the stilting gesture: receive a second sensor signal from at least one of the sensors indicating a rapid linear acceleration of the mobile device upon which the mobile device experiences a bulk translation in a substantially linear direction; determine that a flinging gesture has been made with the mobile device, as if the mobile device is being thrown, by utilizing the second sensor signal to distinguish the linear acceleration of the mobile device from the tilting gesture and from a shaking gesture with the mobile device; and based on determining that the flinging gesture has been made with the mobile device, switch from displaying the first application window in the user interface to displaying a second application window in the user interface. 16. The mobile device of claim 14 , wherein the first and second application windows comprise different pages within a same application. | 0.741445 |
8,924,844 | 23 | 27 | 23. An article of manufacture including a non-transitory computer-readable medium having instructions stored thereon that, wherein the instructions are configured to cause a computing device, in response to execution of the instructions by the computing device, to perform operations comprising: selecting an object rendered on a display, wherein the object is associated with an application that includes a first call to a program, wherein the first call is configured to cause the program to render the object on the display; receiving a plurality of annotations associated with the selected object; determining the verbosity level of each annotation of the plurality of annotations, wherein each of the plurality of annotations includes a different verbosity level, and wherein for any two of the annotations associated with the selected object and having different verbosity levels, a first annotation associated with a first verbosity level represents information in a textually-shortened form from information represented in a second of the two annotations with a second verbosity level higher than the first verbosity level, and wherein the first annotation associated with the lower verbosity level comprises an icon; and during execution of the application, and prior to execution of the first call, replacing the first call with a second call to be executed in place of the first call, wherein the second call is different from the first call and is itself configured to both render the plurality of annotations on the display and to cause the program to render the object without requiring execution of the first call, wherein the second call is configured to render the annotations individually based on a requested verbosity level. | 23. An article of manufacture including a non-transitory computer-readable medium having instructions stored thereon that, wherein the instructions are configured to cause a computing device, in response to execution of the instructions by the computing device, to perform operations comprising: selecting an object rendered on a display, wherein the object is associated with an application that includes a first call to a program, wherein the first call is configured to cause the program to render the object on the display; receiving a plurality of annotations associated with the selected object; determining the verbosity level of each annotation of the plurality of annotations, wherein each of the plurality of annotations includes a different verbosity level, and wherein for any two of the annotations associated with the selected object and having different verbosity levels, a first annotation associated with a first verbosity level represents information in a textually-shortened form from information represented in a second of the two annotations with a second verbosity level higher than the first verbosity level, and wherein the first annotation associated with the lower verbosity level comprises an icon; and during execution of the application, and prior to execution of the first call, replacing the first call with a second call to be executed in place of the first call, wherein the second call is different from the first call and is itself configured to both render the plurality of annotations on the display and to cause the program to render the object without requiring execution of the first call, wherein the second call is configured to render the annotations individually based on a requested verbosity level. 27. The article of manufacture of claim 23 , wherein selecting comprises: determining that the object on the display is associated with a graphical cursor image; and receiving an indication that the object has been selected. | 0.686275 |
9,514,377 | 12 | 13 | 12. The computer-implemented method of claim 11 , further comprising transmitting, from the mobile computing device to the server, all of the OCR text when the degree of translation complexity is greater than a second translation complexity threshold that is greater than the first translation complexity threshold, wherein the second translation complexity threshold represents a degree of translation complexity that the mobile computing device is not appropriate for performing itself. | 12. The computer-implemented method of claim 11 , further comprising transmitting, from the mobile computing device to the server, all of the OCR text when the degree of translation complexity is greater than a second translation complexity threshold that is greater than the first translation complexity threshold, wherein the second translation complexity threshold represents a degree of translation complexity that the mobile computing device is not appropriate for performing itself. 13. The computer-implemented method of claim 12 , wherein when the degree of translation complexity is between the first and second translation complexity thresholds, the mobile computing device performs machine language translation for a first portion of the OCR text and the mobile computing device transmits a second portion of the OCR text to the server, the first and second portions of the OCR text collectively forming the entire OCR text. | 0.5 |
9,436,891 | 1 | 8 | 1. A method for identifying synonymous expressions, comprising: determining synonymous expression candidates for a target non-facial-based expression; identifying a plurality of target images related to the target non-facial-based expression and a plurality of candidate images related to each of the synonymous expression candidates; and comparing features extracted from the plurality of target images with features extracted from the plurality of candidate images using a processor to identify a synonymous expression of the target non-facial-based expression, wherein the synonymous expression includes at least one of a word, a phrase, and a sound. | 1. A method for identifying synonymous expressions, comprising: determining synonymous expression candidates for a target non-facial-based expression; identifying a plurality of target images related to the target non-facial-based expression and a plurality of candidate images related to each of the synonymous expression candidates; and comparing features extracted from the plurality of target images with features extracted from the plurality of candidate images using a processor to identify a synonymous expression of the target non-facial-based expression, wherein the synonymous expression includes at least one of a word, a phrase, and a sound. 8. The method as recited in claim 1 , further comprising removing outliers from the plurality of target images. | 0.739437 |
8,265,933 | 16 | 17 | 16. The computing device of claim 13 , wherein the at least one processor is further programmed to adjust the probability for at least one word in the at least one selected n-gram based, at least in part, on the first text. | 16. The computing device of claim 13 , wherein the at least one processor is further programmed to adjust the probability for at least one word in the at least one selected n-gram based, at least in part, on the first text. 17. The computing device of claim 16 , wherein the probability for the at least one candidate word of the at least one of the plurality of n-grams is increased. | 0.5 |
8,646,029 | 22 | 23 | 22. The computing device of claim 14 , the computer readable instructions further configured to implement: a binding module configured to enable unified programming access between the web browser's scripting engine and layout engine, the binding module comprising a module configured to enable one or more properties associated with the layout engine to be virtually replaced by the scripting engine. | 22. The computing device of claim 14 , the computer readable instructions further configured to implement: a binding module configured to enable unified programming access between the web browser's scripting engine and layout engine, the binding module comprising a module configured to enable one or more properties associated with the layout engine to be virtually replaced by the scripting engine. 23. The computing device of claim 22 , at least one property of the one or more properties associated with the layout engine comprising a read-only value. | 0.5 |
4,445,196 | 2 | 4 | 2. The calculator set forth in claim 1 further including selection command data storage means coupled to said biblical text storage means for retaining data indicative of said selection command data generated by said address keying means for enabling regeneration of selected text at a later time. | 2. The calculator set forth in claim 1 further including selection command data storage means coupled to said biblical text storage means for retaining data indicative of said selection command data generated by said address keying means for enabling regeneration of selected text at a later time. 4. The calculator as set forth in claim 2 wherein said character display means is configured to produce larger characters than those printed in the average Bible. | 0.5 |
8,024,345 | 7 | 10 | 7. A system for associating advertisements with a web page, said system comprising one or more tangible computer readable storage media having stored thereon: a database containing advertisements and associated advertisement keyword meanings; an indexing module for creating an advertisement reference index for said advertisements contained in said database, wherein said advertisements are indexed based on the associated advertisement keyword meanings; a disambiguation module for disambiguating words contained on the web page into page keyword meanings, each of said page keyword meanings comprising a specific deduced intended meaning of a respective word on the web page, in view of the context of its usage on the web page; a keyword expanding module for expanding said page keyword meanings using their relevant semantic relations to other word meanings to create an expanded list of page keyword meanings; and, a text processing module for: searching the advertisement reference index to find relevant advertisements for said web page by matching the page keyword meanings to the advertisement keyword meanings indexed in said database; and providing search results comprising said relevant advertisements. | 7. A system for associating advertisements with a web page, said system comprising one or more tangible computer readable storage media having stored thereon: a database containing advertisements and associated advertisement keyword meanings; an indexing module for creating an advertisement reference index for said advertisements contained in said database, wherein said advertisements are indexed based on the associated advertisement keyword meanings; a disambiguation module for disambiguating words contained on the web page into page keyword meanings, each of said page keyword meanings comprising a specific deduced intended meaning of a respective word on the web page, in view of the context of its usage on the web page; a keyword expanding module for expanding said page keyword meanings using their relevant semantic relations to other word meanings to create an expanded list of page keyword meanings; and, a text processing module for: searching the advertisement reference index to find relevant advertisements for said web page by matching the page keyword meanings to the advertisement keyword meanings indexed in said database; and providing search results comprising said relevant advertisements. 10. The system of claim 7 wherein: said database further contains said web pages and associated page keyword meanings; said indexing module further creates a web page reference index for said web pages contained in said database, wherein said web pages are indexed based on the associated page keyword meanings; and, said text processing module searches the advertisement reference index and the web page reference index to find matches between the indexed advertisement keyword meanings and the indexed page keyword meanings. | 0.5 |
9,920,855 | 1 | 5 | 1. A system, comprising: a process line comprising a valve assembly; 4-20 analog instrumentation wiring coupled to the valve assembly to exchange signals; a computing device coupled with the 4-20 analog instrumentation wiring, the computing device generating signals to manage operation of the valve assembly; a network coupled with the computing device; and a terminal coupled with the network, the terminal having a display with a Web-based user interface, wherein the computing device comprises, a processor; a memory coupled with the processor, the memory having executable instructions stored thereon that are configured to be accessed and executed by the processor, the executable instructions comprising instructions for implementing an architecture comprising a first architecture layer and a second architecture layer, which is different from the first architecture layer, wherein the first architecture layer is configured to exchange data in a first format that allows communication between the computing device and the valve assembly, the data relating to an operating variable for the valve assembly on the process line, wherein the second architecture layer is configured to exchange data in a second format with the network, wherein the second format is different from the first format, and wherein the second format utilizes a JavaScript Object Notation (JSON) format, and wherein the data in JSON format transits the network to change the Web-based user interface on the display to correspond with real-time operation of the valve assembly. | 1. A system, comprising: a process line comprising a valve assembly; 4-20 analog instrumentation wiring coupled to the valve assembly to exchange signals; a computing device coupled with the 4-20 analog instrumentation wiring, the computing device generating signals to manage operation of the valve assembly; a network coupled with the computing device; and a terminal coupled with the network, the terminal having a display with a Web-based user interface, wherein the computing device comprises, a processor; a memory coupled with the processor, the memory having executable instructions stored thereon that are configured to be accessed and executed by the processor, the executable instructions comprising instructions for implementing an architecture comprising a first architecture layer and a second architecture layer, which is different from the first architecture layer, wherein the first architecture layer is configured to exchange data in a first format that allows communication between the computing device and the valve assembly, the data relating to an operating variable for the valve assembly on the process line, wherein the second architecture layer is configured to exchange data in a second format with the network, wherein the second format is different from the first format, and wherein the second format utilizes a JavaScript Object Notation (JSON) format, and wherein the data in JSON format transits the network to change the Web-based user interface on the display to correspond with real-time operation of the valve assembly. 5. The system of claim 1 , wherein the executable instructions comprise instructions that configure the first architecture layer to exchange data with a process server of the process component. | 0.768029 |
8,458,168 | 7 | 12 | 7. A system, for determining an intent that is related to a present intent of a user, the system comprising: at least one processor; one or more computer-storage media embedded with computer-executable instructions, the embedded computer-executable instructions are executed by the at least one processor to: receive one or more actions performed by the user, wherein the one or more actions include at least one action toward a goal; determine, for the user, a present intent, which is an object logically accomplished by performing an online action, based on the received one or more performed actions, wherein the determined present intent is one of a plurality of intents within an intent ontology that defines relationships between intents and actions, and wherein each of the plurality of intents is associated with at least one other intent through a chain of intent, wherein the chain of intent includes a chronological sequence of two or more related intents, wherein the chain of intent has a chronological relationship based on a temporal progression of intents; select a related intent that is part of a corresponding chain of intent that includes the determined present intent; and retrieve an online object that is associated with the related intent in anticipation to the related intent. | 7. A system, for determining an intent that is related to a present intent of a user, the system comprising: at least one processor; one or more computer-storage media embedded with computer-executable instructions, the embedded computer-executable instructions are executed by the at least one processor to: receive one or more actions performed by the user, wherein the one or more actions include at least one action toward a goal; determine, for the user, a present intent, which is an object logically accomplished by performing an online action, based on the received one or more performed actions, wherein the determined present intent is one of a plurality of intents within an intent ontology that defines relationships between intents and actions, and wherein each of the plurality of intents is associated with at least one other intent through a chain of intent, wherein the chain of intent includes a chronological sequence of two or more related intents, wherein the chain of intent has a chronological relationship based on a temporal progression of intents; select a related intent that is part of a corresponding chain of intent that includes the determined present intent; and retrieve an online object that is associated with the related intent in anticipation to the related intent. 12. The system of claim 7 , wherein the embedded computer-executable instructions are further executed by the at least one processor to: categorize the user into a lifestyle category based on information known about the user, wherein the lifestyle category describes a user's interests, hobbies, and activities; and wherein the online object is retrieved based on the related intent and a best match within the lifestyle category. | 0.564777 |
9,514,746 | 17 | 18 | 17. A method of mitigating hazards in a voice-driven control system for controlling a medical device in an operating room, comprising the steps of: providing a medical device; providing a database including a plurality of rules, a first one of the plurality of rules immediately stopping a system or device activity if one or more speech commands is begun within a predetermined period of time after the activity was commenced, and a second one of the plurality of rules alerting if a disconnection with a microphone is detected; receiving an audio input including the one or more speech commands; identifying at least one event of the audio input; determining a system status including actions currently being performed by devices; determining whether hazard mitigation is necessary based on a comparison of the at least one event, the system status, and at least one rule; and if having determined that hazard mitigation is necessary, sending a control command to the medical device in communication with the voice-driven control system instructing it to perform an action. | 17. A method of mitigating hazards in a voice-driven control system for controlling a medical device in an operating room, comprising the steps of: providing a medical device; providing a database including a plurality of rules, a first one of the plurality of rules immediately stopping a system or device activity if one or more speech commands is begun within a predetermined period of time after the activity was commenced, and a second one of the plurality of rules alerting if a disconnection with a microphone is detected; receiving an audio input including the one or more speech commands; identifying at least one event of the audio input; determining a system status including actions currently being performed by devices; determining whether hazard mitigation is necessary based on a comparison of the at least one event, the system status, and at least one rule; and if having determined that hazard mitigation is necessary, sending a control command to the medical device in communication with the voice-driven control system instructing it to perform an action. 18. The method of claim 17 , wherein the control command countermands a speech command to the medical device. | 0.717617 |
8,347,405 | 1 | 6 | 1. An apparatus for Asynchronous Java Script and XML (AJAX) form-based authentication using Java 2 Platform Enterprise Edition, the apparatus comprising: a server having a processor coupled to a memory, wherein the processor is programmed to perform authentication by executing computer code implementing: a redirection module configured to: detect whether an AJAX request received from an AJAX-enabled application on a client requires access to data marked as secure; and redirect the AJAX request to an authentication required servlet in response to detecting that the AJAX request requires access to data marked as secure; a response module configured to issue an AJAX response to the AJAX-enabled application on the client if the AJAX request is redirected to the authentication required servlet, the AJAX response, independently of a server-side security credential form, directing the AJAX-enabled application on the client to obtain user security credentials and to return the obtained security credentials to the server; an authentication module configured to authenticate the user security credentials using a web container authentication service, the user security credentials received by way of an AJAX form-based authentication request such that the authentication module simulates a conventional form submission without actually using a form on the server-side; and a processing module configured to process the AJAX request in response to a positive authentication of the user security credentials. | 1. An apparatus for Asynchronous Java Script and XML (AJAX) form-based authentication using Java 2 Platform Enterprise Edition, the apparatus comprising: a server having a processor coupled to a memory, wherein the processor is programmed to perform authentication by executing computer code implementing: a redirection module configured to: detect whether an AJAX request received from an AJAX-enabled application on a client requires access to data marked as secure; and redirect the AJAX request to an authentication required servlet in response to detecting that the AJAX request requires access to data marked as secure; a response module configured to issue an AJAX response to the AJAX-enabled application on the client if the AJAX request is redirected to the authentication required servlet, the AJAX response, independently of a server-side security credential form, directing the AJAX-enabled application on the client to obtain user security credentials and to return the obtained security credentials to the server; an authentication module configured to authenticate the user security credentials using a web container authentication service, the user security credentials received by way of an AJAX form-based authentication request such that the authentication module simulates a conventional form submission without actually using a form on the server-side; and a processing module configured to process the AJAX request in response to a positive authentication of the user security credentials. 6. The apparatus of claim 1 , wherein the processing module is further configured to pass the authentication result to an authentication failed servlet in response to a rejection of the user security credentials, and wherein the authentication failed servlet returns a Java Script Object Notation (JSON) object configured to indicate that authentication has failed. | 0.550493 |
9,891,792 | 1 | 2 | 1. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring a user's interaction with the interactive software system and obtaining user interaction activity data indicating the user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the user at defined times as the user interacts with the interactive software system; correlating the biometric data associated with the user with the user's interaction activity data at the defined times; obtaining baseline data associated with the user, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the user and correlated to the user's interaction activity data and the baseline data associated with the user, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with the user; based, at least in part, on the emotional pattern predictive model associated with the user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the user; and presenting the customized interactive software system user experience to the user. | 1. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring a user's interaction with the interactive software system and obtaining user interaction activity data indicating the user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the user at defined times as the user interacts with the interactive software system; correlating the biometric data associated with the user with the user's interaction activity data at the defined times; obtaining baseline data associated with the user, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the user and correlated to the user's interaction activity data and the baseline data associated with the user, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with the user; based, at least in part, on the emotional pattern predictive model associated with the user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the user; and presenting the customized interactive software system user experience to the user. 2. The method for building and utilizing interactive software system predictive models using biometric data of claim 1 , wherein the interactive software system is selected from the group of interactive software systems consisting of: a computing system implemented tax preparation software system; a network accessed tax preparation software system; a web-based tax preparation software system; a cloud-based tax preparation software system; a computing system implemented business management software system; a network accessed business management software system; a web-based business management software system; a cloud-based business management software system; a computing system implemented accounting software system; a network accessed accounting software system; a web-based accounting software system; a cloud-based accounting software system; a computing system implemented financial management system; a network accessed financial management system; a web-based financial management system; and a cloud-based financial management system. | 0.65798 |
10,055,487 | 16 | 17 | 16. A censorship system comprising: one or more processors programmed to: receive, from a censorship device, data generated by an individual person that is within a field-of-censorship; generate historical information regarding a history of an object indicated by text data based on the received individual person generated data; extract historical text data that satisfies a predetermined historical condition regarding the generated historical information; generate a number of references in connection with a user ID that identifies the individual person who has generated the individual person generated data, the number of references indicating a number of times the text data is at least one of: re-posted, re-tweeted or referred to in an email chain; extract particular text data that satisfies a predetermined reference condition, based on the number of references, out of the historical text data; transmit, to the censorship device, the particular text data thereby making the particular text data available to the censorship system; and generate a censorship control command as a specific executable command for the individual person based on the related text data, wherein the censorship control command causes blocking of information containing the particular text data. | 16. A censorship system comprising: one or more processors programmed to: receive, from a censorship device, data generated by an individual person that is within a field-of-censorship; generate historical information regarding a history of an object indicated by text data based on the received individual person generated data; extract historical text data that satisfies a predetermined historical condition regarding the generated historical information; generate a number of references in connection with a user ID that identifies the individual person who has generated the individual person generated data, the number of references indicating a number of times the text data is at least one of: re-posted, re-tweeted or referred to in an email chain; extract particular text data that satisfies a predetermined reference condition, based on the number of references, out of the historical text data; transmit, to the censorship device, the particular text data thereby making the particular text data available to the censorship system; and generate a censorship control command as a specific executable command for the individual person based on the related text data, wherein the censorship control command causes blocking of information containing the particular text data. 17. The censorship system of claim 16 , wherein the one or more processors are further programmed to: generate monitoring information based on the historical text data. | 0.642553 |
7,805,710 | 1 | 18 | 1. A method of translating a subject code executable by a subject computing architecture into a target code executable by a second computing architecture, wherein the subject code includes at least a first program and a second program, comprising: providing a first translator instance which translates the subject code of the first program into the target code including translating a first portion of the subject code into a portion of the target code; caching said portion of the target code into a shared code cache facility; providing a second translator instance which is different from the first translator instance and which translates the subject code of the second program into the target code, wherein the second translator instance operates simultaneously with the first translator instance; retrieving the cached portion of the target code from the shared code cache facility upon a compatibility detection between said cached portion of the target code and a second portion of the subject code in the second program, including loading the portion of the target code in the shared code cache facility into a portion of memory which is shared amongst at least the first and second translator instances; and, copying at least one part of the shared code cache facility to a private portion of memory associated with the second translator instance upon modification of the at least one part of the shared code cache facility by the second translator instance. | 1. A method of translating a subject code executable by a subject computing architecture into a target code executable by a second computing architecture, wherein the subject code includes at least a first program and a second program, comprising: providing a first translator instance which translates the subject code of the first program into the target code including translating a first portion of the subject code into a portion of the target code; caching said portion of the target code into a shared code cache facility; providing a second translator instance which is different from the first translator instance and which translates the subject code of the second program into the target code, wherein the second translator instance operates simultaneously with the first translator instance; retrieving the cached portion of the target code from the shared code cache facility upon a compatibility detection between said cached portion of the target code and a second portion of the subject code in the second program, including loading the portion of the target code in the shared code cache facility into a portion of memory which is shared amongst at least the first and second translator instances; and, copying at least one part of the shared code cache facility to a private portion of memory associated with the second translator instance upon modification of the at least one part of the shared code cache facility by the second translator instance. 18. The method of claim 1 , wherein the first translator instance translates the first subject program including the first portion of the subject code into the portion of the target code, and the second translator instance translates the second subject program including reusing the portion of the target code created by the first translator instance. | 0.5 |
5,572,668 | 8 | 9 | 8. The method as defined by claim 7, wherein if said script interpreter is unable to accommodate multibyte characters, upon detecting said flag, each of said encapsulated strings of ASCII characters representing said predefined characters represented by multiple bytes is provided to a UNLS interpreter. | 8. The method as defined by claim 7, wherein if said script interpreter is unable to accommodate multibyte characters, upon detecting said flag, each of said encapsulated strings of ASCII characters representing said predefined characters represented by multiple bytes is provided to a UNLS interpreter. 9. The method as defined by claim 8, wherein said script interpreter provides said string of ASCII characters requiring multiple bytes to said UNLS interpreter, said UNLS interpreter including input method editor means for generating said predefined characters in said target language from said ASCII characters requiring multiple bytes and providing said generated predefined characters in said target language to said computer program for execution in conjunction with said translated test commands. | 0.5 |
7,720,789 | 7 | 9 | 7. A computer-readable storage medium encoded with executable instructions for causing a programmable processor to: select a MUN transformation, wherein the instructions to select the MUN transformation comprise instructions to: receive a source report dimensional member reference and a target report dimensional member reference; and select the MUN transformation based upon: a source model type associated with the source dimensional member reference; and a target model type associated with the target dimensional member reference; and transform a MUN of a first data source into a MUN of a second data source, the instructions to transform comprising at least one of: instructions to transform a first OLAP MUN to a second OLAP MUN, the first OLAP MUN and second OLAP MUN being of different source technologies; or instructions to transform a DMR MUN to an OLAP MUN. | 7. A computer-readable storage medium encoded with executable instructions for causing a programmable processor to: select a MUN transformation, wherein the instructions to select the MUN transformation comprise instructions to: receive a source report dimensional member reference and a target report dimensional member reference; and select the MUN transformation based upon: a source model type associated with the source dimensional member reference; and a target model type associated with the target dimensional member reference; and transform a MUN of a first data source into a MUN of a second data source, the instructions to transform comprising at least one of: instructions to transform a first OLAP MUN to a second OLAP MUN, the first OLAP MUN and second OLAP MUN being of different source technologies; or instructions to transform a DMR MUN to an OLAP MUN. 9. The computer-readable storage medium of claim 7 , wherein the collection of MUN transformations comprises one or more of instructions to: transform a first dimensionally modeled relational (DMR) MUN to a second DMR MUN; transform a third OLAP MUN to a fourth OLAP MUN, the third OLAP MUN and fourth OLAP MUN being of the same source technology; transform an OLAP MUN to a DMR MUN; transform a DMR MUN into a MUN containing a dimensional reference and a canonical business key; and transform an OLAP MUN into a MUN containing a dimensional reference and a canonical business key. | 0.759321 |
7,676,589 | 13 | 17 | 13. A computer readable storage, having stored thereon a computer program having a plurality of code sections, that, when executed by a computer, cause the computer to perform a plurality of steps, the computer readable storage comprising: code for identifying a location of structured data described by a data model specification; code for automatically determining, by a computer, from the data model specification, relationships between a plurality of objects within the structured data, wherein the data model specification is automatically introspected to identify primary keys associated with each of the plurality of objects and foreign key relationships between the plurality of objects; code for automatically generating a plurality of portlets, wherein at least one portlet is automatically generated for each object of the plurality of objects according to the relationships specified within the data model specification, wherein at least one function, for querying the structured data, of each portlet is automatically determined by a foreign key relationship of the object associated with each portlet, and wherein automatically creating a plurality of portlets further comprises generating code in at least a first portlet of the plurality of portlets that triggers the action in at least a second portlet of the plurality of portlets according to the relationships specified within the data model specification; and code for automatically creating at least one communication link between at least two of the plurality of portlets according to the relationships specified within the data model specification, wherein over the communication link the first portlet of the at least two portlets triggers an action within the second portlet of the at least two portlets, and responsive to that action, the second portlet sends data to the first portlet, wherein at least one of the first portlet or the second portlet is displayed within a portal page. | 13. A computer readable storage, having stored thereon a computer program having a plurality of code sections, that, when executed by a computer, cause the computer to perform a plurality of steps, the computer readable storage comprising: code for identifying a location of structured data described by a data model specification; code for automatically determining, by a computer, from the data model specification, relationships between a plurality of objects within the structured data, wherein the data model specification is automatically introspected to identify primary keys associated with each of the plurality of objects and foreign key relationships between the plurality of objects; code for automatically generating a plurality of portlets, wherein at least one portlet is automatically generated for each object of the plurality of objects according to the relationships specified within the data model specification, wherein at least one function, for querying the structured data, of each portlet is automatically determined by a foreign key relationship of the object associated with each portlet, and wherein automatically creating a plurality of portlets further comprises generating code in at least a first portlet of the plurality of portlets that triggers the action in at least a second portlet of the plurality of portlets according to the relationships specified within the data model specification; and code for automatically creating at least one communication link between at least two of the plurality of portlets according to the relationships specified within the data model specification, wherein over the communication link the first portlet of the at least two portlets triggers an action within the second portlet of the at least two portlets, and responsive to that action, the second portlet sends data to the first portlet, wherein at least one of the first portlet or the second portlet is displayed within a portal page. 17. The computer readable storage of claim 13 , further comprising code for configuring the first portlet to pass an object to the second portlet. | 0.775385 |
8,812,494 | 3 | 4 | 3. The method of claim 1 , wherein the step of identifying further comprises: determining an initial membership for the clusters from the input data set; obtaining a probability function based on the initial membership; and defining the clusters to include the delivered invitational content and the known contexts within a distance based on moments of the obtained probability function. | 3. The method of claim 1 , wherein the step of identifying further comprises: determining an initial membership for the clusters from the input data set; obtaining a probability function based on the initial membership; and defining the clusters to include the delivered invitational content and the known contexts within a distance based on moments of the obtained probability function. 4. The method of claim 3 , wherein the step of generating the first and second rank values comprises: computing the first and second rank values for each of the clusters based on the moments of the obtained probability function. | 0.5 |
7,818,174 | 1 | 3 | 1. An apparatus comprising: an input that receives indicia of a grammar; an output that provides a recognition parameter associated with said grammar; a processor coupled to said input and to said output and a computer-readable medium including computer executable instructions that, when executed by said processor, cause said processor to: analyze said grammar to determine a perplexity and word length associated with said grammar; determine a category of said grammar based on said perplexity and word length; determine said recognition parameter based on said category; and provide indicia of said recognition parameter to said output. | 1. An apparatus comprising: an input that receives indicia of a grammar; an output that provides a recognition parameter associated with said grammar; a processor coupled to said input and to said output and a computer-readable medium including computer executable instructions that, when executed by said processor, cause said processor to: analyze said grammar to determine a perplexity and word length associated with said grammar; determine a category of said grammar based on said perplexity and word length; determine said recognition parameter based on said category; and provide indicia of said recognition parameter to said output. 3. The apparatus of claim 1 , wherein said input is coupled to a packet-switched communication network, and said output communicates with a speech recognizer. | 0.712727 |
8,713,433 | 1 | 10 | 1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of keys; receiving, by the computing device and from an input device, an indication of a selection of one or more of the plurality of keys; determining, by the computing device and based at least in part on the indication of the selection, a character string; determining, by the computing device and based at least in part on the character string, a plurality of candidate words; determining, by the computing device, and based at least in part on the plurality of candidate words and a plurality of features, a spelling probability that the character string comprises an incorrect spelling of at least one of the plurality of candidate words, the plurality of features comprising at least a spatial model probability associated with at least one of the one or more candidate words; and responsive to determining that the spelling probability satisfies a threshold, outputting, by the computing device, for display at the display device, the at least one of the plurality of candidate words. | 1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of keys; receiving, by the computing device and from an input device, an indication of a selection of one or more of the plurality of keys; determining, by the computing device and based at least in part on the indication of the selection, a character string; determining, by the computing device and based at least in part on the character string, a plurality of candidate words; determining, by the computing device, and based at least in part on the plurality of candidate words and a plurality of features, a spelling probability that the character string comprises an incorrect spelling of at least one of the plurality of candidate words, the plurality of features comprising at least a spatial model probability associated with at least one of the one or more candidate words; and responsive to determining that the spelling probability satisfies a threshold, outputting, by the computing device, for display at the display device, the at least one of the plurality of candidate words. 10. The method of claim 1 , wherein the indication of the selection comprises at least one input location of the input device, the method further comprising: determining, by the computing device, a Euclidian distance associated with the at least one input location and a key location of at least one of the plurality of keys; and determining, by the computing device and based on the Euclidian distance, the spatial model probability associated with at least one of the candidate words. | 0.779492 |
9,164,667 | 11 | 17 | 11. A system for displaying an n-dimensional textual data set as a word cloud comprising one electronic device, or a set of two or more electronic devices linked by a network, coupled to a display and to data entry means including manual data entry means, each electronic device having a memory, and a processor, said processors together or singly operable to execute instructions to perform functions comprising: a Processing Component configured to: generate a textual data set whose members comprise a set of words, each of which is associated with an n-dimensional vector populated by n numerical values, said vectors defining an n-dimensional data space; calculate a size attribute for each word in said textual data set; create an initial two-dimensional subspace of the n-dimensional data space; calculate the projection of each said n-dimensional vector onto said subspace; and derive a new subspace and vector projections thereon given a user-selected vector in said n-dimensional vector space and a variable representing change in position within a display space; a Display Component configured to display word clouds in a display space with a two dimensional coordinate system, and specifically to perform steps comprising displaying a word cloud given a set of n-dimensional vectors with calculated projections and corresponding words with calculated size attributes by: placing each word at coordinates determined by its vector's projection; and displaying said word with a font size corresponding to its size attribute; a Data Entry Component configured to capture data entered by the user via said data entry means, and particularly to: capture a selection of a word displayed in said word cloud by a user via said manual data entry means, and record the selection of that word's corresponding n-dimensional vector; capture a user motion input by: selecting a frame rate for animating the movement corresponding to said user's motion input; for each frame, calculating the change in position corresponding to the portion of said user's motion input that occurred during said frame; and repeating for each frame until the cessation of said motion input; and identifying the cessation of the motion input; a Data Storage Component configured to store said textual data set in said memory so as to preserve each word's relationship with its associated vector; store said subspace in said memory; and store each vector's projection in said memory. | 11. A system for displaying an n-dimensional textual data set as a word cloud comprising one electronic device, or a set of two or more electronic devices linked by a network, coupled to a display and to data entry means including manual data entry means, each electronic device having a memory, and a processor, said processors together or singly operable to execute instructions to perform functions comprising: a Processing Component configured to: generate a textual data set whose members comprise a set of words, each of which is associated with an n-dimensional vector populated by n numerical values, said vectors defining an n-dimensional data space; calculate a size attribute for each word in said textual data set; create an initial two-dimensional subspace of the n-dimensional data space; calculate the projection of each said n-dimensional vector onto said subspace; and derive a new subspace and vector projections thereon given a user-selected vector in said n-dimensional vector space and a variable representing change in position within a display space; a Display Component configured to display word clouds in a display space with a two dimensional coordinate system, and specifically to perform steps comprising displaying a word cloud given a set of n-dimensional vectors with calculated projections and corresponding words with calculated size attributes by: placing each word at coordinates determined by its vector's projection; and displaying said word with a font size corresponding to its size attribute; a Data Entry Component configured to capture data entered by the user via said data entry means, and particularly to: capture a selection of a word displayed in said word cloud by a user via said manual data entry means, and record the selection of that word's corresponding n-dimensional vector; capture a user motion input by: selecting a frame rate for animating the movement corresponding to said user's motion input; for each frame, calculating the change in position corresponding to the portion of said user's motion input that occurred during said frame; and repeating for each frame until the cessation of said motion input; and identifying the cessation of the motion input; a Data Storage Component configured to store said textual data set in said memory so as to preserve each word's relationship with its associated vector; store said subspace in said memory; and store each vector's projection in said memory. 17. A system according to claim 11 , wherein said Processing Component is configured to calculate a metric for degree of relatedness between two words and wherein said Display Component is configured to display said selected word in a color that contrasts with the default display color and to display all other words with coloration indicating the degree of relatedness between each word and the selected word. | 0.61803 |
9,234,765 | 1 | 13 | 1. A computer-implemented method, comprising: identifying a starting point and a destination point for travel by a user including any constraints of the user regarding the travel; determining one or more initial routes between the starting point and the destination point; for each initial route, segmenting the route into a plurality of segments based on one or more criteria; and determining attribute oriented routes using the segments including: determining one or more entities associated with each segment; identifying attributes for each determined entity; aggregating and ranking the attributes along all the determined initial routes and determining one or more emerging attributes; determining one or more attribute oriented routes based on the emerging attributes including identifying a theme for an attribute oriented route based on one or more of the emerging attributes, identifying a set of entities from the determined entities that are associated with the one or more emerging attributes, and creating the attribute oriented route that passes through a region that includes the set of entities, wherein determining one or more attribute oriented routes includes scoring a particular region based on matching emerging attributes of the particular region compared to one or more goals and determining routes that maximize an aggregate rank based on the scoring under the constraints; and providing at least one attribute oriented route and information related to the theme to a device associated with the user. | 1. A computer-implemented method, comprising: identifying a starting point and a destination point for travel by a user including any constraints of the user regarding the travel; determining one or more initial routes between the starting point and the destination point; for each initial route, segmenting the route into a plurality of segments based on one or more criteria; and determining attribute oriented routes using the segments including: determining one or more entities associated with each segment; identifying attributes for each determined entity; aggregating and ranking the attributes along all the determined initial routes and determining one or more emerging attributes; determining one or more attribute oriented routes based on the emerging attributes including identifying a theme for an attribute oriented route based on one or more of the emerging attributes, identifying a set of entities from the determined entities that are associated with the one or more emerging attributes, and creating the attribute oriented route that passes through a region that includes the set of entities, wherein determining one or more attribute oriented routes includes scoring a particular region based on matching emerging attributes of the particular region compared to one or more goals and determining routes that maximize an aggregate rank based on the scoring under the constraints; and providing at least one attribute oriented route and information related to the theme to a device associated with the user. 13. The method of claim 1 further comprising optimizing routes in, or eliminating routes from, the one or more attributed oriented routes based on the constraints provided by the user. | 0.800866 |
8,332,907 | 15 | 16 | 15. The system of claim 12 , said file scanner further adapted to: generate a report based on said scanning. | 15. The system of claim 12 , said file scanner further adapted to: generate a report based on said scanning. 16. The system of claim 15 further comprising: a report database adapted to store said report. | 0.5 |
8,041,555 | 10 | 11 | 10. An information processing system for translating text within an image captured by a wireless device, the information processing system comprising: a memory; a processor communicatively coupled to the memory; a translation manager communicatively coupled to the memory and the processor, wherein the translation manager is configured to perform a method comprising: receiving at least one image from a wireless device; determining a location where the image was captured by the wireless device; identifying a set of text characters within the image; determining a language associated with the set of text characters based on at least the location that has been determined; determining a language context associated with the location that has been determined; identifying at least one word within a language dictionary associated with the language context; generating a prioritized language dictionary based on the at least one location and the language context that has been determined, wherein the generating comprises assigning a higher priority to the word associated with the language context than words in the language dictionary associated with other language contexts; and translating the set of text characters into a language that is different than language that has been determined based on the prioritized language dictionary that has been generated, wherein the word that has been assigned a higher priority is selected from the prioritized language dictionary to translate the set of text characters over other words in the prioritized language dictionary that have been assigned a lower priority. | 10. An information processing system for translating text within an image captured by a wireless device, the information processing system comprising: a memory; a processor communicatively coupled to the memory; a translation manager communicatively coupled to the memory and the processor, wherein the translation manager is configured to perform a method comprising: receiving at least one image from a wireless device; determining a location where the image was captured by the wireless device; identifying a set of text characters within the image; determining a language associated with the set of text characters based on at least the location that has been determined; determining a language context associated with the location that has been determined; identifying at least one word within a language dictionary associated with the language context; generating a prioritized language dictionary based on the at least one location and the language context that has been determined, wherein the generating comprises assigning a higher priority to the word associated with the language context than words in the language dictionary associated with other language contexts; and translating the set of text characters into a language that is different than language that has been determined based on the prioritized language dictionary that has been generated, wherein the word that has been assigned a higher priority is selected from the prioritized language dictionary to translate the set of text characters over other words in the prioritized language dictionary that have been assigned a lower priority. 11. The information processing system of claim 10 , wherein the translation manager is further adapted to: send the set of characters that have been translated to the wireless device. | 0.713166 |
8,504,909 | 6 | 9 | 6. A computer-implemented method comprising: receiving document markup associated with a document; ascertaining, from the document markup, whether an object of interest is encountered in the document markup; for objects of interest that are encountered, making an entry in a resource dictionary, and inserting a resource key associated with the objects of interest in an object model associated with the document, the making an entry comprising modifying a reference count, in the resource dictionary, for objects that reoccur in the document markup; determining objects that do not reoccur in the document markup based on the reference count; removing, from the resource dictionary, one or more entries associated with the objects that do not reoccur in the document markup; and inserting an associated object in the object model in place of an associated resource key for the objects that do not reoccur in the document. | 6. A computer-implemented method comprising: receiving document markup associated with a document; ascertaining, from the document markup, whether an object of interest is encountered in the document markup; for objects of interest that are encountered, making an entry in a resource dictionary, and inserting a resource key associated with the objects of interest in an object model associated with the document, the making an entry comprising modifying a reference count, in the resource dictionary, for objects that reoccur in the document markup; determining objects that do not reoccur in the document markup based on the reference count; removing, from the resource dictionary, one or more entries associated with the objects that do not reoccur in the document markup; and inserting an associated object in the object model in place of an associated resource key for the objects that do not reoccur in the document. 9. The method of claim 6 , wherein said objects of interest comprise SolidColorBrush objects and PathGeometry objects. | 0.5 |
9,633,115 | 1 | 5 | 1. A system for analyzing a query and provisioning data to analytics, the system comprising: a user interface to display a set of selectable terms from a glossary of business terms and to generate, in response to a selection of a subset of the set of selectable terms, a business metadata query that identifies at least one forum with a plurality of member profiles; a generator to generate at least one module from the business metadata query that identifies the at least one forum and an analytical processing environment; a computing platform to deploy the at least one module to move data from the at least one forum into the analytical processing environment and perform, using the analytical processing environment, analytical operations on the data from the at least one forum; and a business extender to: identify metadata from a result of the analytical operations, and update the glossary of business terms using the identified metadata. | 1. A system for analyzing a query and provisioning data to analytics, the system comprising: a user interface to display a set of selectable terms from a glossary of business terms and to generate, in response to a selection of a subset of the set of selectable terms, a business metadata query that identifies at least one forum with a plurality of member profiles; a generator to generate at least one module from the business metadata query that identifies the at least one forum and an analytical processing environment; a computing platform to deploy the at least one module to move data from the at least one forum into the analytical processing environment and perform, using the analytical processing environment, analytical operations on the data from the at least one forum; and a business extender to: identify metadata from a result of the analytical operations, and update the glossary of business terms using the identified metadata. 5. The system of claim 1 , wherein the computing platform is further executes operations to: receive results in response to the performance of the analytical operations on the data; and send the results to an analytical user interface. | 0.682432 |
7,606,425 | 20 | 29 | 20. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence, the behavioral analysis engine including an actor feature database, a frame feature database, and a programmable event library stored in a memory; initiate a training phase mode within the behavioral analysis engine and obtaining a feature vector including one or more parameters relating to an object disposed within the image sequence; analyze the feature vector to determine a number of possible event candidates; prompt a user to confirm whether a detected event candidate is a newly identified event; and store the new event within the event library if the detected event candidate is confirmed by the user. | 20. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence, the behavioral analysis engine including an actor feature database, a frame feature database, and a programmable event library stored in a memory; initiate a training phase mode within the behavioral analysis engine and obtaining a feature vector including one or more parameters relating to an object disposed within the image sequence; analyze the feature vector to determine a number of possible event candidates; prompt a user to confirm whether a detected event candidate is a newly identified event; and store the new event within the event library if the detected event candidate is confirmed by the user. 29. The method of claim 20 , wherein the computing system is further programmed to apply a time-consistency filtering routine to the image seguence prior to said step of analyzing the feature vector to determine a number of possible event candidates. | 0.5 |
9,037,473 | 13 | 16 | 13. A non-transitory computer-readable medium having stored thereon a computer-executable component configured to execute in one or more processors of an electronic communication device, the computer-executable component being further configured to: determine that a first physical phenomenon related to the electronic communication device has occurred; trigger recording of audio data in response to determining that the first physical phenomenon has occurred; provide the audio data to a speech recognition engine; after determining that the first physical phenomenon related to the electronic communication device has occurred, determine that a second physical phenomenon related to the electronic communication device has occurred; and stop recording the audio data comprising speech in response to determining that the second physical phenomenon related to the electronic communication device has occurred. | 13. A non-transitory computer-readable medium having stored thereon a computer-executable component configured to execute in one or more processors of an electronic communication device, the computer-executable component being further configured to: determine that a first physical phenomenon related to the electronic communication device has occurred; trigger recording of audio data in response to determining that the first physical phenomenon has occurred; provide the audio data to a speech recognition engine; after determining that the first physical phenomenon related to the electronic communication device has occurred, determine that a second physical phenomenon related to the electronic communication device has occurred; and stop recording the audio data comprising speech in response to determining that the second physical phenomenon related to the electronic communication device has occurred. 16. The non-transitory computer-readable medium of claim 13 , wherein the computer-executable component is further configured to: obtain speech recognition results corresponding to the audio data; and cause the electronic communication device to present the speech recognition results. | 0.5 |
8,832,151 | 9 | 15 | 9. A computer-accessible, non-transitory storage medium encoded with computer-readable instructions configured to cause one or more data processing apparatus to: establish a relationship between a partner and a hosted server system based on a received request from the partner; receive a request from a partner administrator to customize a container document to provide to a partner end user, the container document including a first level of content and configurations selected by the partner administrator; receive an identification of the partner end user with access to the container document from the partner administrator; serve a customized container document to the partner end user; and receive a request from the partner end user to customize the container document. | 9. A computer-accessible, non-transitory storage medium encoded with computer-readable instructions configured to cause one or more data processing apparatus to: establish a relationship between a partner and a hosted server system based on a received request from the partner; receive a request from a partner administrator to customize a container document to provide to a partner end user, the container document including a first level of content and configurations selected by the partner administrator; receive an identification of the partner end user with access to the container document from the partner administrator; serve a customized container document to the partner end user; and receive a request from the partner end user to customize the container document. 15. The medium of claim 9 , wherein the customized container document served to the partner end user includes a first level of content and configurations. | 0.752412 |
10,115,116 | 1 | 4 | 1. A system for optimizing computer-based crowd-sourced polling, comprising: a processor; and a memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising: receiving an input query representing a crowd-sourced poll comprising two or more branches, each branch associated with a corresponding set of worker qualifications, the query being formatted as a multi-layer structure; iteratively reducing the multi-layer structure of the input query to construct a reformulated query, the reformulated query having a reduced complexity relative to the input query; reducing one or more of expected completion time and expected cost associated with the reformulated query by matching the reformulated query to an optimized execution process selected from a plurality of predefined execution processes; presenting the reformulated query and matching optimized execution process as an optimized version of the crowd-sourced poll for execution via a computer-based crowd-sourcing backend; during execution of the optimized version of the crowd-sourced poll, improving poll efficiency by automatically changing the matching optimized execution process to another of the predefined execution processes and dynamically changing the reformulated query to correspond to the automatically changed execution process in response to collected runtime statistics relating to execution of the optimized version of the crowd-sourced poll; and further during execution, presenting the changed reformulated query and changed matching optimized execution process for continued execution via the computer-based crowd-sourcing backend. | 1. A system for optimizing computer-based crowd-sourced polling, comprising: a processor; and a memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising: receiving an input query representing a crowd-sourced poll comprising two or more branches, each branch associated with a corresponding set of worker qualifications, the query being formatted as a multi-layer structure; iteratively reducing the multi-layer structure of the input query to construct a reformulated query, the reformulated query having a reduced complexity relative to the input query; reducing one or more of expected completion time and expected cost associated with the reformulated query by matching the reformulated query to an optimized execution process selected from a plurality of predefined execution processes; presenting the reformulated query and matching optimized execution process as an optimized version of the crowd-sourced poll for execution via a computer-based crowd-sourcing backend; during execution of the optimized version of the crowd-sourced poll, improving poll efficiency by automatically changing the matching optimized execution process to another of the predefined execution processes and dynamically changing the reformulated query to correspond to the automatically changed execution process in response to collected runtime statistics relating to execution of the optimized version of the crowd-sourced poll; and further during execution, presenting the changed reformulated query and changed matching optimized execution process for continued execution via the computer-based crowd-sourcing backend. 4. The system of claim 1 wherein iteratively reducing the multi-layer structure of the input query further comprises: identifying common subexpressions in the input query; and merging common subexpressions so that expressions in the input query reference merged subexpressions in place of the common subexpressions. | 0.732598 |
7,822,734 | 1 | 6 | 1. A method comprising: a search engine receiving one or more distinct taxonomies and an environment identifier from an administrator of an environment; storing taxonomies received from a plurality of environments, wherein each taxonomy of the one or more distinct taxonomies is stored in association with the environment identifier; wherein said each taxonomy specifies categories and relationships between the categories; receiving a search query; determining a particular environment identifier of a particular environment that is associated with the search query; selecting one of a plurality of taxonomies stored in association with the particular environment identifier; generating a search engine results page, at least in part, by applying to a search engine result item a set of rules that are associated with the selected taxonomy; wherein applying the set of rules to a search engine result item identifies a set of categories in the selected taxonomy to display on the search engine results page in association with the search engine result item; wherein the method is performed by a computer programmed to be a special purpose machine pursuant to instructions from program software. | 1. A method comprising: a search engine receiving one or more distinct taxonomies and an environment identifier from an administrator of an environment; storing taxonomies received from a plurality of environments, wherein each taxonomy of the one or more distinct taxonomies is stored in association with the environment identifier; wherein said each taxonomy specifies categories and relationships between the categories; receiving a search query; determining a particular environment identifier of a particular environment that is associated with the search query; selecting one of a plurality of taxonomies stored in association with the particular environment identifier; generating a search engine results page, at least in part, by applying to a search engine result item a set of rules that are associated with the selected taxonomy; wherein applying the set of rules to a search engine result item identifies a set of categories in the selected taxonomy to display on the search engine results page in association with the search engine result item; wherein the method is performed by a computer programmed to be a special purpose machine pursuant to instructions from program software. 6. The method of claim 1 , wherein generating the search engine results page comprises accessing a table that stores associations between documents and categories in the selected taxonomy. | 0.876478 |
9,280,969 | 4 | 8 | 4. A computer-readable hardware medium storing computer-executable program instructions that when executed cause a computing system to: compute a frame posterior for each word in an utterance from a corpus comprising audio data and a corresponding transcription that contains transcription errors, wherein the instructions to compute the frame posterior include instructions that when executed cause the computing system to: decode the audio data using an existing acoustic model to generate a lattice, merging the decoded lattice with the transcription, labeling each word in the merged lattice as one of correct or incorrect by examining a percentage to which the word is overlapped in duration with the transcription, computing a posterior probability for each word in the merged lattice, and computing the frame posterior q(t) of time t by summing the posterior probabilities of all the correct words passing time t for a time interval; train an acoustic model with confidence-based maximum likelihood estimation (MLE) training using the frame posterior by estimating acoustic model parameters using the transcription, the audio data and the frame posterior; estimate the acoustic model parameters with confidence-based discriminative training using the frame posterior; evaluate the accuracy of the acoustic model built from the corpus including the corresponding transcription that contains transcription errors compared to the accuracy of an acoustic model built from a similar amount of training data having no transcription errors; and generate a finalized acoustic model. | 4. A computer-readable hardware medium storing computer-executable program instructions that when executed cause a computing system to: compute a frame posterior for each word in an utterance from a corpus comprising audio data and a corresponding transcription that contains transcription errors, wherein the instructions to compute the frame posterior include instructions that when executed cause the computing system to: decode the audio data using an existing acoustic model to generate a lattice, merging the decoded lattice with the transcription, labeling each word in the merged lattice as one of correct or incorrect by examining a percentage to which the word is overlapped in duration with the transcription, computing a posterior probability for each word in the merged lattice, and computing the frame posterior q(t) of time t by summing the posterior probabilities of all the correct words passing time t for a time interval; train an acoustic model with confidence-based maximum likelihood estimation (MLE) training using the frame posterior by estimating acoustic model parameters using the transcription, the audio data and the frame posterior; estimate the acoustic model parameters with confidence-based discriminative training using the frame posterior; evaluate the accuracy of the acoustic model built from the corpus including the corresponding transcription that contains transcription errors compared to the accuracy of an acoustic model built from a similar amount of training data having no transcription errors; and generate a finalized acoustic model. 8. The computer-readable hardware medium of claim 4 , wherein the instructions to estimate acoustic model parameters with confidence-based discriminative training include instructions that when executed cause the computing system to: estimate model parameters by separating statistics for a numerator lattice corresponding to the original transcription from the statistics of a decoding lattice generated by decoding the audio data with an existing acoustic model to generate the decoding lattice. | 0.552252 |
6,088,708 | 35 | 36 | 35. A computer system for creating a table from a layout of a plurality of objects, comprising: a processor; an input device coupled to the processor; a pixel-based display device coupled to the processor; a memory storage device coupled to the processor for maintaining the table data structure; and the processor being operative to: (a) identify each of the objects relative to their location on a pagedisplayed on the pixel-based display device, (b) create at least one overlap group of the objects based upon the location of the objects, each overlap group containing at least one object and any other object that overlaps the at least one object, wherein if a first object and a second object overlap each other, an overlap group containing the first object and the second object is created, (c) bound each overlap group within one of a plurality of non-overlapping rectangles, each non-overlapping rectangle defined by its bounding coordinates, each non-overlapping rectangle bounding an area of the page called an overlap region containing at least one object, (d) store the bounding coordinates of each non-overlapping rectangle within the table data structure as a plurality of x-coordinates and a plurality of y-coordinates, (e) sort the x-coordinates into ascending order and delete duplicate x-coordinates from the table data structure maintained on the memory storage device, (g) sort the y-coordinates into ascending order and delete duplicate y-coordinates from the table data structure maintained on the memory storage device, (h) create a framework of cells defining the table from the coordinates, the framework defined by rows and columns, each row defined by the y-coordinates, each column defined by the x-coordinates, the intersection of each row and each column defining the location of each cell within the table, (i) if one of the cells corresponds to a designated part of the overlap region associated with one of the overlap groups, then the processor is operative to merge all of the cells containing parts of the overlap region into a new cell within the framework of the table, and (j) populate the new cell with at least one element representing the objects within the overlap region as the objects are displayed on the page in the layout of the objects. | 35. A computer system for creating a table from a layout of a plurality of objects, comprising: a processor; an input device coupled to the processor; a pixel-based display device coupled to the processor; a memory storage device coupled to the processor for maintaining the table data structure; and the processor being operative to: (a) identify each of the objects relative to their location on a pagedisplayed on the pixel-based display device, (b) create at least one overlap group of the objects based upon the location of the objects, each overlap group containing at least one object and any other object that overlaps the at least one object, wherein if a first object and a second object overlap each other, an overlap group containing the first object and the second object is created, (c) bound each overlap group within one of a plurality of non-overlapping rectangles, each non-overlapping rectangle defined by its bounding coordinates, each non-overlapping rectangle bounding an area of the page called an overlap region containing at least one object, (d) store the bounding coordinates of each non-overlapping rectangle within the table data structure as a plurality of x-coordinates and a plurality of y-coordinates, (e) sort the x-coordinates into ascending order and delete duplicate x-coordinates from the table data structure maintained on the memory storage device, (g) sort the y-coordinates into ascending order and delete duplicate y-coordinates from the table data structure maintained on the memory storage device, (h) create a framework of cells defining the table from the coordinates, the framework defined by rows and columns, each row defined by the y-coordinates, each column defined by the x-coordinates, the intersection of each row and each column defining the location of each cell within the table, (i) if one of the cells corresponds to a designated part of the overlap region associated with one of the overlap groups, then the processor is operative to merge all of the cells containing parts of the overlap region into a new cell within the framework of the table, and (j) populate the new cell with at least one element representing the objects within the overlap region as the objects are displayed on the page in the layout of the objects. 36. The computer system of claim 35, wherein the at least one element is a text element if the overlap group associated with the overlap region contains only one of the objects having a predefined rendering characteristic. | 0.652038 |
9,769,107 | 21 | 28 | 21. At least one non-transitory storage device storing instructions operable to cause one or more computing devices to perform operations comprising: receiving, from a first user device, activity information on an activity performed by a user of the first user device; receiving, from the first user device, a location where the first user device has stayed for at least a threshold amount of time; determining a type of the activity; creating a social group based on the location and the type of the activity, including determining a theme of the social group based on the type of the activity; determining that a first condition that a second user device is located at the location or will visit the location is satisfied; determining that a second condition that the second user device seeks information related to the location or related to the theme of the social group is satisfied; and in response to determining that the first and second conditions are satisfied, providing a recommendation to join the social group to the second user device. | 21. At least one non-transitory storage device storing instructions operable to cause one or more computing devices to perform operations comprising: receiving, from a first user device, activity information on an activity performed by a user of the first user device; receiving, from the first user device, a location where the first user device has stayed for at least a threshold amount of time; determining a type of the activity; creating a social group based on the location and the type of the activity, including determining a theme of the social group based on the type of the activity; determining that a first condition that a second user device is located at the location or will visit the location is satisfied; determining that a second condition that the second user device seeks information related to the location or related to the theme of the social group is satisfied; and in response to determining that the first and second conditions are satisfied, providing a recommendation to join the social group to the second user device. 28. The non-transitory storage device of claim 21 , wherein determining that the first condition is satisfied comprises: receiving, from the second user device, an indication that the second user device is located at the location for at least the threshold amount of time; or receiving, from the second user device, a current location of the second user device and predicting that the second user device will visit the location based on the current location, a future time, and a state model representing past movements of the second user device. | 0.5 |
8,048,115 | 3 | 4 | 3. The surgical tool of claim 2 , further comprising: a spring connected between the elongate tube and the elongate shaft; and wherein the spring is configured to bias the elongate tube to the distal end of the elongated shaft; wherein the elongated tube has a grip at a proximal end adjacent the handle which allows the shaft to be slid toward the proximal end of the elongate shaft to operate the retainer to release the deflectable post. | 3. The surgical tool of claim 2 , further comprising: a spring connected between the elongate tube and the elongate shaft; and wherein the spring is configured to bias the elongate tube to the distal end of the elongated shaft; wherein the elongated tube has a grip at a proximal end adjacent the handle which allows the shaft to be slid toward the proximal end of the elongate shaft to operate the retainer to release the deflectable post. 4. The surgical tool of claim 3 , wherein: the retainer is a ball, which is forced against the deflectable post when the elongate tube is positioned at the distal end of the elongate shaft, and which is released when the elongate tube is slid toward the proximal end of the elongate shaft. | 0.5 |
9,569,537 | 29 | 41 | 29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a search engine server, including instructions configured to cause a data processing apparatus to: detect a request for a search for search results, wherein the request for the search includes topic data describing a search topic, and wherein the request does not include a request for an agent; perform a search for information associated with the search topic; determine a search result, wherein the search result includes the information associated with the search topic; process, by the search engine server, status data stored remotely within an agent search server, wherein the search engine server operates remotely from the agent search server and communicates with the agent search server over a network, wherein the status data corresponds to one or more active relevant agents, wherein the one or more active relevant agents are associated with one or more real-time interaction options, wherein agents are active or inactive, and wherein agents are relevant or irrelevant to the search topic; generate an agent search request using the topic data, wherein the agent search request is separate from the request for the search and includes the topic data describing the search topic, wherein the agent search request is used to determine the one or more active relevant agents associated with the search topic, and wherein agents are determined to be relevant by matching the search topic with a topic included in one or more profiles of the one or more active relevant agents; use the status data to determine whether to associate a real-time interactive element with the search result; associate a real-time interactive element with the search result, wherein the real-time interactive element is separate from the search result, and wherein the real-time interactive element is displayed concurrently with the search result; and detect data corresponding to a selection of the real-time interactive element associated with the search result, wherein the real-time interactive element is associated with one or more agents based on the status data, wherein the selection of the real-time interactive element facilitates a real-time interaction option among two or more devices, and wherein at least one device is associated with an active relevant agent associated with the search topic. | 29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a search engine server, including instructions configured to cause a data processing apparatus to: detect a request for a search for search results, wherein the request for the search includes topic data describing a search topic, and wherein the request does not include a request for an agent; perform a search for information associated with the search topic; determine a search result, wherein the search result includes the information associated with the search topic; process, by the search engine server, status data stored remotely within an agent search server, wherein the search engine server operates remotely from the agent search server and communicates with the agent search server over a network, wherein the status data corresponds to one or more active relevant agents, wherein the one or more active relevant agents are associated with one or more real-time interaction options, wherein agents are active or inactive, and wherein agents are relevant or irrelevant to the search topic; generate an agent search request using the topic data, wherein the agent search request is separate from the request for the search and includes the topic data describing the search topic, wherein the agent search request is used to determine the one or more active relevant agents associated with the search topic, and wherein agents are determined to be relevant by matching the search topic with a topic included in one or more profiles of the one or more active relevant agents; use the status data to determine whether to associate a real-time interactive element with the search result; associate a real-time interactive element with the search result, wherein the real-time interactive element is separate from the search result, and wherein the real-time interactive element is displayed concurrently with the search result; and detect data corresponding to a selection of the real-time interactive element associated with the search result, wherein the real-time interactive element is associated with one or more agents based on the status data, wherein the selection of the real-time interactive element facilitates a real-time interaction option among two or more devices, and wherein at least one device is associated with an active relevant agent associated with the search topic. 41. The computer-program product of claim 29 , wherein the search result includes a link to a webpage or website. | 0.809764 |
9,767,148 | 1 | 3 | 1. A method, implemented at least partly by a device, the method comprising: configuring the database system to operate at a limited capacity below its full capacity for execution of database queries of a database, wherein the database system includes one or more processors operable to process data stored in the database in a database environment in order to process the database queries; learning about optimization of execution of one or more selected database queries that do not meet at least one performance criteria associated with a target performance for processing the selected database queries with the limited capacity in the database environment, by using the excess capacity of the database system configured to operate with the limited capacity for the execution of database queries of the database; allowing at least one portion of the excess capacity available to the database system to be used to perform one or more learning activities associated with learning about optimization of execution of one or more selected database queries in the database environment that do not meet at least one performance criteria; and not allowing the at least one portion of the excess capacity available to the database system to be used to perform other activities not associated with the learning about optimization of execution of the database queries in the database environment. | 1. A method, implemented at least partly by a device, the method comprising: configuring the database system to operate at a limited capacity below its full capacity for execution of database queries of a database, wherein the database system includes one or more processors operable to process data stored in the database in a database environment in order to process the database queries; learning about optimization of execution of one or more selected database queries that do not meet at least one performance criteria associated with a target performance for processing the selected database queries with the limited capacity in the database environment, by using the excess capacity of the database system configured to operate with the limited capacity for the execution of database queries of the database; allowing at least one portion of the excess capacity available to the database system to be used to perform one or more learning activities associated with learning about optimization of execution of one or more selected database queries in the database environment that do not meet at least one performance criteria; and not allowing the at least one portion of the excess capacity available to the database system to be used to perform other activities not associated with the learning about optimization of execution of the database queries in the database environment. 3. The method claim 1 , wherein the method further comprises: selecting one or more database queries as candidates for finding potentially a better execution plan that a current plan known for execution of the one or more database queries; and performing the one or more learning operations to learn about the cost of one or more other execution plans, different than the current execution plan, for executing the one or more database queries. | 0.5 |
9,582,762 | 1 | 2 | 1. A system for using artificially intelligent interactive memories, the system implemented at least in part on one or more computing devices, the system comprising: one or more processor circuits; a memory unit, coupled to the one or more processor circuits, that comprises a plurality of interconnected rounds of conversational exchange including a first round of conversational exchange, the first round of conversational exchange comprising a recording of a first conversation participant's first conversational activity correlated with a recording of a second conversation participant's first conversational activity; a picture-capturing device, coupled to the one or more processor circuits, configured to capture a stream of digital pictures of a user; and a sound-capturing device, coupled to the one or more processor circuits, configured to capture a stream of digital sound samples of the user, wherein the one or more processor circuits are configured to: detect the user's first conversational activity from at least one of the stream of digital pictures of the user or the stream of digital sound samples of the user; compare at least one portion of a recording of the user's first conversational activity with at least one portion of the recording of the first conversation participant's first conversational activity; determine at least a partial match between the recording of the user's first conversational activity and the recording of the first conversation participant's first conversational activity; and cause a display and a sound-producing device to play at least one portion of the recording of the second conversation participant's first conversational activity, the causing performed in response to the determining at least a partial match between the recording of the user's first conversational activity and the recording of the first conversation participant's first conversational activity. | 1. A system for using artificially intelligent interactive memories, the system implemented at least in part on one or more computing devices, the system comprising: one or more processor circuits; a memory unit, coupled to the one or more processor circuits, that comprises a plurality of interconnected rounds of conversational exchange including a first round of conversational exchange, the first round of conversational exchange comprising a recording of a first conversation participant's first conversational activity correlated with a recording of a second conversation participant's first conversational activity; a picture-capturing device, coupled to the one or more processor circuits, configured to capture a stream of digital pictures of a user; and a sound-capturing device, coupled to the one or more processor circuits, configured to capture a stream of digital sound samples of the user, wherein the one or more processor circuits are configured to: detect the user's first conversational activity from at least one of the stream of digital pictures of the user or the stream of digital sound samples of the user; compare at least one portion of a recording of the user's first conversational activity with at least one portion of the recording of the first conversation participant's first conversational activity; determine at least a partial match between the recording of the user's first conversational activity and the recording of the first conversation participant's first conversational activity; and cause a display and a sound-producing device to play at least one portion of the recording of the second conversation participant's first conversational activity, the causing performed in response to the determining at least a partial match between the recording of the user's first conversational activity and the recording of the first conversation participant's first conversational activity. 2. The system of claim 1 , wherein the plurality of interconnected rounds of conversational exchange include a second round of conversational exchange connected with the first round of conversational exchange, the second round of conversational exchange comprising a recording of the first conversation participant's second conversational activity correlated with a recording of the second conversation participant's second conversational activity, and wherein the one or more processor circuits are further configured to: detect the user's second conversational activity from at least one of the stream of digital pictures of the user or the stream of digital sound samples of the user; compare at least one portion of a recording of the user's second conversational activity with at least one portion of the recording of the first conversation participant's second conversational activity; determine at least a partial match between the recording of the user's second conversational activity and the recording of the first conversation participant's second conversational activity; and cause the display and the sound-producing device to play at least one portion of the recording of the second conversation participant's second conversational activity, the causing performed in response to the determining at least a partial match between the recording of the user's second conversational activity and the recording of the first conversation participant's second conversational activity. | 0.5 |
9,818,401 | 7 | 8 | 7. The method of claim 1 , further comprising: specializing the secondary ASR recognizer by using an adaptation grammar of structure and content appropriate to a putative span type, as determined by NLU processing, said adaptation grammar additionally including acoustic prefix words, acoustic suffix words, or both, as transcribed by the primary ASR recognizer to ensure high accuracy secondary ASR recognition in view of coarticulation effects in the processed utterance and potential imprecise determination of span start and end times; and correspondingly expanding said span to include said acoustic prefix words, acoustic suffix words, or both. | 7. The method of claim 1 , further comprising: specializing the secondary ASR recognizer by using an adaptation grammar of structure and content appropriate to a putative span type, as determined by NLU processing, said adaptation grammar additionally including acoustic prefix words, acoustic suffix words, or both, as transcribed by the primary ASR recognizer to ensure high accuracy secondary ASR recognition in view of coarticulation effects in the processed utterance and potential imprecise determination of span start and end times; and correspondingly expanding said span to include said acoustic prefix words, acoustic suffix words, or both. 8. The method of claim 7 , further comprising: including acoustic prefix words, acoustic suffix words, or both within the adaptation grammar by preparing said adaptation grammar as a slotted grammar with appropriate one or more prefix slots, suffix slots, or both and populating said slots as appropriate with acoustic prefix words, acoustic suffix words, or both, as transcribed by the primary ASR recognizer. | 0.704611 |
8,375,008 | 34 | 35 | 34. A method for executing operations in accordance with instructions stored on a computer readable medium having software code embodied therein for managing information, the software code comprising computer-executable instructions for: extracting original data from at least two different data sources, a backup tape data source and a networked data source and another data source; determining email files within the original data; extracting information from the email files using an email extraction engine; forwarding the information extracted from the email files to a de-duplication engine; separating the information extracted from the email files and other original data in content portions and metadata portions; analyzing the content portions; placing, into a collective database, a single copy of unique content portions; and placing, into a collective database, at least one copy of the metadata portions including information regarding from where the files were obtained; collecting the data within a collective database; from a user of the computer system, receiving at least one rule, including: a retention policy for the data; and a query for the data, wherein the query for the data includes a query of at least one of the following for the data: subject matter, author, type, and content; using the rule, identifying: compliant data that comply with the retention policy; and targeted data that correspond to the query; and using the rule, preserving the compliant data and the targeted data within the database, while deleting at least a portion of other data that are neither compliant data nor targeted data within the database. | 34. A method for executing operations in accordance with instructions stored on a computer readable medium having software code embodied therein for managing information, the software code comprising computer-executable instructions for: extracting original data from at least two different data sources, a backup tape data source and a networked data source and another data source; determining email files within the original data; extracting information from the email files using an email extraction engine; forwarding the information extracted from the email files to a de-duplication engine; separating the information extracted from the email files and other original data in content portions and metadata portions; analyzing the content portions; placing, into a collective database, a single copy of unique content portions; and placing, into a collective database, at least one copy of the metadata portions including information regarding from where the files were obtained; collecting the data within a collective database; from a user of the computer system, receiving at least one rule, including: a retention policy for the data; and a query for the data, wherein the query for the data includes a query of at least one of the following for the data: subject matter, author, type, and content; using the rule, identifying: compliant data that comply with the retention policy; and targeted data that correspond to the query; and using the rule, preserving the compliant data and the targeted data within the database, while deleting at least a portion of other data that are neither compliant data nor targeted data within the database. 35. The method of claim 34 , wherein extracting the data comprises extracting the data from the backup tape without recreating a backup environment used for generating the backup tape. | 0.69637 |
8,924,214 | 1 | 2 | 1. A method for detecting and recognizing speech, comprising the steps of: remotely detecting body motions from a speaker during vocalization with one or more radar sensors supporting a plurality of simultaneous diverse wavelengths, wherein the body motions comprise small vibrational displacements and articulator motions; extracting Doppler signals correlated with the speaker vocalization; developing feature vectors utilizing the vocalization Doppler signals; and recognizing words associated with the feature vectors with a word classifier. | 1. A method for detecting and recognizing speech, comprising the steps of: remotely detecting body motions from a speaker during vocalization with one or more radar sensors supporting a plurality of simultaneous diverse wavelengths, wherein the body motions comprise small vibrational displacements and articulator motions; extracting Doppler signals correlated with the speaker vocalization; developing feature vectors utilizing the vocalization Doppler signals; and recognizing words associated with the feature vectors with a word classifier. 2. The method of claim 1 , wherein the step of detecting body motions from a speaker during vocalization with one or more radar sensors, comprises the steps of: transmitting the plurality of diverse wavelengths; transmitting one or more waveforms with a transmit aperture towards the speaker during vocalization, each of the waveforms having a distinct wavelength; receiving scattered radio frequency energy from the speaker with a receiver aperture for each diverse wavelength; and converting the scattered radio frequency energy to an intermediate frequency. | 0.628647 |
10,042,539 | 2 | 4 | 2. The method of claim 1 , further comprising: receiving a second user input requesting adjustment of the adjustable slide control; and changing, in response to receiving the second user input, a characteristic of the default text contained in the text window without changing the width and the height of the text window. | 2. The method of claim 1 , further comprising: receiving a second user input requesting adjustment of the adjustable slide control; and changing, in response to receiving the second user input, a characteristic of the default text contained in the text window without changing the width and the height of the text window. 4. The method of claim 2 , wherein the text characteristic is a font size, and wherein the changing of the characteristic includes changing the font size from a first size to a second size that is different than the first size. | 0.620401 |
8,078,453 | 20 | 35 | 20. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from a psychological state represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the psychological state generating with a computer an output communication pertaining to the risk posed by the person from the psychological state of the at least one communication. | 20. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from a psychological state represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the psychological state generating with a computer an output communication pertaining to the risk posed by the person from the psychological state of the at least one communication. 35. A method in accordance with claim 20 wherein: the at least one output communication pertains to an investigation regarding the person. | 0.642487 |
7,496,854 | 13 | 15 | 13. A computer system related to information handling within a document created using a first application program, comprising: means for entering a first information in the first application program; means for marking without user intervention the first information to alert the user that the first information can be utilized in a second application program; and means for responding to a user selection by inserting a second information into the document, the second information associated with the first information from a second application program. | 13. A computer system related to information handling within a document created using a first application program, comprising: means for entering a first information in the first application program; means for marking without user intervention the first information to alert the user that the first information can be utilized in a second application program; and means for responding to a user selection by inserting a second information into the document, the second information associated with the first information from a second application program. 15. The computer system of claim 13 , wherein the means for inserting the second information into the document further comprises: means for initializing the second application program; means for searching, using the second application program, for the second information associated with the first information; and means for retrieving the second information. | 0.5 |
9,350,863 | 9 | 11 | 9. The method of claim 1 , wherein a chat text is used to build an anchor. | 9. The method of claim 1 , wherein a chat text is used to build an anchor. 11. The method of claim 9 , wherein, after said anchor is built, positive hits generated during anchor building in connection with edit-distance are used to obtain a temporary categorization of a team/department. | 0.5 |
8,170,866 | 8 | 11 | 8. A non-transitory computer-readable storage module containing instructions which, when executed by a computing device, cause the computing device to generate a speech recognition model, the instructions comprising: retrieving a list of numbers in a calling history associated with an individual; identifying data of a social network associated with each number in the list of numbers; refining the data of the social network based on at least one parameter, to yield refined data of the social network; and creating, via a processor, a language model for the individual based on the refined data of the social network. | 8. A non-transitory computer-readable storage module containing instructions which, when executed by a computing device, cause the computing device to generate a speech recognition model, the instructions comprising: retrieving a list of numbers in a calling history associated with an individual; identifying data of a social network associated with each number in the list of numbers; refining the data of the social network based on at least one parameter, to yield refined data of the social network; and creating, via a processor, a language model for the individual based on the refined data of the social network. 11. The non-transitory computer-readable storage module of claim 8 , wherein the language model is one of a deterministic model and a stochastic model. | 0.662946 |
8,015,183 | 29 | 30 | 29. A method comprising: identifying a plurality of locations referenced within a plurality of documents of a corpus of documents; for at least one location of the plurality of locations, computing a value score based on a frequency of occurrences of references to the at least one location in the corpus of documents, wherein the computed value score varies inversely with how frequently the at least one location is referenced in the corpus of documents; determining to display a representation of a domain, the domain encompassing the locations; and determining to display an indicator on the representation of the domain, the indicator representing locations of the plurality of locations having a value score exceeding a predetermined value score. | 29. A method comprising: identifying a plurality of locations referenced within a plurality of documents of a corpus of documents; for at least one location of the plurality of locations, computing a value score based on a frequency of occurrences of references to the at least one location in the corpus of documents, wherein the computed value score varies inversely with how frequently the at least one location is referenced in the corpus of documents; determining to display a representation of a domain, the domain encompassing the locations; and determining to display an indicator on the representation of the domain, the indicator representing locations of the plurality of locations having a value score exceeding a predetermined value score. 30. The method of claim 29 , wherein the indicator comprises a hounding box representing an area encompassing a plurality of proximate locations each having a value score exceeding the predetermined value score. | 0.5 |
8,364,694 | 5 | 7 | 5. A method for searching for digital media information available from an online media store, said method comprising: receiving a search hints request from a client application operating on a client device, the search hints request including at least a character string including at least one character; determining a set of search hints based on the character string, wherein said determining of the set of search hints obtains the matching search hints from a hints data structure and wherein the set of search hints correspond to digital media assets available in an online media repository and at least sales popularity data; obtaining a location of the client device; eliminating from the set of search hints those of the search hints in the set of search hints that are associated with a location other than the location of the client device; obtaining a media popularity indication for each of a plurality of the search hints in the set of search hints; and sending a portion of the search hints in the set of search hints to the client application on the client device, the portion of the search hints sent to the client application being less than all the search hints in the set of search hints. | 5. A method for searching for digital media information available from an online media store, said method comprising: receiving a search hints request from a client application operating on a client device, the search hints request including at least a character string including at least one character; determining a set of search hints based on the character string, wherein said determining of the set of search hints obtains the matching search hints from a hints data structure and wherein the set of search hints correspond to digital media assets available in an online media repository and at least sales popularity data; obtaining a location of the client device; eliminating from the set of search hints those of the search hints in the set of search hints that are associated with a location other than the location of the client device; obtaining a media popularity indication for each of a plurality of the search hints in the set of search hints; and sending a portion of the search hints in the set of search hints to the client application on the client device, the portion of the search hints sent to the client application being less than all the search hints in the set of search hints. 7. The method of claim 5 , wherein said method further comprises: limiting the number of search hints remaining in the set of search hints. | 0.908553 |
10,073,794 | 8 | 9 | 8. The method of claim 6 , further comprising pre-allocating a temporary memory space for use during search activity by the user. | 8. The method of claim 6 , further comprising pre-allocating a temporary memory space for use during search activity by the user. 9. The method of claim 8 , wherein the temporary memory space is an APP container space. | 0.5 |
9,183,321 | 15 | 21 | 15. One or more non-transitory computer-readable media storing instructions which, when executed by one or more processors, cause: storing, within a repository, a plurality of compound documents, each compound document of the plurality of compound documents including: a parent document, a plurality of subdocuments of said parent document; wherein the parent document includes, for each subdocument of the plurality of subdocuments, a link to said each subdocument; storing, in association with a first compound document of the plurality of compound documents, a first compound document declaration that declares a first type of link; storing, in association with a second compound document of the plurality of compound documents, a second compound document declaration that declares a second type of link that is different than the first type of link; wherein the first type of link is one of a hard link, a weak link, or a symbolic link; wherein the second type of link is another one of the hard link, the weak link, or the symbolic link; wherein the hard link is a link such that a first subdocument that is a target of the hard link cannot be deleted from the repository as long as the hard link is included in a first parent document, wherein the hard link is uniquely associated with the first subdocument, and wherein the hard link between a first parent document and the first subdocument is preserved if the first subdocument is moved to another location within the repository; wherein the weak link is a link such that a second subdocument that is a target of the weak link is uniquely associated with the weak link and can be deleted from the repository even while a second parent document includes the weak link to the second subdocument; wherein the symbolic link is a link such that a third parent document that includes the symbolic link is no longer linked to a third subdocument that is a target of the symbolic link when the third subdocument is moved to a different location in the repository, wherein the symbolic link is not uniquely associated with the third subdocument. | 15. One or more non-transitory computer-readable media storing instructions which, when executed by one or more processors, cause: storing, within a repository, a plurality of compound documents, each compound document of the plurality of compound documents including: a parent document, a plurality of subdocuments of said parent document; wherein the parent document includes, for each subdocument of the plurality of subdocuments, a link to said each subdocument; storing, in association with a first compound document of the plurality of compound documents, a first compound document declaration that declares a first type of link; storing, in association with a second compound document of the plurality of compound documents, a second compound document declaration that declares a second type of link that is different than the first type of link; wherein the first type of link is one of a hard link, a weak link, or a symbolic link; wherein the second type of link is another one of the hard link, the weak link, or the symbolic link; wherein the hard link is a link such that a first subdocument that is a target of the hard link cannot be deleted from the repository as long as the hard link is included in a first parent document, wherein the hard link is uniquely associated with the first subdocument, and wherein the hard link between a first parent document and the first subdocument is preserved if the first subdocument is moved to another location within the repository; wherein the weak link is a link such that a second subdocument that is a target of the weak link is uniquely associated with the weak link and can be deleted from the repository even while a second parent document includes the weak link to the second subdocument; wherein the symbolic link is a link such that a third parent document that includes the symbolic link is no longer linked to a third subdocument that is a target of the symbolic link when the third subdocument is moved to a different location in the repository, wherein the symbolic link is not uniquely associated with the third subdocument. 21. The one or more non-transitory computer-readable media of claim 15 , wherein the instructions, when executed by the one or more processors, further cause: creating an expanded view of a particular compound document of the plurality of compound documents, wherein a link to a particular subdocument is replaced with content imported from said subdocument into the expanded view of the particular compound document; receiving an update to the expanded view of the compound document, wherein applying the update changes content imported from said particular subdocument; and automatically applying changes corresponding to said update to said particular subdocument that is stored separately from the expanded view of the particular compound document. | 0.625125 |
8,452,794 | 1 | 4 | 1. A method comprising: receiving, at a first computing device, a search request from a second computing device of a user, the search request for images associated with a textual query; determining, by the first computing device and based at least in part on the received textual query, multiple images that are associated with the received textual query; determining, by the first computing device, a first keyword that is associated with a first set of the multiple images and determining, by the first computing device, a second keyword that is associated with a second set of the multiple images; clustering, by the first computing device, the first set of the multiple images into two or more clusters and clustering, by the first computing device, the second set of the multiple images into two or more clusters; determining, by the first computing device: (i) an image from the first cluster of the first set of the multiple images that is representative of the first cluster of the first set of the multiple images; (ii) an image from the second cluster of the first set of the multiple images that is representative of the second cluster of the first set of the multiple images; (iii) an image from the first cluster of the second set of the multiple images that is representative of the first cluster of the second set of the multiple images, and (iv) an image from the second cluster of the second set of the multiple images that is representative of the second cluster of the second set of the multiple images; providing the first keyword and the second keyword and the respective representative images of the first and the second clusters of the first set and the respective representative images of the first and the second clusters of the second set, to the second computing device of the user, in a suggestion to refine the search request based at least on the first keyword or the second keyword and based at least on one of the respective representative images; and responsive to receiving a selection of one of the first keyword or the second keyword and a selection of one of the respective representative images, refining the search request based at least on the selected keyword and based at least on the selected representative image. | 1. A method comprising: receiving, at a first computing device, a search request from a second computing device of a user, the search request for images associated with a textual query; determining, by the first computing device and based at least in part on the received textual query, multiple images that are associated with the received textual query; determining, by the first computing device, a first keyword that is associated with a first set of the multiple images and determining, by the first computing device, a second keyword that is associated with a second set of the multiple images; clustering, by the first computing device, the first set of the multiple images into two or more clusters and clustering, by the first computing device, the second set of the multiple images into two or more clusters; determining, by the first computing device: (i) an image from the first cluster of the first set of the multiple images that is representative of the first cluster of the first set of the multiple images; (ii) an image from the second cluster of the first set of the multiple images that is representative of the second cluster of the first set of the multiple images; (iii) an image from the first cluster of the second set of the multiple images that is representative of the first cluster of the second set of the multiple images, and (iv) an image from the second cluster of the second set of the multiple images that is representative of the second cluster of the second set of the multiple images; providing the first keyword and the second keyword and the respective representative images of the first and the second clusters of the first set and the respective representative images of the first and the second clusters of the second set, to the second computing device of the user, in a suggestion to refine the search request based at least on the first keyword or the second keyword and based at least on one of the respective representative images; and responsive to receiving a selection of one of the first keyword or the second keyword and a selection of one of the respective representative images, refining the search request based at least on the selected keyword and based at least on the selected representative image. 4. The method as recited in claim 1 , the providing the first keyword and the second keyword and the respective representative images of the first and the second clusters of the first set and the respective representative images of the first and the second clusters of the second set, to the second computing device of the user, in a suggestion comprises causing display of the first and the second keywords and the images that are each representative of a respective cluster, and the receiving of the selection comprises receiving a selection of a displayed representative image. | 0.5 |
8,145,719 | 1 | 8 | 1. A network communication method at a client, wherein the client includes at least a first file, comprising: establishing a first and second connection between the client and a server, wherein the first connection comprises an open connection that utilizes an instant messaging protocol and the connections are not necessarily established at the same time; receiving a persistent message pushed from the server through the first connection, wherein the first message instructs the client to request first update data from the server through the second network connection, wherein the persistent message is generated in response to receiving the first update data and the persistent message instructs the client that first update data is available for the first HTML file at the server, wherein the persistent message is only pushed from the server in response to the server receiving the first update data; automatically requesting the first update data from the server through the second connection in response to the instructions in the persistent message; and updating the first file with the first update data received from the server. | 1. A network communication method at a client, wherein the client includes at least a first file, comprising: establishing a first and second connection between the client and a server, wherein the first connection comprises an open connection that utilizes an instant messaging protocol and the connections are not necessarily established at the same time; receiving a persistent message pushed from the server through the first connection, wherein the first message instructs the client to request first update data from the server through the second network connection, wherein the persistent message is generated in response to receiving the first update data and the persistent message instructs the client that first update data is available for the first HTML file at the server, wherein the persistent message is only pushed from the server in response to the server receiving the first update data; automatically requesting the first update data from the server through the second connection in response to the instructions in the persistent message; and updating the first file with the first update data received from the server. 8. The network communication method of claim 1 , further comprising: receiving second update data through a user interface; and updating the first file with the second update data. | 0.618644 |
9,798,767 | 1 | 25 | 1. An automated method in a computing system for facilitating a search of intellectual property information from a corpus of patent related publications by automatically performing citation analysis upon each iteration of the search, the citation analysis comprising citations from a respective face of each patent publication, which lists backward references as well as forward references to patents and/or patent publications, comprising: receiving an indication of source text and/or patent related publications as source input; automatically analyzing the indicated source input using semantic analysis of the indicated source input to automatically determine a first set of search-based keywords that are present in the indicated source text, wherein the automatically analyzing the source input to determine the first set of search-based keywords using semantic analysis parses the source in to determine grammatical usage to automatically determine the first set of search-based key words; from the automatically determined first set of search-based keywords, performing an initial search iteration automatically, and wherein the initial search iteration is performed without additional user input, by performing the steps of: automatically determining an initial set of patent related publications that include the automatically determined first set of keywords; automatically determining a correlated set of patent related publications that are correlated to the initial set of patent related publications using automatic citation analysis of the initial set of patent related publications, wherein the correlated set is determined to be some number of patent related publications from the corpus that have unique citation relationships to any one of the patent related publications of the initial set, and wherein the correlated set is automatically sorted based upon the correlated patent related publications that involve the most number of citation paths with the initial set of patent related publications; and automatically extracting from the automatically determined initial set of patent related publications a set of related keywords not found in the first set of keywords or in the source input; and providing indicators to the automatically determined initial set and the sorted determined correlated set of patent related publications and the set of related keywords as output from the initial search iteration. | 1. An automated method in a computing system for facilitating a search of intellectual property information from a corpus of patent related publications by automatically performing citation analysis upon each iteration of the search, the citation analysis comprising citations from a respective face of each patent publication, which lists backward references as well as forward references to patents and/or patent publications, comprising: receiving an indication of source text and/or patent related publications as source input; automatically analyzing the indicated source input using semantic analysis of the indicated source input to automatically determine a first set of search-based keywords that are present in the indicated source text, wherein the automatically analyzing the source input to determine the first set of search-based keywords using semantic analysis parses the source in to determine grammatical usage to automatically determine the first set of search-based key words; from the automatically determined first set of search-based keywords, performing an initial search iteration automatically, and wherein the initial search iteration is performed without additional user input, by performing the steps of: automatically determining an initial set of patent related publications that include the automatically determined first set of keywords; automatically determining a correlated set of patent related publications that are correlated to the initial set of patent related publications using automatic citation analysis of the initial set of patent related publications, wherein the correlated set is determined to be some number of patent related publications from the corpus that have unique citation relationships to any one of the patent related publications of the initial set, and wherein the correlated set is automatically sorted based upon the correlated patent related publications that involve the most number of citation paths with the initial set of patent related publications; and automatically extracting from the automatically determined initial set of patent related publications a set of related keywords not found in the first set of keywords or in the source input; and providing indicators to the automatically determined initial set and the sorted determined correlated set of patent related publications and the set of related keywords as output from the initial search iteration. 25. The method of claim 1 wherein the correlated set of patent related publications is further constrained to patent related publications that share the same primary classification category as one or more of the initial set of patent related publications. | 0.922492 |
9,846,731 | 11 | 18 | 11. One or more non-transitory computer-readable storage media comprising stored instructions which, when executed by one or more processors, cause performing a method of matching a plurality of imported data entities to a plurality of existing data entities in a database comprising: receiving first input specifying a first matching criteria that is based at least in part on a first subset of one or more properties of the imported data entities, and specifying a first matching technique to use as part of the first matching criteria; receiving second input specifying a second matching criteria that is different from the first matching criteria and that is based at least in part on a second subset of the one or more properties of the imported data entities, wherein the second subset of the one or more properties is different than the first subset of one or more properties, and specifying a second matching technique that is different than the first matching technique and to use as part of the second matching criteria; receiving third input specifying a particular one of the imported data entities and signaling a request to resolve that particular one of the imported data entities in relation to the existing data entities; matching the particular one of the imported data entities to a first subset of the existing data entities using the first matching criteria and using the first matching technique; matching the particular one of the imported data entities to a second subset of the existing data entities using the second matching criteria and using the second matching technique; causing display of a first result of matching the particular one imported data entity to the first subset of the existing data entities and a second result of matching the particular one imported data entity to the second subset of the existing data entities; receiving, in response to the display, a selection of one or more of continuing resolving the particular one imported data entity, resolving others of the imported data entities, and consolidating the particular one imported data entity into the existing data entities, the consolidating comprising adding at least one value from the particular one imported data entity to one of the first subset of the existing data entities or one of the second subset of the existing data entities; performing further resolution or consolidation based on the selection. | 11. One or more non-transitory computer-readable storage media comprising stored instructions which, when executed by one or more processors, cause performing a method of matching a plurality of imported data entities to a plurality of existing data entities in a database comprising: receiving first input specifying a first matching criteria that is based at least in part on a first subset of one or more properties of the imported data entities, and specifying a first matching technique to use as part of the first matching criteria; receiving second input specifying a second matching criteria that is different from the first matching criteria and that is based at least in part on a second subset of the one or more properties of the imported data entities, wherein the second subset of the one or more properties is different than the first subset of one or more properties, and specifying a second matching technique that is different than the first matching technique and to use as part of the second matching criteria; receiving third input specifying a particular one of the imported data entities and signaling a request to resolve that particular one of the imported data entities in relation to the existing data entities; matching the particular one of the imported data entities to a first subset of the existing data entities using the first matching criteria and using the first matching technique; matching the particular one of the imported data entities to a second subset of the existing data entities using the second matching criteria and using the second matching technique; causing display of a first result of matching the particular one imported data entity to the first subset of the existing data entities and a second result of matching the particular one imported data entity to the second subset of the existing data entities; receiving, in response to the display, a selection of one or more of continuing resolving the particular one imported data entity, resolving others of the imported data entities, and consolidating the particular one imported data entity into the existing data entities, the consolidating comprising adding at least one value from the particular one imported data entity to one of the first subset of the existing data entities or one of the second subset of the existing data entities; performing further resolution or consolidation based on the selection. 18. The one or more non-transitory computer-readable storage media of claim 11 , wherein the instructions when executed cause storing the first matching criteria and the second matching criteria for use in subsequent entity resolution operations. | 0.806604 |
8,762,857 | 1 | 13 | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy. | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy. 13. The portable dataport of claim 1 , wherein the portable dataport wirelessly synchronizes to a remote, host server to provide the ability to load real-time documents onto the portable dataport. | 0.934051 |
9,953,186 | 10 | 12 | 10. The system of claim 7 , wherein the network proxy server is further configured to determine the character type of the search term, to pad at least one trailing character to the search term using the minimum possible value associated with the character type of the search term to generate the minimum possible plaintext string, and to pad at least one trailing character to the search term using the maximum possible value associated with the character type of the search term to generate the maximum possible plaintext string. | 10. The system of claim 7 , wherein the network proxy server is further configured to determine the character type of the search term, to pad at least one trailing character to the search term using the minimum possible value associated with the character type of the search term to generate the minimum possible plaintext string, and to pad at least one trailing character to the search term using the maximum possible value associated with the character type of the search term to generate the maximum possible plaintext string. 12. The system of claim 10 , wherein the network proxy server is further configured to pad at least one trailing character to the search term using the maximum possible value associated with the character type of the search term based on the ASCII values assigned to the character type. | 0.5 |
8,566,277 | 16 | 17 | 16. A computer program product comprising a computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: generating an interface for receiving a copybook selection and REDEFINE criteria; importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a dynamic COBOL construct; creating an object model for the copybook; receiving the set of COBOL data; identifying, based at least in part on the received set of COBOL data, an instance of a REDEFINE clause and automatically forming the REDEFINE clause as an object instance; and forming the object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the dynamic COBOL construct without requiring custom coding for the forming of the object instance. | 16. A computer program product comprising a computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: generating an interface for receiving a copybook selection and REDEFINE criteria; importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a dynamic COBOL construct; creating an object model for the copybook; receiving the set of COBOL data; identifying, based at least in part on the received set of COBOL data, an instance of a REDEFINE clause and automatically forming the REDEFINE clause as an object instance; and forming the object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the dynamic COBOL construct without requiring custom coding for the forming of the object instance. 17. The computer program product of claim 16 , wherein automatically forming the REDEFINE clause as the object instance further comprises: reading the set of COBOL data; identifying an instance of the REDEFINE clause affecting a REDEFINE subset; recursively rereading the REDEFINE subset; and automatically forming each reread portion of the REDEFINE subset as the object instance. | 0.5 |
8,024,337 | 1 | 2 | 1. A method of determining query similarity, comprising: logging instances of a first query; logging instances of a second query; deriving a first query distribution using the logged instances of the first query; deriving a second query distribution using the logged instances of the second query; comparing the first and second query distributions, where comparing the first and second query distributions comprises: determining a distance measure between the first query distribution and the second query distribution; comparing the distance measure to a specified threshold; and designating the second query as similar to the first query if the distance measure is below the specified threshold; and determining whether the second query is similar to the first query based on the comparison. | 1. A method of determining query similarity, comprising: logging instances of a first query; logging instances of a second query; deriving a first query distribution using the logged instances of the first query; deriving a second query distribution using the logged instances of the second query; comparing the first and second query distributions, where comparing the first and second query distributions comprises: determining a distance measure between the first query distribution and the second query distribution; comparing the distance measure to a specified threshold; and designating the second query as similar to the first query if the distance measure is below the specified threshold; and determining whether the second query is similar to the first query based on the comparison. 2. The method of claim 1 , wherein the first query comprises a first language and wherein the second query comprises a second language that is different than the first language. | 0.689474 |
10,003,492 | 1 | 30 | 1. A method for managing data related to network elements in a telecommunications network, comprising: receiving, at a server, a document containing data related to one or more network elements in the telecommunications network, the document associated with a corresponding source provider, a location, a receipt timestamp indicating the time and date that the document was received, and a creation timestamp indicating the time and date that the document was created; determining a document class for the document; generating an intermediate, in-memory representation of the document data, the intermediate representation comprising a plurality of key-value pairs, wherein each key-value pair is associated with a network element in the telecommunications network; identifying a parsing template corresponding to the document class and the corresponding source provider of the document, the parsing template comprising a plurality of parsing rules; parsing the intermediate representation according to the plurality of parsing rules to identify relevant values from the intermediate representation; correlating the identified values to a network model according to the plurality of parsing rules, the network model comprising a plurality of network entities that represent types of network elements in the telecommunications network, wherein the network model provides a uniform structure to be applied across a plurality of source providers, wherein each network entity of the network model comprises one or more attributes, and wherein each identified value is correlated to an attribute of a network entity in the network model based on a respective parsing rule of the parsing template; normalizing each identified value according to a format defined by the network model; writing the normalized values to a networking database, the networking database comprising a plurality of different types of data related to network elements in the telecommunications network, wherein the written values are linked to the corresponding associated network elements and correlated network entity attributes. | 1. A method for managing data related to network elements in a telecommunications network, comprising: receiving, at a server, a document containing data related to one or more network elements in the telecommunications network, the document associated with a corresponding source provider, a location, a receipt timestamp indicating the time and date that the document was received, and a creation timestamp indicating the time and date that the document was created; determining a document class for the document; generating an intermediate, in-memory representation of the document data, the intermediate representation comprising a plurality of key-value pairs, wherein each key-value pair is associated with a network element in the telecommunications network; identifying a parsing template corresponding to the document class and the corresponding source provider of the document, the parsing template comprising a plurality of parsing rules; parsing the intermediate representation according to the plurality of parsing rules to identify relevant values from the intermediate representation; correlating the identified values to a network model according to the plurality of parsing rules, the network model comprising a plurality of network entities that represent types of network elements in the telecommunications network, wherein the network model provides a uniform structure to be applied across a plurality of source providers, wherein each network entity of the network model comprises one or more attributes, and wherein each identified value is correlated to an attribute of a network entity in the network model based on a respective parsing rule of the parsing template; normalizing each identified value according to a format defined by the network model; writing the normalized values to a networking database, the networking database comprising a plurality of different types of data related to network elements in the telecommunications network, wherein the written values are linked to the corresponding associated network elements and correlated network entity attributes. 30. The method of claim 1 , wherein the steps of generating, identifying, parsing, correlating, normalizing, and writing are generated via a functional programming language. | 0.843297 |
8,086,442 | 14 | 19 | 14. A system for dividing an input into segments, the system comprising: a memory; a processor; and a segmentation component that is stored in said memory and that executes on said processor, wherein said segmentation component represents one or more segment breaking rules in a first regular expression, wherein said segmentation component combines a plurality of exceptions to said one or more segment breaking rules disjunctively into a second regular expression, said second regular expression being distinct from said first regular expression, wherein said segmentation component finds first strings in said input that match said second regular expression, wherein said segmentation component replaces said first strings with placeholders to create a second string, wherein said second string comprises said input but with said placeholders in place of said first strings, wherein said segmentation component uses said first regular expression to detect segment break points in said second string subsequent to finding of said first strings, and wherein said segmentation component replaces said placeholders in said second string with said first strings subsequent to detecting said segment break points. | 14. A system for dividing an input into segments, the system comprising: a memory; a processor; and a segmentation component that is stored in said memory and that executes on said processor, wherein said segmentation component represents one or more segment breaking rules in a first regular expression, wherein said segmentation component combines a plurality of exceptions to said one or more segment breaking rules disjunctively into a second regular expression, said second regular expression being distinct from said first regular expression, wherein said segmentation component finds first strings in said input that match said second regular expression, wherein said segmentation component replaces said first strings with placeholders to create a second string, wherein said second string comprises said input but with said placeholders in place of said first strings, wherein said segmentation component uses said first regular expression to detect segment break points in said second string subsequent to finding of said first strings, and wherein said segmentation component replaces said placeholders in said second string with said first strings subsequent to detecting said segment break points. 19. The system of claim 14 , wherein a first one of said one or more segment breaking rules has both a before break rule and an after break rule, and wherein said first regular expression includes said before break rule as a positive lookbehind and said after break rule as a non-capture group. | 0.606952 |
5,466,072 | 6 | 31 | 6. A shorthand machine for recording and translating shorthand notes including a non-redundant binary tree look-up table comprising: a keyboard having keys representing letter symbols of a language; conversion means connected to said keyboard for generating a particular electric shorthand signal for each key or combination of keys pressed by an operator; a look-up table having a plurality of entries for electronically storing a translation dictionary; said look-up table further having main level and sublevel memory locations for storing said electric shorthand signals representing groups of one or more entry symbols, and electric signals representing groups of one or more translation symbols corresponding to the groups of entry symbols, said main level and sublevel memory locations containing no more than one of the groups of entry symbols; control means connected to said conversion means and to said look-up table; said control means capable of searching said look-up table entries to locate and read a particular electric translation signal corresponding to the particular electric shorthand signal generated at said conversion means; and display means connected to said control means for converting a predetermined number of said read translation signals into groups of display characters representing language words and displaying said words on a plurality of lines. | 6. A shorthand machine for recording and translating shorthand notes including a non-redundant binary tree look-up table comprising: a keyboard having keys representing letter symbols of a language; conversion means connected to said keyboard for generating a particular electric shorthand signal for each key or combination of keys pressed by an operator; a look-up table having a plurality of entries for electronically storing a translation dictionary; said look-up table further having main level and sublevel memory locations for storing said electric shorthand signals representing groups of one or more entry symbols, and electric signals representing groups of one or more translation symbols corresponding to the groups of entry symbols, said main level and sublevel memory locations containing no more than one of the groups of entry symbols; control means connected to said conversion means and to said look-up table; said control means capable of searching said look-up table entries to locate and read a particular electric translation signal corresponding to the particular electric shorthand signal generated at said conversion means; and display means connected to said control means for converting a predetermined number of said read translation signals into groups of display characters representing language words and displaying said words on a plurality of lines. 31. The device defined in claim 6 further comprising a printing mechanism connected to said keyboard for printing shorthand notes on a paper tape in response to a key or a combination of keys being pressed. | 0.821181 |
8,023,719 | 11 | 14 | 11. A method of implementing a phase angle based magnetic ink character recognition (MICR) system, comprising: generating a set of phase angle components from a Fourier transform of temporal MICR data for an inputted arbitrary character, wherein the set of phase angle components comprises a plurality of harmonics; calculating a phase angle difference between adjacent harmonics of the plurality of harmonics to generate a set of phase angle differences; and comparing the set of phase angle differences with each of a set of reference waveforms to determine an identity of the inputted arbitrary character. | 11. A method of implementing a phase angle based magnetic ink character recognition (MICR) system, comprising: generating a set of phase angle components from a Fourier transform of temporal MICR data for an inputted arbitrary character, wherein the set of phase angle components comprises a plurality of harmonics; calculating a phase angle difference between adjacent harmonics of the plurality of harmonics to generate a set of phase angle differences; and comparing the set of phase angle differences with each of a set of reference waveforms to determine an identity of the inputted arbitrary character. 14. The method of claim 11 , wherein a reference waveform is provided for each character in a character set. | 0.727273 |
7,683,810 | 8 | 9 | 8. The method of claim 7 wherein the step of producing the additional code words includes modifying the data and flag bits differently for each additional code word and encoding the modified bits. | 8. The method of claim 7 wherein the step of producing the additional code words includes modifying the data and flag bits differently for each additional code word and encoding the modified bits. 9. The method of claim 8 wherein the respective modified data and flag bits are encoded in the same manner as the (N−y)−1 and y flag bits. | 0.5 |
9,548,051 | 1 | 3 | 1. A method comprising: partitioning speech recognizer output into a plurality of independent clauses; and for an independent clause in the plurality of independent clauses: identifying an object; and recursively generating, via a processor, for each sub-independent clause within the independent clause, a semantic representation using the object. | 1. A method comprising: partitioning speech recognizer output into a plurality of independent clauses; and for an independent clause in the plurality of independent clauses: identifying an object; and recursively generating, via a processor, for each sub-independent clause within the independent clause, a semantic representation using the object. 3. The method of claim 1 , wherein the object comprises a domain-dependent object. | 0.817778 |
7,603,651 | 1 | 3 | 1. A language processing system taking as input a grammar model for a language, formulated as an RTN and, secondly, one or more partially overlapping sequences at a time, of concatenable terminals, or more specifically language elements, said set of input sequences together formulated as a sequence-chart of such elements, said system delivering as output a parse result for each incoming sequence-chart, obtained by applying a parse operation on said sequence-chart, characterised in that said system comprises: memory access to store and consult a set of phonological, morphological, syntactical and/or semantic rules for a language, formulated as an RTN data-structure; memory access to store and consult a plurality of n-Swings, in which n represents an integer number being at least 2, organised in lists of finite length, each list labelled with an n-fold of said language elements, and each n-Swing being defined as a unique path segment that is a contiguous part of at least one partial parse pathway (passing over transitions and jumps for FSM calling and returning), thus a Link sequence complying with the RTN, and that comprises one terminal transition at the start of the segment and one terminal transition at the end of the segment, and includes n-2 terminal transitions in between; derivation means to derive said lists of n-Swings for a given n from the RTN, while limiting the length of the n-Swings to a predetermined number of transitions to prevent infinite lengths, by applying the following algorithms for deriving n-Swings in three phases, the first phase being the generation of all possible Links in every FSM of said RTN, the second phase being the generation of all possible Bi-Swings in the RTN, the Bi-Swings being limited by a fixed limit on the length of its sequence of Links and/or by a limit of the call level span; the optional third phase being the generation of all possible n-Swings for a predetermined integer n>2, which are calculated by induction in recursive incremental phases, starting by calculating 3-Swings, by either left or right attachment of matching Bi-Swings to (n−1)-Swings, parsing means provided to derive a parse result from said supplied token sequence-chart of concatenable language elements by using said lists of n-Swings, said parsing means being provided to build all possible parses, by building a list of every n-Swings that matches a full sequence of N language elements that is derivable from said input sequence-chart; an optional means to derive a parse result from said supplied token sequence-chart of concatenable language elements, by seeding the set of possible parses, each regarded as Link sequences, from the set of n-Swings of the n-Swing list associated with an n-fold of n subsequent language elements, as occurs at the start or the end of a sequence comprised in the sequence-chart, and by trying to extend each seed of a parse by repeatedly attaching matching subsequent n-Swings at the begin or the end of the open ended sides of its Link sequences, while taking the subsequent n-Swings from lists that are associated with a sequence of n language elements as they occur directly at the one, respectively the other side of those language elements in the supplied sequence as derived from the sequence chart, that have not yet been associated with a set of n-Swings, said parsing means being also provided to multiply the built-up Link sequences each time multiple possibilities exist for extension, such that every extension possibility is generated and every possibility is unique and for rejecting extensions that contain non-matching call correspondences at any call level and for rejecting extensions that contain below zero calling levels, and for rejecting extensions that would contain call level differences exceeding a predetermined threshold value and for rejecting Link sequences that can't be extended, said parsing means being further provided to form a list of parse result contributions, being a list of only those Link sequences that span the longest length of the supplied sequence and for organising each parse result contribution as a tree structure, said parsing means provided to further add all parse trees for each possible element sequence possible according to the supplied input sequence-chart and finally summarising the entire parse result in one parse forest, containing all parse trees or no parse tree if no full parse was found, or in, equivalently, a parse tree chart. | 1. A language processing system taking as input a grammar model for a language, formulated as an RTN and, secondly, one or more partially overlapping sequences at a time, of concatenable terminals, or more specifically language elements, said set of input sequences together formulated as a sequence-chart of such elements, said system delivering as output a parse result for each incoming sequence-chart, obtained by applying a parse operation on said sequence-chart, characterised in that said system comprises: memory access to store and consult a set of phonological, morphological, syntactical and/or semantic rules for a language, formulated as an RTN data-structure; memory access to store and consult a plurality of n-Swings, in which n represents an integer number being at least 2, organised in lists of finite length, each list labelled with an n-fold of said language elements, and each n-Swing being defined as a unique path segment that is a contiguous part of at least one partial parse pathway (passing over transitions and jumps for FSM calling and returning), thus a Link sequence complying with the RTN, and that comprises one terminal transition at the start of the segment and one terminal transition at the end of the segment, and includes n-2 terminal transitions in between; derivation means to derive said lists of n-Swings for a given n from the RTN, while limiting the length of the n-Swings to a predetermined number of transitions to prevent infinite lengths, by applying the following algorithms for deriving n-Swings in three phases, the first phase being the generation of all possible Links in every FSM of said RTN, the second phase being the generation of all possible Bi-Swings in the RTN, the Bi-Swings being limited by a fixed limit on the length of its sequence of Links and/or by a limit of the call level span; the optional third phase being the generation of all possible n-Swings for a predetermined integer n>2, which are calculated by induction in recursive incremental phases, starting by calculating 3-Swings, by either left or right attachment of matching Bi-Swings to (n−1)-Swings, parsing means provided to derive a parse result from said supplied token sequence-chart of concatenable language elements by using said lists of n-Swings, said parsing means being provided to build all possible parses, by building a list of every n-Swings that matches a full sequence of N language elements that is derivable from said input sequence-chart; an optional means to derive a parse result from said supplied token sequence-chart of concatenable language elements, by seeding the set of possible parses, each regarded as Link sequences, from the set of n-Swings of the n-Swing list associated with an n-fold of n subsequent language elements, as occurs at the start or the end of a sequence comprised in the sequence-chart, and by trying to extend each seed of a parse by repeatedly attaching matching subsequent n-Swings at the begin or the end of the open ended sides of its Link sequences, while taking the subsequent n-Swings from lists that are associated with a sequence of n language elements as they occur directly at the one, respectively the other side of those language elements in the supplied sequence as derived from the sequence chart, that have not yet been associated with a set of n-Swings, said parsing means being also provided to multiply the built-up Link sequences each time multiple possibilities exist for extension, such that every extension possibility is generated and every possibility is unique and for rejecting extensions that contain non-matching call correspondences at any call level and for rejecting extensions that contain below zero calling levels, and for rejecting extensions that would contain call level differences exceeding a predetermined threshold value and for rejecting Link sequences that can't be extended, said parsing means being further provided to form a list of parse result contributions, being a list of only those Link sequences that span the longest length of the supplied sequence and for organising each parse result contribution as a tree structure, said parsing means provided to further add all parse trees for each possible element sequence possible according to the supplied input sequence-chart and finally summarising the entire parse result in one parse forest, containing all parse trees or no parse tree if no full parse was found, or in, equivalently, a parse tree chart. 3. A method to parse an input sequence of N elements for use in a language processing system as claimed in claim 1 , that assumes availability of at least all possible Bi-Swings for the given RTN, each calculated and stored from before, said method in a first phase dividing up the entire sequence in contiguous non-overlapping sub-sequences of at least length 2, such that for each sub-sequence of length m there is a corresponding complete set of m-Swings pre-calculated, stored and available, and said method, in a second phase gradually multiplying and unifying neighbouring m- and m′-Swing-sets by controlling if a combination of both matches and if so by joining them to into all possible combined (m+m′)-Swings corresponding to sub -sequences of length (m+m′) of the input sequence, taking into account that if n-Swings correspond with sub-sequences that include the first or last element in the sequence, matching includes base call-level checking, said method resulting in a final list of 0 or more N-Swings matching the entire sequence of N elements, each of which is equivalent with a parse tree. | 0.824006 |
8,082,215 | 11 | 12 | 11. The system of claim 10 , wherein said inference data inclusion module configured to include into the electronic message the first inference data and the second inference data into the electronic message comprises: an inference data inclusion module configured to include into the electronic message an indication of an action executed in connection with the particular item and performed, at least in part, by the first authoring user. | 11. The system of claim 10 , wherein said inference data inclusion module configured to include into the electronic message the first inference data and the second inference data into the electronic message comprises: an inference data inclusion module configured to include into the electronic message an indication of an action executed in connection with the particular item and performed, at least in part, by the first authoring user. 12. The system of claim 11 , wherein said inference data inclusion module configured to include into the electronic message an indication of an action executed in connection with the particular item and performed, at least in part, by the first authoring user comprises: an inference data inclusion module configured to include into the electronic message an indication of an action executed in connection with the particular item and performed, at least in part, by the second authoring user. | 0.5 |
10,146,939 | 13 | 14 | 13. The system of claim 12 , wherein the hardware processor is further configured to: determine a first plurality of appearance frequencies corresponding to the first plurality of distinct training n-grams; and determine a second plurality of appearance frequencies corresponding to the second plurality of distinct training n-grams; and determining a first anomaly detection score based on the first plurality of appearance frequencies and a second anomaly detection score based on the second plurality of appearance frequencies. | 13. The system of claim 12 , wherein the hardware processor is further configured to: determine a first plurality of appearance frequencies corresponding to the first plurality of distinct training n-grams; and determine a second plurality of appearance frequencies corresponding to the second plurality of distinct training n-grams; and determining a first anomaly detection score based on the first plurality of appearance frequencies and a second anomaly detection score based on the second plurality of appearance frequencies. 14. The method of claim 13 , wherein the hardware processor is further configured to: determine which of the first anomaly detection score and the second anomaly detection score is higher; and output the input dataset based on the anomaly detection score that is higher. | 0.5 |
9,131,045 | 27 | 29 | 27. The system of claim 24 wherein the microphone and the speaker are in communication with the captioned device processor. | 27. The system of claim 24 wherein the microphone and the speaker are in communication with the captioned device processor. 29. The method of claim 27 wherein the caption switch includes a button. | 0.712 |
9,646,097 | 1 | 5 | 1. One or more computer-storage devices accessible by a computing device having computer-executable instructions embodied thereon that, when executed by a computing device, cause the computing device to perform a method of augmenting Web-based search results with relevant content received from third-party applications, the method comprising: registering each of a plurality of third-party applications to obtain an indication of one or more entity types associated with the each registered third-party application of the plurality of third-party applications; receiving an annotated search query, the annotated search query comprising at least an inputted search query and at least one entity type determined to be associated with the inputted search query; in response to receiving the annotated search query, receiving at least one search result from at least a first third-party application of the plurality of third-party applications, wherein the at least one search result from the at least first third-party application is relevant to the at least one entity type associated with the inputted search query; and presenting the at least one search result from the at least first third-party application on a results page. | 1. One or more computer-storage devices accessible by a computing device having computer-executable instructions embodied thereon that, when executed by a computing device, cause the computing device to perform a method of augmenting Web-based search results with relevant content received from third-party applications, the method comprising: registering each of a plurality of third-party applications to obtain an indication of one or more entity types associated with the each registered third-party application of the plurality of third-party applications; receiving an annotated search query, the annotated search query comprising at least an inputted search query and at least one entity type determined to be associated with the inputted search query; in response to receiving the annotated search query, receiving at least one search result from at least a first third-party application of the plurality of third-party applications, wherein the at least one search result from the at least first third-party application is relevant to the at least one entity type associated with the inputted search query; and presenting the at least one search result from the at least first third-party application on a results page. 5. The one or more computer-storage devices of claim 1 , further comprising receiving additional information from the at least first third-party application, the additional information comprising one or more selected from the following: an identity of a user associated with the at least first third-party application; user engagement history with the at least first third-party application; actions and associated uniform resource locators that are relevant to the annotated search query; and rendering information. | 0.596875 |
7,533,172 | 60 | 61 | 60. The method as recited in claim 52 , further comprising the peer locating other peers, services, or content in the peer-to-peer network by discovering one or more peer, service, or content advertisements published on the network. | 60. The method as recited in claim 52 , further comprising the peer locating other peers, services, or content in the peer-to-peer network by discovering one or more peer, service, or content advertisements published on the network. 61. The method as recited in claim 60 , wherein said discovering comprises: sending a discovery query message specifying a particular type of advertisement; receiving one or more advertisements corresponding to the particular type of advertisement in response to said discovery query message. | 0.5 |
9,607,612 | 7 | 10 | 7. A method for speech recognition on a computing device, the method comprising: capturing audio input using an audio sensor of the computing device; distorting a waveform of the audio input to produce a plurality of distorted audio variations, wherein distorting the waveform comprises adjusting a temporal duration of the waveform; performing speech recognition on the audio input and each of the distorted audio variations to produce a plurality of speech recognition results; and selecting a result from the speech recognition results based on contextual information. | 7. A method for speech recognition on a computing device, the method comprising: capturing audio input using an audio sensor of the computing device; distorting a waveform of the audio input to produce a plurality of distorted audio variations, wherein distorting the waveform comprises adjusting a temporal duration of the waveform; performing speech recognition on the audio input and each of the distorted audio variations to produce a plurality of speech recognition results; and selecting a result from the speech recognition results based on contextual information. 10. The method of claim 7 , wherein distorting the audio input further comprises performing at least one of: (i) adjusting a pitch of the audio input or (ii) introducing noise to the audio input, and wherein adjusting the temporal duration of the waveform comprises at least one of: (i) speeding up the audio input or (ii) slowing down the audio input. | 0.531915 |
8,332,400 | 19 | 21 | 19. A tree text web history management system for managing automatically created tree text history entries during a web search by a user with a server connected to a client comprising: a tree text history section having the tree text history entries, wherein the tree text history entries are repeatedly created in a hierarchical format based at least in part on an association with history data received from at least one of a web search and a sub-search conducted using a context menu pulled up in one of the tree text history section and a web document section and within the context of a search term and using a dialog box to select a display option for any sub-search results; a computer program in the client for executing instructions to create and manage the tree text history entries within the tree text history section; a server for retrieving and transmitting history data requested from the client; and wherein the tree text history management system provides tree text history entries that are reusable, modifiable, and manageable, and wherein the context menu is integrated with the tree text history management system. | 19. A tree text web history management system for managing automatically created tree text history entries during a web search by a user with a server connected to a client comprising: a tree text history section having the tree text history entries, wherein the tree text history entries are repeatedly created in a hierarchical format based at least in part on an association with history data received from at least one of a web search and a sub-search conducted using a context menu pulled up in one of the tree text history section and a web document section and within the context of a search term and using a dialog box to select a display option for any sub-search results; a computer program in the client for executing instructions to create and manage the tree text history entries within the tree text history section; a server for retrieving and transmitting history data requested from the client; and wherein the tree text history management system provides tree text history entries that are reusable, modifiable, and manageable, and wherein the context menu is integrated with the tree text history management system. 21. The tree text web history management system of claim 19 , wherein the computer program is a browser add-on. | 0.808621 |
7,603,353 | 21 | 25 | 21. A computer-implemented method for processing multilingual documents in a document database using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the multi-lingual documents having an initial ranking based upon a user search query provided by a user, the method comprising; operating the processor to perform the following selecting N top ranked multi-lingual documents from the retrieved multilingual documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved multi-lingual documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved multi-lingual documents; generating a re-ranking of the N top ranked multi-lingual documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the multi-lingual documents, and for each multi-lingual document being displayed, also to display its initial ranking. | 21. A computer-implemented method for processing multilingual documents in a document database using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the multi-lingual documents having an initial ranking based upon a user search query provided by a user, the method comprising; operating the processor to perform the following selecting N top ranked multi-lingual documents from the retrieved multilingual documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved multi-lingual documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved multi-lingual documents; generating a re-ranking of the N top ranked multi-lingual documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the multi-lingual documents, and for each multi-lingual document being displayed, also to display its initial ranking. 25. A computer-implemented method according to claim 21 further comprising translating the user search query into a multi-lingual user search query before generating the initial ranking of the retrieved multi-lingual documents. | 0.5 |
7,475,016 | 20 | 21 | 20. The computer-readable storage medium of claim 19 , further encoded with computer instructions for: ranking each cluster relative to one another if at least two clusters are identified; ranking each aggregate cluster relative to one another if at least two aggregate clusters are generated; and ranking each cluster and each aggregate cluster relative to each other if at least one cluster is identified and at least one aggregate cluster is generated. | 20. The computer-readable storage medium of claim 19 , further encoded with computer instructions for: ranking each cluster relative to one another if at least two clusters are identified; ranking each aggregate cluster relative to one another if at least two aggregate clusters are generated; and ranking each cluster and each aggregate cluster relative to each other if at least one cluster is identified and at least one aggregate cluster is generated. 21. The computer-readable storage medium of claim 20 , wherein the ranking reflects a relative severity of speech misalignments. | 0.5 |
7,577,718 | 18 | 19 | 18. An information dissemination system comprising: a profiler component that executes on a client and that identifies user interests, that derives key terms from terms extracted from the user interests, and that generates queries from one or more of the key terms, wherein the key terms are derived based on the relevance of the terms to the user interests; an information garnerer component that executes on a server and that obtains search results from executing the queries against information sources; a ranker component that executes on the server and that ranks the search results by, calculating a static weight for each search result, calculating a temporal weight for each search result, calculating a total weight for each search result based at least in part on the static and temporal weights, and ranking the search results based on the total weight of each search result; and a renderer component that executes on the server and that renders the ranked search results for viewing. | 18. An information dissemination system comprising: a profiler component that executes on a client and that identifies user interests, that derives key terms from terms extracted from the user interests, and that generates queries from one or more of the key terms, wherein the key terms are derived based on the relevance of the terms to the user interests; an information garnerer component that executes on a server and that obtains search results from executing the queries against information sources; a ranker component that executes on the server and that ranks the search results by, calculating a static weight for each search result, calculating a temporal weight for each search result, calculating a total weight for each search result based at least in part on the static and temporal weights, and ranking the search results based on the total weight of each search result; and a renderer component that executes on the server and that renders the ranked search results for viewing. 19. The system of claim 18 further comprising a feedback component that executes on the server and that incorporates feedback regarding the search results into the user interests. | 0.857484 |
9,253,607 | 12 | 14 | 12. A system for wireless communication, the system comprising: one or more circuits for use in a wireless communication device, said one or more circuits being operable to: capture one or more images of one or more sources of textual information in the vicinity of said wireless communication device; extract text from said one or more sources of textual information; and determine a position of said wireless communication device based on a comparison of said extracted text in said captured one or more images to text in a stored database of textual information, wherein the position is determined by, at least in part, determining a distance to a letter at a beginning of the one or more sources of textual information, determining a distance to a letter at an end of the one or more sources of textual information, and triangulating the position using the determined distances. | 12. A system for wireless communication, the system comprising: one or more circuits for use in a wireless communication device, said one or more circuits being operable to: capture one or more images of one or more sources of textual information in the vicinity of said wireless communication device; extract text from said one or more sources of textual information; and determine a position of said wireless communication device based on a comparison of said extracted text in said captured one or more images to text in a stored database of textual information, wherein the position is determined by, at least in part, determining a distance to a letter at a beginning of the one or more sources of textual information, determining a distance to a letter at an end of the one or more sources of textual information, and triangulating the position using the determined distances. 14. The system according to claim 12 , wherein said one or more circuits are operable to utilize an orientation of said wireless device in conjunction with said extracted text for said position determining. | 0.720109 |
9,183,535 | 1 | 15 | 1. A computer-implemented method of generating a user's social network model, the method comprising: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing name disambiguation using the social network model to determine which of at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. | 1. A computer-implemented method of generating a user's social network model, the method comprising: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing name disambiguation using the social network model to determine which of at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. 15. The method of claim 1 , wherein the other identified entities comprise locations and people, the method further comprising: adjusting a relationship strength between a person entity and a location entity based at least in part on a frequency of mentions of the location in correspondence to or from the person. | 0.674274 |
9,247,100 | 25 | 33 | 25. A computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code readable/executable by a processor to cause the processor to: generate text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text for at least one of a meaning and a context of the text; initiate a business process based on the analysis; detect a problem with the business process; generate a notification of the problem; notify one or more entities of the problem; and route at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the routing utilizes an outgoing communication device. | 25. A computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code readable/executable by a processor to cause the processor to: generate text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text for at least one of a meaning and a context of the text; initiate a business process based on the analysis; detect a problem with the business process; generate a notification of the problem; notify one or more entities of the problem; and route at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the routing utilizes an outgoing communication device. 33. The computer readable program product as recited in claim 25 , wherein at least one of the confirmation destinations corresponds to a recipient other than an intended recipient of the facsimile and/or the confirmation. | 0.682857 |
7,873,634 | 1 | 2 | 1. A method for automatic ranking of target files according to a predefined scheme, comprising the steps of: building a database of reference files already ranked according to the predefined scheme; for each target file: i) determining a neighborhood of the target file among the reference files in the database of reference files, and forming a training set comprising reference files of this neighborhood, versus which neighborhood as a whole the target file is to be assessed, wherein said step of forming a training set comprises extracting a feature vector of the target file and finding n closest neighbors of the feature vector of the target file among features vectors in the database of reference files, and wherein said finding n closest neighbors comprises using one of: i) Euclidean distance, ii) cosine distance and iii) Jensen-Shannon distribution similarity; ii) building a test set from features of the target file; iii) dynamically generating a learning model from the training set, the learning model defining a correlation between the reference files in the training set and a rank thereof according to the predefined scheme; and iv) applying the learning model to the test set; whereby a rank corresponding to the target file is predicted according to the predefined scheme. | 1. A method for automatic ranking of target files according to a predefined scheme, comprising the steps of: building a database of reference files already ranked according to the predefined scheme; for each target file: i) determining a neighborhood of the target file among the reference files in the database of reference files, and forming a training set comprising reference files of this neighborhood, versus which neighborhood as a whole the target file is to be assessed, wherein said step of forming a training set comprises extracting a feature vector of the target file and finding n closest neighbors of the feature vector of the target file among features vectors in the database of reference files, and wherein said finding n closest neighbors comprises using one of: i) Euclidean distance, ii) cosine distance and iii) Jensen-Shannon distribution similarity; ii) building a test set from features of the target file; iii) dynamically generating a learning model from the training set, the learning model defining a correlation between the reference files in the training set and a rank thereof according to the predefined scheme; and iv) applying the learning model to the test set; whereby a rank corresponding to the target file is predicted according to the predefined scheme. 2. The method of claim 1 , further comprising storing the predicted rank in a result database. | 0.850794 |
8,489,982 | 17 | 18 | 17. The non-transitory computer-readable medium of claim 15 , wherein the method further comprises storing contents of the markup document in cells of a spreadsheet, wherein the spreadsheet is viewable in a spreadsheet view. | 17. The non-transitory computer-readable medium of claim 15 , wherein the method further comprises storing contents of the markup document in cells of a spreadsheet, wherein the spreadsheet is viewable in a spreadsheet view. 18. The non-transitory computer-readable medium of claim 17 , wherein adding or removing one or more line items from the chart view or from the tree view results in corresponding changes to the spreadsheet. | 0.5 |
9,020,866 | 5 | 10 | 5. A computer implemented method, comprising: under the control of one or more computer systems configured with executable instructions, training a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; training a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and ranking the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request. | 5. A computer implemented method, comprising: under the control of one or more computer systems configured with executable instructions, training a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; training a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and ranking the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request. 10. The computer implemented method of claim 5 , wherein the first ranking score is computed and stored into the index periodically upon expiration of a predetermined time interval. | 0.669708 |
7,788,103 | 1 | 2 | 1. A computer implemented method for speech recognition output confirmation, comprising: receiving an automatic speech recognition result with an associated score indicating a level of confidence with respect to the speech recognition result; accepting a mode selection specifying when an automated confirmation is to be performed, said mode selection chosen from a group consisting of a deterministic mode, a random mode and an integrated mode, wherein the random mode comprises randomly determining whether to perform the automated confirmation; determining, based on said accepted mode selection and said score, whether a confirmation is to be performed on the speech recognition result; and if it is determined that said confirmation is to be performed, performing an automated confirmation to verify the automatic speech recognition result by activating a confirmation construction mechanism operatively configured to carry out a speech recognition confirmation. | 1. A computer implemented method for speech recognition output confirmation, comprising: receiving an automatic speech recognition result with an associated score indicating a level of confidence with respect to the speech recognition result; accepting a mode selection specifying when an automated confirmation is to be performed, said mode selection chosen from a group consisting of a deterministic mode, a random mode and an integrated mode, wherein the random mode comprises randomly determining whether to perform the automated confirmation; determining, based on said accepted mode selection and said score, whether a confirmation is to be performed on the speech recognition result; and if it is determined that said confirmation is to be performed, performing an automated confirmation to verify the automatic speech recognition result by activating a confirmation construction mechanism operatively configured to carry out a speech recognition confirmation. 2. The method according to claim 1 , wherein said determining step when performed for said deterministic mode comprises: determining whether the confidence score associated with the speech recognition result is within a pre-defined range; performing a confirmation if the confidence score associated with the speech recognition result is within the pre-defined range. | 0.664534 |
7,739,658 | 18 | 19 | 18. Apparatus as claimed in claim 17 , wherein the set of data objects further comprises multiple versions corresponding to a set of available user preferences. | 18. Apparatus as claimed in claim 17 , wherein the set of data objects further comprises multiple versions corresponding to a set of available user preferences. 19. Apparatus as claimed in claim 18 , comprising means for determining a user preference from the request message and wherein the selecting means is further operable to select the data object according to the user preference. | 0.5 |
8,996,515 | 3 | 4 | 3. One or more computer readable media according to claim 2 , wherein the query expansion procedure treats an input term as a search query and then uses results of executing the search query to represent the input term as a set of semantically related words. | 3. One or more computer readable media according to claim 2 , wherein the query expansion procedure treats an input term as a search query and then uses results of executing the search query to represent the input term as a set of semantically related words. 4. One or more computer readable media according to claim 3 , wherein the input term is mapped to a pseudo document by obtaining documents returned by a search engine that received the search query. | 0.5 |
7,747,557 | 16 | 17 | 16. The computer readable storage medium of claim 14 , further comprising accessing a dialog pane of the flag library storage from the operating system user interface, wherein the dialog pane includes a listing of flag types and a count of document files having a respective flag type within the file storage of the operating system. | 16. The computer readable storage medium of claim 14 , further comprising accessing a dialog pane of the flag library storage from the operating system user interface, wherein the dialog pane includes a listing of flag types and a count of document files having a respective flag type within the file storage of the operating system. 17. The computer readable storage medium of claim 16 , wherein the dialog pane of the flag library storage includes an icon selection field, a color selection field and a label selection field. | 0.5 |
8,392,360 | 1 | 2 | 1. A system for providing an answer to a question left unanswered in a discussion forum, the system comprising: a data store that stores data associated with a plurality of discussion forums, wherein each discussion forum comprises text corresponding to a discussion; and a computing device in communication with the data store and that is operative to: identify a question in a first discussion forum stored in the data store; determine that the first discussion forum does not include an answer to the question; determine a second discussion forum in which to present the question, wherein determining a second discussion forum in which to present the question comprises determining that the second discussion forum is more likely than the first discussion forum to result in an answer to the question; present the question in the second discussion forum based at least in part on the determination that the first discussion forum does not include an answer to the question; receive at least one response, in the second discussion forum, to the question presented in the second discussion forum; determine whether the at least one response comprises a good answer to the question based at least in part on behavior of one or more users that have each viewed the at least one response; and when the determination is that the at least one response in the second discussion forum comprises a good answer: present the good answer in the first discussion forum; and notify a user that the question has received a good answer, wherein the user submitted the question in the first discussion forum. | 1. A system for providing an answer to a question left unanswered in a discussion forum, the system comprising: a data store that stores data associated with a plurality of discussion forums, wherein each discussion forum comprises text corresponding to a discussion; and a computing device in communication with the data store and that is operative to: identify a question in a first discussion forum stored in the data store; determine that the first discussion forum does not include an answer to the question; determine a second discussion forum in which to present the question, wherein determining a second discussion forum in which to present the question comprises determining that the second discussion forum is more likely than the first discussion forum to result in an answer to the question; present the question in the second discussion forum based at least in part on the determination that the first discussion forum does not include an answer to the question; receive at least one response, in the second discussion forum, to the question presented in the second discussion forum; determine whether the at least one response comprises a good answer to the question based at least in part on behavior of one or more users that have each viewed the at least one response; and when the determination is that the at least one response in the second discussion forum comprises a good answer: present the good answer in the first discussion forum; and notify a user that the question has received a good answer, wherein the user submitted the question in the first discussion forum. 2. The system of claim 1 , wherein the computing device is further operative to determine at least one additional location in which to present the good answer, said at least one additional location comprising a location other than the first discussion forum and the second discussion forum. | 0.5 |
8,442,309 | 14 | 18 | 14. A computer system for method for learning a random multinomial logit (RML) classifier for scene segmentation, the system comprising: an image textonization module configured to: receive an image training set, wherein the image training set comprises multiple digital representations of images, and an object of an image of the image training set has a semantic label; and generate a plurality of texton images corresponding to the images in the image training set, wherein a texton image of its corresponding image in the image training set is an image of pixels, and wherein each pixel value in a texton image is replaced by a representation of the pixel value of its corresponding image in the image training set; a feature selection module configured to select one or more texture-layout features from the plurality of the texton images, wherein selecting one or more texture-layout features comprises swapping a feature currently being used by the RML classifier with a randomly selected new feature based on the statistical significance of the feature currently being used; and a RML classifier configured to: learn multiple multinomial logistic regression models of the RML classifier based on the selected texture-layout features; and evaluate the performance of the multiple multinomial logistic regression models based on the semantic labels of the objects in the image training set. | 14. A computer system for method for learning a random multinomial logit (RML) classifier for scene segmentation, the system comprising: an image textonization module configured to: receive an image training set, wherein the image training set comprises multiple digital representations of images, and an object of an image of the image training set has a semantic label; and generate a plurality of texton images corresponding to the images in the image training set, wherein a texton image of its corresponding image in the image training set is an image of pixels, and wherein each pixel value in a texton image is replaced by a representation of the pixel value of its corresponding image in the image training set; a feature selection module configured to select one or more texture-layout features from the plurality of the texton images, wherein selecting one or more texture-layout features comprises swapping a feature currently being used by the RML classifier with a randomly selected new feature based on the statistical significance of the feature currently being used; and a RML classifier configured to: learn multiple multinomial logistic regression models of the RML classifier based on the selected texture-layout features; and evaluate the performance of the multiple multinomial logistic regression models based on the semantic labels of the objects in the image training set. 18. The system of claim 14 , wherein a selected texture-layout feature from a texton image comprises a rectangle area of the texton image and a texton word. | 0.808354 |
7,788,711 | 11 | 12 | 11. The system of claim 8 , wherein the first artifact comprises a type code, a source identification, and an assertion identification. | 11. The system of claim 8 , wherein the first artifact comprises a type code, a source identification, and an assertion identification. 12. The system of claim 11 , wherein the first artifact further comprises a server identification. | 0.5 |
9,449,287 | 1 | 8 | 1. A method for predicting a personality of at least one human subject, the method comprising: receiving data associated with the at least one human subject from one or more sources; clustering the data based on one or more topics of interest of the at least one human subject using one or more topic modeling algorithms; predicting at least one high level personality trait associated with the at least one human subject by analyzing the clustered data, the at least one high level personality trait being one of one or more high level personality traits defined by a first model; and predicting at least one personality profile by classifying the at least one high level personality trait into one or more granular level personality traits defined by a second model, the classifying being based on clustered data, wherein at least one of the receiving data, the clustering the data, the predicting at least one first personality, and the predicting at least one second personality is performed by a processor. | 1. A method for predicting a personality of at least one human subject, the method comprising: receiving data associated with the at least one human subject from one or more sources; clustering the data based on one or more topics of interest of the at least one human subject using one or more topic modeling algorithms; predicting at least one high level personality trait associated with the at least one human subject by analyzing the clustered data, the at least one high level personality trait being one of one or more high level personality traits defined by a first model; and predicting at least one personality profile by classifying the at least one high level personality trait into one or more granular level personality traits defined by a second model, the classifying being based on clustered data, wherein at least one of the receiving data, the clustering the data, the predicting at least one first personality, and the predicting at least one second personality is performed by a processor. 8. The method of claim 1 , further comprising monitoring response of a user to the predicted at least one high level personality trait and the predicted at least one personality profile using self-learning techniques. | 0.747674 |
9,418,124 | 7 | 9 | 7. A system for processing a set of data records having time conflicts, the data records representing respective versions of an entity for which there can be only one preferred value at any given point in time, wherein each of the data records has an n-dimensional time record, the system comprising: one or more processors; and a memory comprising instructions which, when executed by the one or more processors, cause the one or more processors to: define a policy from among a plurality of candidate policies, said defined policy designed to resolve time conflicts between those data records having time conflicts; compare all data records in a cumulative, pair-wise fashion; identify time-based conflicts between pairs of records and identify time-conflicted pairs; determine which record in every time-conflicted pair of records is to be adjusted in accordance with said defined policy; adjust the time interval of every said determined record to be adjusted in accordance with said defined policy; and output a modified set of data records having said adjusted time intervals, wherein (i) said modified set of data records contains no time conflicts and (ii) said adjusted time intervals in the modified set of data records do not depend on the order in which the data records are processed by said computer-implemented method. | 7. A system for processing a set of data records having time conflicts, the data records representing respective versions of an entity for which there can be only one preferred value at any given point in time, wherein each of the data records has an n-dimensional time record, the system comprising: one or more processors; and a memory comprising instructions which, when executed by the one or more processors, cause the one or more processors to: define a policy from among a plurality of candidate policies, said defined policy designed to resolve time conflicts between those data records having time conflicts; compare all data records in a cumulative, pair-wise fashion; identify time-based conflicts between pairs of records and identify time-conflicted pairs; determine which record in every time-conflicted pair of records is to be adjusted in accordance with said defined policy; adjust the time interval of every said determined record to be adjusted in accordance with said defined policy; and output a modified set of data records having said adjusted time intervals, wherein (i) said modified set of data records contains no time conflicts and (ii) said adjusted time intervals in the modified set of data records do not depend on the order in which the data records are processed by said computer-implemented method. 9. The system of claim 7 , wherein said method is implemented as part of a parallel database system. | 0.787234 |
7,904,424 | 1 | 10 | 1. A method for managing document data used for reproducing a document the method comprising: in a case where second generation document data can be generated by replicating first generation document data that is original document data and (n+1)-th (n≧2) generation document data can be generated by replicating n-th generation document data, combining the first generation document data and child identification data in one unit, the child identification data indicating the second generation document data generated by replicating the first generation document data; combining k-th (N≧2) generation document data and parent identification data in one unit, the parent identification data indicating which of other (k−1)-th generation document data is replicated to generate the k-th generation document data; incorporating, into the unit where the first generation document data is combined, an event execution permission/denial determination program for implementing a determination portion that determines permission/denial of execution of an event relating to document data whose generation is younger than the second generation document data, and incorporating, into each of the units where the document data is combined, an information exchange program for implementing an information exchange portion that sends and receives information, and when the event relating to the k-th generation document data is executed, implementing, in a computer managing the k-th generation document data, the information exchange portion relating to the k-th generation document data by causing the computer to execute the information exchange program, implementing, in each computer managing document data that is in a direct line from the k-th generation document data and is older than the k-th generation document data, the information exchange portion relating to each piece of the older document data by causing each of the computers to execute the information exchange program, implementing, in a computer managing the first generation document data, the determination portion by causing the computer to execute the determination program, giving, to the determination portion implemented in the computer managing the first generation document data, a request to the effect that execution of the event relating to the k-th generation document data should be permitted, by causing each of the information exchange portions relating to each piece of the older document data to relay the request in a manner to deliver the request from the information exchange portion relating to the k-th generation document data to older generation document data based on parent attribute information, causing the determination portion to determine whether execution of the event relating to the k-th generation document data is permitted, and executing the event in a case where the determination portion determines that execution of the event relating to the k-th generation document data is permitted. | 1. A method for managing document data used for reproducing a document the method comprising: in a case where second generation document data can be generated by replicating first generation document data that is original document data and (n+1)-th (n≧2) generation document data can be generated by replicating n-th generation document data, combining the first generation document data and child identification data in one unit, the child identification data indicating the second generation document data generated by replicating the first generation document data; combining k-th (N≧2) generation document data and parent identification data in one unit, the parent identification data indicating which of other (k−1)-th generation document data is replicated to generate the k-th generation document data; incorporating, into the unit where the first generation document data is combined, an event execution permission/denial determination program for implementing a determination portion that determines permission/denial of execution of an event relating to document data whose generation is younger than the second generation document data, and incorporating, into each of the units where the document data is combined, an information exchange program for implementing an information exchange portion that sends and receives information, and when the event relating to the k-th generation document data is executed, implementing, in a computer managing the k-th generation document data, the information exchange portion relating to the k-th generation document data by causing the computer to execute the information exchange program, implementing, in each computer managing document data that is in a direct line from the k-th generation document data and is older than the k-th generation document data, the information exchange portion relating to each piece of the older document data by causing each of the computers to execute the information exchange program, implementing, in a computer managing the first generation document data, the determination portion by causing the computer to execute the determination program, giving, to the determination portion implemented in the computer managing the first generation document data, a request to the effect that execution of the event relating to the k-th generation document data should be permitted, by causing each of the information exchange portions relating to each piece of the older document data to relay the request in a manner to deliver the request from the information exchange portion relating to the k-th generation document data to older generation document data based on parent attribute information, causing the determination portion to determine whether execution of the event relating to the k-th generation document data is permitted, and executing the event in a case where the determination portion determines that execution of the event relating to the k-th generation document data is permitted. 10. The method according to claim 1 , further comprising in a case where a storage location of m-th generation document data is changed, wherein m≧2, updating the child identification data in line with a storage location after the change, the child identification data being combined in a unit along with document data that is in a direct line from the document data and one generation older than the document data, and updating the parent identification data in line with the storage location after the change, the parent identification data being combined in a unit along with document data that is in a direct line from the document data and one generation younger than the document data. | 0.5 |
5,479,487 | 18 | 27 | 18. An integrated telephone call handling system, comprising: a telephone line coupling said system with a telephone network to thereby allow communication between said system and parties via said network; a plurality of functional partitions within a common memory and under control of a common processor, said functional partitions capable of providing mechanized communication with said parties via said system and said network, said communication comprising data selected from the group consisting of: voice, text and image data; a plurality of agent workstations and agent telephones coupled to said system, said workstations and telephones capable of providing communication between agents and said parties via said system and said network; a unified controller within said system for controlling calls between said system and said parties, said unified controller (1) capable of transferring said calls among said functional partitions and agent workstations and telephones, (2) capable of directing communications between said parties and said functional partitions and (3) capable of directing communications between said system and said agent workstations and agent telephones, said unified controller including a unified script language operable to generate a voice script from inception to termination of said call, said voice script including a first script for directing interaction between said party and said functional partitions and a second script for directing interaction between said system and said agent. | 18. An integrated telephone call handling system, comprising: a telephone line coupling said system with a telephone network to thereby allow communication between said system and parties via said network; a plurality of functional partitions within a common memory and under control of a common processor, said functional partitions capable of providing mechanized communication with said parties via said system and said network, said communication comprising data selected from the group consisting of: voice, text and image data; a plurality of agent workstations and agent telephones coupled to said system, said workstations and telephones capable of providing communication between agents and said parties via said system and said network; a unified controller within said system for controlling calls between said system and said parties, said unified controller (1) capable of transferring said calls among said functional partitions and agent workstations and telephones, (2) capable of directing communications between said parties and said functional partitions and (3) capable of directing communications between said system and said agent workstations and agent telephones, said unified controller including a unified script language operable to generate a voice script from inception to termination of said call, said voice script including a first script for directing interaction between said party and said functional partitions and a second script for directing interaction between said system and said agent. 27. The system as recited in claim 18 further comprising means for means for controlling an external PBX. | 0.872573 |
8,099,663 | 4 | 5 | 4. The computer readable storage medium of claim 3 , wherein a key is associated with a node in a tree hierarchy and the node represents a document object corresponding to the key. | 4. The computer readable storage medium of claim 3 , wherein a key is associated with a node in a tree hierarchy and the node represents a document object corresponding to the key. 5. The computer readable storage medium of claim 4 , further comprising executable instructions to: read a destination document key from the changelist; identify a node in the destination document tree hierarchy that is associated with the destination document key; and remove the destination document object represented by the node from the destination document. | 0.5 |
10,019,491 | 17 | 23 | 17. A non-transitory, computer program product comprising code stored therein and executable by one or more processors to cause machine learning in the selection of a ranked response to a structured data input having a natural language processing output schema received from a requesting device, wherein the code is executable to cause the one or more data processors to: receive the structured data input, wherein the structured data input includes filtering parameters for conversion into response template filtering criteria; convert the filtering parameters into the response template filtering criteria; query a library of response templates to identify candidate response templates that meet the response template filtering criteria to filter the response templates; receive a selection of the candidate response templates that meet the response template filtering criteria and respond to the structured input data, wherein the candidate response templates include static data; operate a ranking engine to rank the selection of candidate response templates in accordance with ranking criteria; select a highest ranked candidate response template to provide a response to a device; derive the response to the structured data input from the selected, highest ranked, candidate response template; provide the response to a recipient device; and provide feedback to the ranking engine to refine the ranking criteria. | 17. A non-transitory, computer program product comprising code stored therein and executable by one or more processors to cause machine learning in the selection of a ranked response to a structured data input having a natural language processing output schema received from a requesting device, wherein the code is executable to cause the one or more data processors to: receive the structured data input, wherein the structured data input includes filtering parameters for conversion into response template filtering criteria; convert the filtering parameters into the response template filtering criteria; query a library of response templates to identify candidate response templates that meet the response template filtering criteria to filter the response templates; receive a selection of the candidate response templates that meet the response template filtering criteria and respond to the structured input data, wherein the candidate response templates include static data; operate a ranking engine to rank the selection of candidate response templates in accordance with ranking criteria; select a highest ranked candidate response template to provide a response to a device; derive the response to the structured data input from the selected, highest ranked, candidate response template; provide the response to a recipient device; and provide feedback to the ranking engine to refine the ranking criteria. 23. The non-transitory, computer program product of claim 17 wherein the ranking criteria comprises a function of a conversion rate of each of the candidate response templates that distributes the highest conversion rate ranking among candidate response templates to allow the machine to learn about each of the candidate response templates. | 0.597877 |
7,853,574 | 6 | 7 | 6. The computer readable storage medium of claim 5 , wherein the instructions to analyze a future event further comprises instructions to analyze a past event associated with the user to determine the contextual setting. | 6. The computer readable storage medium of claim 5 , wherein the instructions to analyze a future event further comprises instructions to analyze a past event associated with the user to determine the contextual setting. 7. The computer readable storage medium of claim 6 , further comprising instructions to analyze at least one of a past event of the user, a future event of the user, and personal information of the user to generate a dynamic interest profile for the user and wherein the instructions to dynamically generate the search query comprises instructions to extract data from the dynamic interest profile and the contextual setting to generate the search query. | 0.5 |
8,280,734 | 19 | 22 | 19. A non-transitory computer-readable storage medium having computer-readable instructions, wherein the computer-readable instructions when executed on a computer cause the computer to: commence a title acquisition mode; receive an utterance representing a title during the title acquisition mode; convert the utterance into a series of textual characters, wherein the textual characters represent a lingual translation of the utterance; store the series of textual characters representing the title in memory; automatically commence a recording mode a predetermined time after the title acquisition mode is commenced; receive a body of a recording during the recording mode; store the body of the recording in the memory; and automatically link the series of textual characters to the body of the recording in the memory to title the body of the recording. | 19. A non-transitory computer-readable storage medium having computer-readable instructions, wherein the computer-readable instructions when executed on a computer cause the computer to: commence a title acquisition mode; receive an utterance representing a title during the title acquisition mode; convert the utterance into a series of textual characters, wherein the textual characters represent a lingual translation of the utterance; store the series of textual characters representing the title in memory; automatically commence a recording mode a predetermined time after the title acquisition mode is commenced; receive a body of a recording during the recording mode; store the body of the recording in the memory; and automatically link the series of textual characters to the body of the recording in the memory to title the body of the recording. 22. The non-transitory computer-readable storage medium of claim 19 , wherein the predetermined length of title acquisition mode is user-configurable. | 0.84787 |
9,307,003 | 1 | 2 | 1. A method for prefetching at a proxy server based on root node identification for a requested HTTP object at the proxy server, the method comprising: receiving a request for an HTTP object; determining, using a computing system, a plurality of candidate root nodes for the requested HTTP object, each candidate root node comprising an object that may have caused the request for the HTTP object; for each candidate root node: determining a likelihood that the respective candidate root node is the root node that caused the request for the HTTP object, and associating, at the computing system proxy server, the determined likelihood with the candidate root node; selecting one of the candidate root nodes from the plurality of candidate root nodes based on the determined likelihoods for each of the candidate root nodes; and establishing the selected candidate root node as the root node for the requested HTTP object. | 1. A method for prefetching at a proxy server based on root node identification for a requested HTTP object at the proxy server, the method comprising: receiving a request for an HTTP object; determining, using a computing system, a plurality of candidate root nodes for the requested HTTP object, each candidate root node comprising an object that may have caused the request for the HTTP object; for each candidate root node: determining a likelihood that the respective candidate root node is the root node that caused the request for the HTTP object, and associating, at the computing system proxy server, the determined likelihood with the candidate root node; selecting one of the candidate root nodes from the plurality of candidate root nodes based on the determined likelihoods for each of the candidate root nodes; and establishing the selected candidate root node as the root node for the requested HTTP object. 2. The method of claim 1 wherein identifying a plurality of candidate root nodes comprises identifying a first node of the plurality of candidate root nodes from a referrer tag as a first potential candidate root node. | 0.5 |
8,527,480 | 16 | 17 | 16. The system of claim 15 wherein the vNode manager component is configured to: generate a new ancestor vNode representing the ancestor of the modified first object and the parent of the shareable object, wherein the new ancestor vNode includes versioning information associated with the next version of the structured document; and store the new ancestor vNode in the data store along with a vNode representing the ancestor of the first version of the structured document. | 16. The system of claim 15 wherein the vNode manager component is configured to: generate a new ancestor vNode representing the ancestor of the modified first object and the parent of the shareable object, wherein the new ancestor vNode includes versioning information associated with the next version of the structured document; and store the new ancestor vNode in the data store along with a vNode representing the ancestor of the first version of the structured document. 17. The system of claim 16 wherein the vNode manager component is configured to update the vNode representing the sharable object by adding information identifying the new ancestor vNode as an additional parent vNode of the updated vNode, wherein by including the information identifying the new ancestor vNode, the updated vNode is shared across the first version and the next version of the structured document. | 0.5 |
8,395,966 | 11 | 13 | 11. A system comprising: an interface to receive seismic data acquired by seismic sensors of a composite seismic signal produced by the firings of multiple seismic sources; and a processor to process the seismic data to: model the seismic data based at least in part on models for the sources and linear operators; jointly determine the models based at least in part on the modeling and at least one constraint specifying an interdependency between at least two of the models, wherein the at least two models are different; and based at least in part on the determined models, generate a dataset representing a component of the composite seismic signal attributable to one of the seismic sources. | 11. A system comprising: an interface to receive seismic data acquired by seismic sensors of a composite seismic signal produced by the firings of multiple seismic sources; and a processor to process the seismic data to: model the seismic data based at least in part on models for the sources and linear operators; jointly determine the models based at least in part on the modeling and at least one constraint specifying an interdependency between at least two of the models, wherein the at least two models are different; and based at least in part on the determined models, generate a dataset representing a component of the composite seismic signal attributable to one of the seismic sources. 13. The system of claim 11 , wherein the seismic sources are fired simultaneously. | 0.753012 |
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